bluuebunny/crossref_metadata_2025 huggingface dataset:
Correlation between Grading Histopathology and Sentinel Lymph Node Metastasis in Early Breast Cancer in University of Sumatera Utara Hospital
Authors: Hermansyah Dedy , Pricilia Gracia , Azrah Arjumardi , Rahayu Yolanda , Paramita Desiree A. , Siregar Edwin S.
Published: August 2021

BACKGROUND: Breast cancer is a malignancy in breast tissue from the duct or lobar epithelium. American Joint Committee on Cancer has specified important prognostic factors such as primary tumor size, regional lymph node status, and distant metastasis. Axillary lymph node status has been one of the most reliable prognostic factors in early breast cancer in women. Axillary lymph node dissection is an old method to identify metastasis in axillary lymph nodes and started being replaced by sentinel lymph node biopsy (SLNB). SLNB has been introduced as a minimal invasive procedure, but in Indonesia, this procedure cannot be done due to technology limitation. Grading tumor is one of the predictor factors that can predict lymph node metastasis. This predictor factor has been associated with sentinel lymph node metastasis significantly.

AIM: According to this, we conduct this study to analyze the correlation between grading histopathology in breast cancer with sentinel lymph node metastasis to lower false-negative rate in SLNB using methylene blue dye.

MATERIALS AND METHODS: In this study, we included 51 patients that qualified using inclusion and exclusion criteria. Then, sentinel lymph node metastasis and grading histopathology data were retrieved from the patient’s medical record. This data are analyzed using SPSS with Chi-square test.

RESULTS: The most type of breast cancer in this study is invasive ductal carcinoma was found in 40 patients (78.4%). There are 22 of 51 patients (51.6%) with metastasis to sentinel lymph node, have Grade 3 in histopathologic findings.

CONCLUSIONS: The statistical evaluation showed that there is significant correlation between grading histopathology and SLNB with p = 0.001.
Nicotiana rupicola sp. nov and Nicotiana knightiana (Paniculatae, Solanaceae), a new endemic and a new record for the flora of Chile
Authors: Santilli Ludovica , Pérez Maria Fernanda , de Schrevel Claire , Dandois Philippe , Mondaca Hector , Lavandero Nicolás
Published: August 2021

Nicotiana knightiana is recorded for the first time for the flora of Chile. A new species of Nicotiana, endemic to the coast of the Coquimbo region is described and illustrated. Molecular analysis placed the new species within the section Paniculatae, as sister to Nicotiana cordifolia, endemic to Juan Fernandez islands. The new species can be considered critically endangered (CR) according to the IUCN categories for its restricted and fragmented distribution, small population number, and the threat that urbanization and mining activities represent for the conservation of the biodiversity of the area.
Distribution of macroalgae in the area of Calvi (Corsica)
Authors: Katz Lea , Sirjacobs Damien , Gobert Sylvie , Lejeune Pierre , Danis Bruno
Published: August 2021

Macroalgae play a structuring role in benthic ecosystems, which makes it very important to monitor their cover rates and study their community structures and changes in time. Such studies are usually led by autonomous divers and often do not generate sufficient data to provide enough material for strategically-sound conservation plans. This paper describes the dataset generated in the framework of the evaluation of the potential of a complementary data acquisition method: annotating videos transects obtained using an underwater Remotely Operated Vehicle (ROV).

The focus was on Cystoseira brachycarpa, together with the abundance of several other macroalgae species, which could be identified using the ROV images after validation through specimen identification. Furthermore, in order to allow future uses, such as monitoring the status of colonisation of the invasive algae Caulerpa cylindracea, the ROV was sent to some deeper transects on sedimentary habitats (40 m) below the Posidonia meadows lower limits.

The project, while providing some interesting insights on using a ROV as a tool to study marine biodiversity, generated a dataset for the distribution of 19 macroalgae on both standardised and new transects in the Bay of Calvi (Katz et al. 2021). The observed species of macroalgae included: Acetabularia acetabulum, Amphiroa rigida, Caulerpa prolifera, Caulerpa cylindracea, Codium bursa, Colpomenia sinuosa, Corallinales (order), Cystoseira brachycarpa, Cystoseira crinita, Cystoseira spinosa, Cystoseira zosteroides, Dictyota (genus), Flabellia petiolata, Halopteris (genus), Halopteris scoparia, Jania (genus), Osmundaria volubilis, Padina pavonica and Peyssonnelia squamaria.

The videos also showed that the invasive algae Caulerpa cylindracea has spread between 2016 and 2019 and that more focused studies should be held in the Bay to assess the actual reach and possible impacts of this invasion.

Finally, our ROV video transects have also underlined the significant presence of particular benthic macroalgae communities over habitat zones described as "soft-bottom" on benthic habitat maps. Although the biomass per unit area of these communities is probably lower than for most coastal rocky bottoms, this widely-spread habitat type holds a contribution to primary production to be considered in coastal ecosystem models.
Benthic habitat mapping of Plazh Gradina – Zlatna ribka (Black Sea) and Karpathos and Saria Islands (Mediterranean Sea)
Authors: Nikolopoulou Stamatina , Berov Dimitar , Klayn Stefania , Dimitrov Lyubomir , Velkovsky Kiril , Chatzinikolaou Eva , Chatzigeorgiou Giorgos , Karamfilov Ventzislav , Pavloudi Christina
Published: August 2021

Habitat mapping is nеcessary for the efficient conservation and protection of marine ecosystems. In addition, it is a requirement for EU Member States as stated in the European Union (EU) Habitats Directive (92/43/EEC), as well as necessary for the achievement and maintenance of 'good environmental status (GES)' of benthic marine habitats in the framework of the EU Marine Strategy Framework Directive (2008/56/EC).

This study provides baseline information on the marine benthic habitats of Sozopol Bay (Black Sea) and Karpathos and Saria Islands (Mediterranean Sea). These two Natura 2000 sites were selected as study sites of the RECONNECT project, which aimed at creating a transnational cooperative network to confront the environmental threats of ecosystems with a high natural and cultural interest, by the establishment of common practices and a joint regional strategy. The specific objective was to map the marine habitats using a defined a priori classification (EUNIS), with the ultimate purpose of supporting government marine spatial planning, management and decision-making processes through the development of a Decision Support System.
Understanding rider:horse bodyweight ratio trends, weight management practices and rider weight perceptions within leisure and amateur riders in the UK
Authors: Challinor C.L. , Randle H. , Williams J.M.
Published: August 2021

Horse riders in the UK have a legal responsibility for the welfare of the horses in their care, outlined by the Animal Welfare Act (2006). Understanding weight management factors that influence rider: horse bodyweight (RHBW) ratio is key to safeguarding horse welfare as human obesity rates increase. Recent high-profile incidents have seen riders being asked to dismount for being too heavy, demonstrating an awareness of the possible impact of excessive rider weight, threatening the equestrian industry’s social licence to operate. This study investigated RHBW trends within the UK leisure and amateur rider population to understand rider perception of ‘ideal’ RHBW and factors influencing rider and horse weight management. An online survey (SurveyMonkey®) was distributed via UK equine-related Facebook™ groups and collