bluuebunny/crossref_metadata_2025 huggingface dataset:
Existing Assistive Techniques for Dyslexics
Authors: Singh Kulwinder , Goyal Vishal , Rana Parshant
Published: August 2021

Reading is an essential skill for literacy development in children. But it is a challenge for children with dyslexia because of phonological-core deficits. Poor reading skills have an impact on vocabulary development and to exposure to relevant background knowledge. It affects the ability to interpret what one sees and hears or the ability to link information from different parts of the brain. Dyslexic children face many challenges in their educational life due to reading difficulty. Support to dyslexic children include computer-based applications and multi-sensory methods like text-to-speech and character animation techniques. Some applications provide immediate reading intervention facility. Automatic speech recognition (ASR) is a new platform with immediate intervention for assisting dyslexic children to improve their reading ability. Findings contribute to develop a suitable approach to correct the reading mistakes of dyslexic children. Speech recognition technology provides the most interactive environment between human and machine.
Optimization of Machine Learning Models for Early Diagnosis of Autism Spectrum Disorder
Authors: Allam Mohan , Nandhini M. , Thangadarshini M.
Published: August 2021

Autism spectrum disorder is a syndrome related to interaction with people and repetitive behavior. ASD is diagnosed by health experts with the help of special practices that can be prolonged and costly. Researchers developed several ASD detection techniques by utilizing machine learning tools. ML provides the advanced algorithms that build automatic classification models. But disease prediction is a challenge for ML models due to the majority of the medical datasets including irrelevant features. Feature selection is a critical job in the predictive modeling for selecting a subset of significant features from the dataset. Recent feature selection techniques are using the optimization algorithms to improve the prediction rate of classification models. Most of the optimization algorithms make use of several controlling parameters that have to be tuned for improved productivity. In this chapter, a novel feature selection technique is proposed using binary teaching learning-based optimization algorithm that requires standard controlling parameters to acquire optimum features from ASD data.
Recent Trends and Repercussions in Civil and Criminal Justice Systems
Authors: Parikh Mitsu , Krishna V. S.
Published: August 2021

The reform of civil and criminal justice systems is a contentious issue and has become the top priority for the international community in re-establishing the rule of law. The justice systems in many common law jurisdictions are perceived to be ‘in crisis' deformed by exorbitant delay, cost, and complexity in proceedings. The level of resources engulfed in the judicial system has very little or no impact on judicial performance. Comparative and comprehensive analysis of the law not only leads to a better realization of the foreign laws, but also it aids with law unification. This chapter will attempt to highlight the issues in the civil and criminal justice system and comparatively analyze the scenario in England, Singapore, and India. In furtherance, the authors explore the possible methods to curb the delay in justice systems and canvas the modern trends in civil and criminal justice policy.
Approaches of Early Detection of Autism Spectrum Disorders
Authors: Papaefstathiou Elpis
Published: August 2021

Due to the heterogeneity of ASD population, many difficulties emerge when it comes to diagnosis of the disorder and even more difficulties regarding early detection. Specifically, early detection enables diagnosis to be made before the span of 24-30 months, the age where the official diagnosis is usually made. As it is known, earlier diagnosis is very crucial as children with ASD can benefit more from programs of early intervention. Taking all these into account, a brief review of the most popular approaches for early detection of ASD would be elaborated in order to raise awareness to health care professionals, clinicians, and parents. Moreover, in this chapter, the pros and the cons of each approach would be elaborated, and in the final part, some recommendations would be made concerning the process of early detection.
Autism Spectrum Disorder and the Paradigm of Neurodiversity
Authors: Folostina Ruxandra , Dragomir Alexandra Andreea
Published: August 2021

The new approaches for disability are characterized through respect towards the beneficiary. In practice, this means empowering the person with a disability or an association that fights for the rights to make choices about their personal life. Empowering a person with disabilities, trusting their potential, and encouraging them to look with optimism towards the future are just a few of the aspects of change. Involving the person in making decisions for themselves and promoting those changes that have an impact on the quality of life also has a pragmatic side in the sense that it requires considerable expenses. Several debates for child's rights and people's with disabilities rights proposed the definition of “rights for a future” (Crețu, 2006). The freedom of choice does not only represent a topic from the individualized intervention plan, but additionally refers to taking responsibility, taking ownership for what the person with a disability agreed with.
Bullying and Autism Spectrum Disorder
Authors: Golu Florinda , Gutu Smaranda M.
Published: August 2021

Across schools, bullying under all of its forms (e.g., physical, verbal, relational, cyber) is a concerning phenomenon. Prevalence studies suggest that children with ASD are a particularly vulnerable population. Specifically, children with ASD are at a considerably higher risk of being bullied than their peers with other or no special educational needs. This chapter aims to examine in what way bullying occurs in ASD populations and what particular challenges individuals with ASD have to deal with. More specifically, the chapter describes and discusses key points in the existing literature on bullying and autism spectrum disorder, such as (1) types of bullying, (2) causes and determining factors, (3) risk and protective factors, (4) consequences of bullying, (5) prevention strategies and interventions where the transition to recommendations is made through thorough research specifically applied to this topic in order to provide theory and evidence-based practices for educators, teachers, school counselors, parents, and any other interested party.
Mental Disorders in Children and Adolescents With Autism
Authors: Filiou Areti-Eirini
Published: August 2021

Children and adolescents with autism frequently have symptoms of various mental disorders along with the features that define autism. Problems with anxiety, depression, emotion regulation, cognitive problems, and associated behavioural problems occur in children with autism of all ages. Overall, high rates of several psychiatric disorders have been reported in individuals with autism. Several authors have suggested cognitive and behaviour therapy (CBT) as a very useful intervention therapy, which can apply in schools, in order to help these children with autism and mental health disorders. It is also important the use of information and communications technology (ICT) and other computer programs to support students with autism in education. Therefore, with a coordinated effort to use this intervention program, schools have an opportunity to address the goals of improving social, emotional, and behavioural competence for these students and minimising the impact of established emotional, behavioural, or educational disorders.
Representation of Autism Spectrum Disorder in Greek Cinema
Authors: Kanaveli Eliana , Syriopoulou-Delli Christine K.
Published: August 2021

The chapter examines the representation of autism spectrum disorder (ASD) in Greek cinema and its possible pedagogical effect. The qualitative method of discourse analysis was applied to investigate these issues in four short Greek films, two of which were documentaries in each of which the protagonist was a child or young person with ASD. Preliminary analysis revealed space and gender as the dominant factors used by the filmmakers to depict ASD. The research findings show that this disorder, which is relatively unknown for the Greek public, is represented in the films as dissimilarity from the norm, and people with ASD are depicted as the “others” of this society, with isolation of themselves and their families. Certain positive aspects of ASD were also portrayed, but there is a need for more positive images of ASD to raise public awareness. The cinema could play a pedagogical role in this process and help in the social integration of people with ASD.
Prospect of Promoting Sikkim as a Smart Tourism Destination
Authors: Dam Supriya
Published: August 2021

Since 2006, Sikkim progressively switching to a full-fledged tourism-centred state having declared it a predominant industry as an engine for its economic growth. The state accounted for the highest influx of foreign tourists amongst the eight north eastern states of India during the last 20 years or so. The smart city mission was commissioned by government of India as a centrally sponsored scheme destined to provide financial support for the allotted cities to the extent of INR. 100 Crore per city per year spanning over five years. Studies suggest that induction of smart city concept will act as precursor for growth of smart tourism destinations (STDs) across the country. The STD as a concept revolves around “6A's,” an essential ingredient for promoting smart tourism in destinations. Incidentally, two cities in Sikkim have been enlisted amongst the top 100 cities in India for promoting smart city, instrumental in promoting STD in tourism-driven states. The chapter delves into the concept of smart city as an antecedent for promoting STD along with conditions with respect to Sikkim.
Technology Gap
Authors: Rana Ritu , Sharma Manoj , Singh Ajay
Published: August 2021

This chapter extends the authors' previous research work in which an examination of causality was conducted between foreign direct investment (FDI), economic growth (GDP), and the environment (CO2 emissions and energy consumption [EC]) in the Indian context. Two more important variables (i.e., trade openness and technology gap) were also added. The chapter further examines the effects of information and communication technology (ICT) trade on both GDP and the environment of India. The results of previous model show that FDI is neither causing GDP nor is it bridging the technology gap. The results also indicate the existence of pollution haven hypothesis (PHH) in India as FDI is causing both CO2 and EC. Also, FDI is, though not causing the GDP directly, doing so indirectly through CO2 validating the existence of PHH. FDI is causing trade openness in India, but that openness is again causing more FDI, which is doing no good for India. The results of ICT trade model indicate that both GDP and ICT exports cause CO2 in India. Also, both the GDP and ICT exports are consuming energy in India.
Eco-Innovation and IT Technologies for Sustainable Development of Health and Recreational Tourism of Serbia
Authors: Djukic Gordana Petar , Biljana Ilic S. , Milovanović Goran R.
Published: August 2021

The aim of the chapter is to point the importance of eco-innovation and IT technologies for the sustainable development of health and recreational tourism in Serbia. The subject of the research is the rehabilitation center in Eastern Serbia. The main idea of the chapter is to show how those hospital institutions use artificial intelligence-IT technologies for improving recovery services to patients in the post-COVID condition. The chapter will discuss the most common types of support and measures to facilitate the functioning of eco-tourism in Serbia with the aim to adopt good practices of developed countries (Hungary). Ecological tourism takes place in areas of pure and preserved nature. The contribution of the chapter is to point to new strategies in spa tourism, to shorten the time and reduce business costs. This would contribute to the sustainability of tourism.
Investigation of Green Criteria With Clustering Analysis in Green Supplier Selection
Authors: Taş Mehmet Ali , Akcan Serap
Published: August 2021

Green supplier selection has a crucial importance for businesses. In the past, the selection of suppliers was solely based on conventional criteria such as cost, quality, and flexibility whereas expectations of businesses transformed in today's world on grounds of raised environmental awareness, public pressure, and regulations. Alternatives called green suppliers sensitive to the environment, preserving the ecological balance, managing wastes, and preventing pollution increased in value. This study analyzes practices on the selection of green suppliers. The articles between 2014 and 2021 were analyzed from the perspective of green criteria. The green criteria in the 50 articles determined are divided into 28 groups. With the k-means algorithm, these criteria groups are divided into four clusters, which was aimed to analyze the usage frequency of green criteria. This study is intended to contribute to green supplier selection practices in academia and industry in the future.
Distributed Energy Resource Management System Based on Discrete Event Simulation
Authors: Šinko Simona , Kragelj Dušan , Radić Ivana , Gajšek Brigita , Kramberger Tomaž , Rupnik Bojan
Published: August 2021

Nowadays, there is more and more discussion about Industry 4.0. The introduction of which could result into growing larger power consumption in a world. On the other side, some parts of Industry 4.0 can help to reduce energy consumption with the use of smart grid, internet of things, renewable energy, etc. The future of energy seems to be in the distributed energy resources (DER). The chapter presents the use of DER on the example of hospital, which are considered as the biggest consumer of energy in commercial sector. Because of important role of understanding the energy consumption, there is an emphasis on the energy modeling and analysis. The chapter provides a new approach in the modelling of energy with the discrete even simulation in which energy is presented by logistics packages, where every package presents a unit of energy. Basic analyses that can be made with the model are presented.
Life Cycle Energy Assessment of a Typical Marble Processing Plant
Authors: Prajwal Bhargav , Mali Harlal S. , Nagar Ravindra
Published: August 2021

This article describes how marble is one of the most important stone resources in terms of durability. It is aesthetically pleasing, and a decorative material used by many architects, as well as plays an important role in the economy of India. Most of the marble processing activities are performed by small and medium scale industries (SMEs) not only in India but worldwide. These industries have low efficiency and productivity due to lack of new technologies, high productivity cost and a lack of proper sustainable waste management systems, thereby increasing the waste generated during the processing stage. There is a significant need within the sector for increasing production efficiency, combined with the need of a substantial reduction in waste generated that can be achieved by endorsing technological innovations. This is in addition to following best available processing practices, incorporating energy saving technologies and modernizing the sectors management and organization structure which will substantially increase efficiency as well as production. This article provides a systematic approach for assessing the current energy and present environment status of a typical SME processing units of Rajasthan area, and proposes measures for meeting cleaner production principles. An evaluation methodology was developed considering the realistic plant operation scenarios. The total energy inputs for processing the products with their appropriate environmental indices like CO2 emissions were calculated. Alternatively, the CO2 emissions were also calculated by Gabi educational software for different industries and the best way of reducing the energy consumption is suggested by following alternate source of energy.
Renewable Energy Distribution and Management in Green Buildings
Authors: Kumar Suman , Kaur Gurjit
Published: August 2021

There are various environmental problems (i.e., “global warming,” air and water pollution), which need to be prevented. Construction of buildings plays a significant role in pollution. To reduce the harmful effects in constructing buildings, it is necessary to move on to sustainable architecture. In this chapter, different advantages and standards for green buildings will be discussed. Different organizations are contributing towards a green environment. There are even different sensors that are able to detect wastage of energy and can predict the requirement of energy. Machine learning, a hot topic these days, can also play its role in demand prediction. In this chapter, role of network communication and sensing to optimize the energy of green buildings and machine learning-based demand prediction to optimize the energy of green buildings are discussed. Further predicting energy harvesting from weather forecasts, return on investment of green buildings, and potential benefits of energy-efficient green buildings are also discussed.
Digitalization of the Development of the Fuel and Energy Balance of Russia's Northern Territories
Authors: Elyakova Izabella , Elyakov Aleksandr
Published: August 2021

The urgency of the energy budget research practice in the Republic of Sakha (Yakutia) on settlements with software for effective formation, implementation, management, monitoring, analysis, evaluation, rapid response, and strategic management of the entire complex of the energy budget is substantiated. The chapter reveals the lack of problems of unified methodology for the development of the energy budget and the use of different fundamentals of its preparation. The necessity of using digital technologies to develop a control system for a complex network of production and consumption of fuel and energy resources is rationalized.
Renewable Energy Policy in Africa and Policy Options for Sustainability
Authors: Lemba Isata Teixeira , Ferreira Dias Marta , Robaina Margarita
Published: August 2021

The aim of this research is to propose actions for energy policy aimed at the inclusion of renewable energy sources for Namibe, Angola. The chapter begins by describing the barriers that have been encountered in other countries in the same policy path. Renewable energy opportunities and potentialities are also described for the Namibe province. Finally, the energy policy proposal for the Namibe province is exposed, based on some experiences that have achieved positive results in other countries.
Calculation of Receipt of Renewable Energy Resources and Operation Modes of Power Plants
Authors: Babaev Baba Dzhabrailovich , Panchenko Vladimir , Kharchenko Valeriy Vladimirovich
Published: August 2021

The main objective of the work is to develop principles for the formation of the optimal composition of the energy complex from all the given power plants based on renewable energy sources for an autonomous consumer, taking into account the variable energy loads of the consumer, changing climatic conditions and the possibility of using local fuel and energy resources. As a result of solving this optimization problem, in addition to the optimal configuration of the power complex, it is also necessary to solve the problem of optimizing the joint operation of different types of power plants from the selected optimal configuration, that is, it is necessary to determine the optimal modes of operation of power plants and the optimal share of their participation in providing consumers at every moment in time. A numerical method for analyzing and optimizing the parameters and operating mode of the energy complex with the most accurate consideration of the schedule of changes in consumer load and software that automates the solution of this optimization problem are also presented.
Countries Progress in Solar PV in Support of NDC Implementation and Contribution to Achieving SDG7
Authors: Senshaw Dereje Azemraw , Edwards Alexander
Published: August 2021

This case study examines the progress being made by 12 least developed countries (LDCs) in their effort to achieve Sustainable Development Goal 7 (SDG7) – access to clean and sustainable energy for all. Focusing on solar photovoltaics (PV), the authors look at what can be done to further the spread of renewable energy, and the role various actors have to playing in helping these countries to meet SDG7. Furthermore, with countries on the cusp of submitting their revised contributions under the Paris Agreement, they look at the role solar PV can play in helping LDCs to participate in taking action against climate change. After outlining the current policy landscape, and efforts being made within these countries, they look at the obstacles, opportunities, and the role of solar PV going forward. They also look at the steps that policymakers, both national and international, can take to encourage the rapid uptake of renewable energy in developing nations.
The Cultural and Institutional Barrier of Knowledge Exchanges in the Development of Open Source Software
Authors: Maulana Ikbal
Published: August 2021

Open source software (OSS) gives developing countries inexpensive or free alternatives to proprietary software. It gives them the opportunity to develop software and software industry without starting from scratch. This chapter discusses the diffusion and development of OSS in Indonesia especially after the government took “Indonesia, Go Open Source” (IGOS) initiative. This initiative united government organizations, communities, R&D institutions, and universities. While the government's concern was to tackle piracy by replacing illegal software with OSS, the others sought to develop their own OSS. However, the openness of their software is only in terms of that they were developed using OSS development tools, while their mode of development remained closed, which was caused by cultural barrier and institutional incompatibility between government's regime of project administration and the governance of OSS development.
Critical Barriers to Business Intelligence Open Source Software Adoption
Authors: Poba-Nzaou Placide , Uwizeyemungu Sylvestre , Saada Mariem
Published: August 2021

Over the past few years, managers have been hard pressed to become more data-driven, and one of the prerequisites in doing so is through the adoption of Business Intelligence (BI) tools. However (1) the adoption of BI tools remains relatively low (2) the acquisition costs of proprietary BI tools are relatively high and (3) the level of satisfaction with these BI tools remain low. Given the potential of open source BI (OSBI) tools, there is a need for analyzing barriers that prevent organizations from adopting OSBI. Drawing a systematic review and a Qualitative Survey of BI Experts, this study proposes a framework that categorizes and structures 23 barriers to OSBI adoption by organizations including 4 that were identified by BI Experts but not explicitly found in the literature. This paper contributes to OSS and Information Systems (IS) research literature on BI adoption in general and provides specific insights to practitioners.
Application of Quality in Use Model to Evaluate the User Experience of Online Banking Software
Authors: Abu Talib Manar , Alsaafin Areej , Medjden Selma Manel
Published: August 2021

Open source software (OSS) has recently become very important due to the rapid expansion of the software industry. In order to determine whether the quality of the software can achieve the intended purposes, the components of OSS need to be assessed as they are in closed source (conventional) software. Several quality in-use models have been introduced to evaluate software quality in various fields. The banking sector is one of the most critical sectors, as it deals with highly sensitive data; it therefore requires an accurate and effective assessment of software quality. In this article, two pieces of banking software are compared: one open source and one closed source. A new quality in use model, inspired by ISO/IEC 25010, is used to ensure concise results in the comparison. The results obtained show the great potential of OSS, especially in the banking field.
Using Design of Experiments to Analyze Open Source Software Metrics for Change Impact Estimation
Authors: Dahane Miloud , Abdi Mustapha Kamel , Bouneffa Mourad , Ahmad Adeel , Basson Henri
Published: August 2021

Software evolution control mostly relies on the better structure of the inherent software artifacts and the evaluation of different qualitative factors like maintainability. The attributes of changeability are commonly used to measure the capability of the software to change with minimal side effects. This article describes the use of the design of experiments method to evaluate the influence of variations of software metrics on the change impact in developed software. The coupling metrics are considered to analyze their degree of contribution to cause a change impact. The data from participant software metrics are expressed in the form of mathematical models. These models are then validated on different versions of software to estimate the correlation of coupling metrics with the change impact. The proposed approach is evaluated with the help of a set of experiences which are conducted using statistical analysis tools. It may serve as a measurement tool to qualify the significant indicators that can be included in a Software Maintenance dashboard.
Efficient Computation of Top-K Skyline Objects in Data Set With Uncertain Preferences
Authors: Sukhwani Nitesh , Kagita Venkateswara Rao , Kumar Vikas , Panda Sanjaya Kumar
Published: August 2021

Skyline recommendation with uncertain preferences has drawn AI researchers' attention in recent years due to its wide range of applications. The naive approach of skyline recommendation computes the skyline probability of all objects and ranks them accordingly. However, in many applications, the interest is in determining top-k objects rather than their ranking. The most efficient algorithm to determine an object's skyline probability employs the concepts of zero-contributing set and prefix-based k-level absorption. The authors show that the performance of these methods highly depends on the arrangement of objects in the database. In this paper, the authors propose a method for determining top-k skyline objects without computing the skyline probability of all the objects. They also propose and analyze different methods of ordering the objects in the database. Finally, they empirically show the efficacy of the proposed approaches on several synthetic and real-world data sets.
Performance Evaluation of Machine Learning for Recognizing Human Facial Emotions
Authors: Adel Alti , Farid Ayeche
Published: August 2021

Facial expression recognition is a human emotion classification problem attracting much attention from scientific research. Classifying human emotions can be a challenging task for machines. However, more accurate results and less execution time are still the issues when extracting features of human emotions. To cope with these challenges, the authors propose an automatic system that provides users with a well-adopted classifier for recognizing facial expressions in a more accurate manner. The system is based on two fundamental machine learning stages, namely feature selection and feature classification. Feature selection is realized by active shape model (ASM) composed of landmarks while the feature classification algorithm is based on seven well-known classifiers. The authors have used CK+ dataset, implemented and tested seven classifiers to find the best classifier. The experimental results show that quadratic classifier (DA) provides excellent performance, and it outperforms the other classifiers with the highest recognition rate of 100% for the same dataset.
A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Virtualized Cloud Environment
Authors: Aliyu Muhammad , Murali M.  , Gital Abdulsalam Y. , Boukari Souley , Kabir Rumana , Musa Maryam Abdullahi , Zambuk Fatima Umar , Shawulu Joshua Caleb , Umar Ibrahim M.
Published: August 2021

As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modification so as to enhance its potential. An optimized dynamic scheme that combined several algorithms' characteristics was proposed to map out such a challenge. The hybridized proposed scheme involved the meta-heuristic swarm mechanism of ant colony optimization (ACO) and deterministic spanning tree (SPT) algorithm as it obtained faster convergence chain, ensured resource utilization in least time and cost. Extensive experiments conducted in cloudsim simulator provided an efficient result in terms of minimized makespan time and throughput as compared to SPT, round robin (RR), and pre-emptive fair scheduling algorithm (PFSA) as it significantly improves performance.
Evaluation of Economic Security of Water Resources and Analysis of Influencing Factors
Authors: Peng Licheng , Ma Xiaowei , Ma Wanwan , Zhou Yuanxiang
Published: August 2021

To effectively evaluate the level of economic security of water resources (WES) in China and analyze its influencing factors, a comprehensive evaluation model of WES and a regression analysis model of influencing factors are established based on the panel data of 30 provinces in China from 2011 to 2017. It is found that, first, WES in China presents a fluctuating upward trend. Second, different regions have different economic security levels for their water resources in China, among which WES in the central region is the highest. Third, there is a U-shaped correlation between economic development and WES, and the population, pollution control level, technological innovation have negative impacts on WES. Moreover, this study also finds that with upgrades to the industrial structure and level of human capital, there will be improvements to WES. However, the external coefficient and the investment scale of fixed assets have a negative impact on the economic security of water resources. This is helpful to utilize the water resources, and improve the water resources safety management.
Soil biological attributes in monoculture and integrated systems in the Cerrado region of Piauí State, Brazil
Authors: Cunha João Rodrigues da , Freitas Rita de Cassia Alves de , Souza Djalma Junior de Almeida Taveres , Gualberto Adriano Veniciús Santana , Souza Henrique Antunes de , Leite Luiz Fernando Carvalho
Published: August 2021

The implementation of integrated agricultural production systems is considered a promising strategy for sustainable agricultural intensification in Brazil. This study aimed to evaluate the effects of different monoculture and integrated production systems on the microbiological attributes and organic carbon of soil from the Cerrado region in Piauí, Brazil. Soil samples were collected from the 0.0-0.10-m layer in the following systems: no-tillage (PD), pasture (PAS), exclusive eucalyptus cultivation (CEE), integrated livestock-forest system (IPF) and a native Cerrado (CN) area, which was used as reference. Total organic carbon (TOC) and nitrogen (NT) contents, microbial biomass carbon (CMIC), microbial respiration (MR), microbial quotient (qMIC), metabolic quotient (qCO2), as well as the activities of the hydrolysis of fluorescein diacetate (FDA), acid phosphatase, β-glucosidase and urease enzymes were evaluated. High TOC contents were found in the CEE, IPF and PAS systems, and high CMIC and qMIC values were found in the CN and CEE systems. The variables MR, qCO2 and enzymatic activity varied as a function of the management systems. The IPF and CEE systems caused improvements in the soil attributes, with increases in organic carbon and microbial biomass. The IPF integrated production system promoted improvements in the microbiological indicators of soil quality and was considered an environmentally sustainable agricultural production system. The transition from CN to agricultural areas caused changes in the soil microbiological indicators, which were perceived several years after anthropogenic intervention, indicating that even with the adoption of conservation systems, it was not possible to reestablish the soil microbial biomass.
Effect of the planting season on carrot cultivars growth and yield in the brazilian semiarid region
Authors: Gomes Victor Emmanuel de Vasconcelos , Grangeiro Leilson Costa , Ferreira Núbia Marisa , Lacerda Rodolfo Rodrigo de Almeida , Almeida Antônio Fabrício de , Silva Jorge  Luiz Alves da
Published: August 2021

In regions with high temperatures, carrot cultivation is impracticable, as high temperatures tend to reduce yield and quality of the product. However, with the advent of summer cultivars, carrot cultivation in these regions has become viable. The aim of this work was to evaluate the performance of ten carrot cultivars in different planting seasons. The experiments were carried out at the Rafael Fernandes Experimental Farm of the Federal Rural Semiarid University (UFERSA). The experiments were carried out in May, June, July and August of 2017. The experimental design was a randomized block with ten treatments and four repetitions. The characteristics that were evaluated were the root classification (long, average and short roots); commercial, non-commercial and total yield; dry plant weight and root fresh weight. Both the planting season and the cultivar played important roles in agronomic performance throughout the experimental period. In May and June, the highest average yields and plant growth were obtained (43 and 45 t ha-1 yield, respectively). Hybrid cultivars showed better performance than open-pollinated cultivars in terms of yield. The Brasília, BRS Planalto, and Kuronan varieties showed poor performance in all the evaluated characteristics.
Seed priming improves Salvia hispanica L. seed performance under salt stress
Authors: Costa Ana Alessandra da , Paiva Emanoela Pereira de , Torres Salvador Barros , Pereira Kleane Targino de Oliveira , Leite Moadir de Sousa , Sá Francisco Vanies da Silva
Published: August 2021

Salvia hispanica L. is an alternative crop cultivated by farmers who want to diversify their production. However, this species is sensitive to salinity, which affects its germination negatively. Seed priming with different attenuators is a technique with potential to mitigate the effects of salt stress. Thus, the objective of this study was to evaluate the effect of seed priming with the use of different attenuators on the germination, growth, and organic solute accumulation of S. hispanica seedlings under salt stress. The experimental design was completely randomized, with treatments distributed in a 4 × 5 factorial scheme, corresponding to four seed priming treatments and five osmotic potentials, with four replicates of 50 seeds in each treatment. The seed treatments consisted of presoaking seeds for 4h in salicylic acid, gibberellic acid, and distilled water and the control treatment, which did not involve soaking. These seeds were germinated at osmotic potentials of 0.0, -0.1, -0.2, -0.3, and -0.4 MPa, using NaCl as an osmotic agent to simulate the different salinity levels. Among all the treatments implemented, S. hispanica seed priming with salicylic acid was the most efficient in mitigating the salt stress effects.
Using Response Surface Methodology to evaluate the effect of pequi flour, and pulp and by-product on sweet bread development
Authors: Cunha Mariana Crivelari da , Cunha Marília Crivelari da , Lago Rafael Carvalho do , Melo Rafaela da Silva , Almeida Letícia Casarine , Pereira Joelma , Alves José Guilherme Lembi Ferreira , Carvalho Elisângela Elena Nunes , Vilas Boas Eduardo Valério de Barros
Published: August 2021

In this work, the effect of wheat flour and water replacement by pequi pulp and flour on the bread development and preparation enriched with this fruit was studied. Two experimental designs were used for two independent variables, the first evaluating the wheat flour partial replacement by pequi husk flour (x1) and pequi pulp flour (x2). The second design evaluated the wheat flour and water partial replacement by pequi husk flour (x1) and pequi pulp (x2), respectively. At the same time, a control test was conducted (without the addition of pequi flour and pulp) for comparison. The evaluated dependent variables of the bread quality characteristics were: dough volume; expansion rate; specific volume and density; texture profile and gluten content. It was possible to verify that only the gluten content was influenced by the replacement of wheat flour by pequi husk flour, whereas, only the specific volume was influenced by the replacement of water by pequi pulp. In general, the best replacement range was obtained with the formulation using between 0.75 to 2.5% pequi husk flour; up to 20% pequi pulp flour and between 5 and 35% of pequi pulp.
Using the Ultrasonic Method for the Defectoscopy of Failures in Reinforced Concrete Columns
Authors: Hrabová Kristýna , Hüblová Sabina , Cikrle Petr , Vymazal Tomáš
Published: August 2021

Using non-destructive diagnostic methods is currently important not only with regard to preserving existing structures but also with regard to sustainable development, which is getting more and more to the forefront of attention. This paper deals with defectoscopy of a reinforced concrete column made with artificially created defects corresponding to the defects in real structures. Modern diagnostic methods enable detailed determination of the properties of structures and detection of their critical points. A method which appears to be very promising in detecting defects and failures is the ultrasonic method. It enables monitoring the development of failures at different levels of loading. Besides that, permanent deformation will also be monitored during the loading using a strain gauge.
Static Reservoir Modeling Comparing Inverse Distance Weighting to Kriging Interpolation Algorithm in Volumetric Estimation. Case Study: Gullfaks Field
Authors: Otchere Daniel Asante , Hodgetts David , Ganat Tarek Arbi Omar , Ullah Najeeb , Rashid Alidu
Published: August 2021

Understanding and characterizing the behaviour of the subsurface by combining it with a suitable statistical method gives a higher level of confidence in the reservoir model produced. Interpolation of porosity and permeability data with minimum error and high accuracy is, therefore, essential in reservoir modeling. The most widely used interpolation algorithm, kriging, with enough well data is the best linear unbiased estimator. This research sought to compare the applicability and competitiveness of inverse distance weighting (IDW) method using power index of 1, 2 and 4 to kriging when there is sparse data, due to time and budget constraints, to calculate hydrocarbon volumes in a fluvial-deltaic reservoir.

Interpolation results, estimated from descriptive statistics, were insignificant and showed similar prediction accuracy and consistency but IDW with power index of 1 indicated the least error estimation and higher accuracy. The assessment of hydrocarbon volume calculations also showed a marginal difference below 0.08 between IDW power index of 1 and kriging in the reservoir zones. Reservoir segments cross-validation and correlation analysis results indicate IDW to have no significant difference to kriging with absolute errors of 3% for recoverable oil and 0.7% for recoverable gas. Grid upscaling, which usually causes a loss of geological features and extreme porosity values, did not impact the results but rather complemented the robustness of IDW in both fine and coarse grid upscale.

With IDW exhibiting least errors and higher accuracy, the volumetric and statistical results confirm that when there are fewer well data in a fluvial-deltaic reservoir, the suitable spatial interpolation choice should be IDW method with a power index of 1.
Pipe Conveyed NMR Logging Secures Successful Reservoir Characterization in a Low Resistivity Pay
Authors: Romero Rojas Pedro , Tagarieva Larisa , Mohamed Said , Belloul Mohand Arezki , Chen Chao , Boushari Mohammed , Nwab Mahdi , Al-Hindi Khaled , Manzo Jesus
Published: August 2021

The Middle Burgan formation in North Kuwait is very challenging: its limited vertical thickness and overall low resistivity require complex and special operations for drilling, formation evaluation and completion to ensure optimum production. The objective of this case study is to demonstrate the value of Nuclear Magnetic Resonance (NMR) log data to provide rock quality and fluid typing in this challenging environment, where conventional logs are not enough for reservoir understanding along a horizontal well.

A horizontal 6 1/8" section was drilled through the Middle Burgan formation with oil-based mud and Gamma Ray, Resistivity, Density data were acquired while drilling, and data from the latest generation of multifrequency, focused NMR wireline tool (FMR), conveyed on pipe (PCL). Water saturation computation in low resistivity pay often exceeds the real value when computed using conventional logs. In this environment, NMR logging proved to be essential for the proper reservoir characterization and to support critical decisions on well completion design. Fundamental rock quality and permeability profiles were supplied by NMR. Oil saturation was identified by applying the 2D-NMR methods, Diffusion vs. T2, or DT2 maps.

Despite the presence of washouts, high quality NMR data was obtained at different depths of investigation in the horizontal well section. Integrating the NMR data with conventional well logs helped advanced reservoir characterization, in reducing the uncertainty in formation evaluation by clearly identifying pay and shale zones, and furthermore, in providing necessary information to support management decisions regarding fracking design to maximize oil production.

The formation evaluation and well objectives were met with the aid of the high-quality NMR log data. The multifrequency capability of the tool allows data acquisition at different depths of investigation which helped to overcome the negative effects of washouts in the data interpretation. A remarkable well performance and high productivity from the low resistivity, thin reservoir layers, is expected based on decisions made from the by very reliable well log data interpretation.
On the Likelihood of Encountering Design Conditions During Heavy Transport - A Case Study of 56 Replicate Voyages From Korea to the Suez Canal
Authors: Hodapp David , den Breejen Stephan , Pniewski Tomasz , Wang Hai Ming , Lin Zhen
Published: August 2021

A critical element in heavy transport design is the identification of design wave conditions. Since most transports are one-of-a-kind, statistically meaningful comparisons of observed vs. design conditions are nonexistent. The present paper examines the experience from a recent oil and gas giga-project, encompassing 56 replicate voyages from Korea to the Suez Canal. In doing so, this paper provides an anchor point for assessing the real-world likelihood of exceeding design wave conditions during heavy transport.

Voyage maximum wave conditions from the 56 replicate voyages are found to closely follow a Weibull distribution, allowing for the ready evaluation of observed 1-in-N voyage extremes. These observed wave conditions are compared with corresponding design values on both a year-round and seasonal (3-month) basis. Three important observations are drawn from these comparisons. First, operating limits established by heavy transport contractors to avoid waves above a predetermined threshold do not eliminate the need to design for higher wave conditions. Over the 56 replicate voyages studied, observed wave conditions slightly exceeded the contractor's self-imposed operating limit (i.e., by approximately 10% or less) on five separate voyages; on a sixth voyage, this same operating limit was exceeded by approximately 40%. Second, simplified tools for evaluating design wave conditions using Global Wave Statistics do not consistently estimate the 1-in-10 voyage extreme. While the simplified approach is shown to be conservative for the route studied, the associated design margin varies considerably throughout the year. Third, SafeTrans voyage simulations are observed to well-predict the 1-in-10 voyage extreme for the route studied.
Drilling Optimization Applying Machine Learning Regression Algorithms
Authors: Marquez Freddy J.
Published: August 2021

Machine Learning is an artificial intelligence subprocess applied to automatically and quickly perform mathematical calculations to data in order to build models used to make predictions. Technical papers related to machine learning algorithms applications have being increasingly published in many oil and gas disciplines over the last five years, revolutionizing the way engineers approach to their works, and sharing innovating solutions that contributes to an increase in efficiency.

In this paper, Machine Learning models are built to predict inverse rate of penetration (ROPI) and surface torque for a well located at Gulf of Mexico shallow waters. Three type of analysis were performed. Pre-drill analysis, predicting the parameters without any data of the target well in the database. Drilling analysis, running the model every sixty meters, updating the database with information of the target well and predicting the parameters ahead the bit. Sensitivity parameter optimization analysis was performed iterating weight on bit and rotary speed values as model inputs in order identify the optimum combination to deliver the best drilling performance under the given conditions.

The Extreme Gradient Boosting (XGBoost) library in Python programming language environment, was used to build the models. Model performance was satisfactory, overcoming the challenge of using drilling parameters input manually by drilling bit engineers. The database was built with data from different fields and wells. Two databases were created to build the models, one of the models did not consider logging while drilling (LWD) data in order to determine its importance on the predictions.

Pre-drill surface torque prediction showed better performance than ROPI. Predictions ahead the bit performance was good both for torque and ROPI. Sensitivity parameter optimization showed better resolution with the database that includes LWD data.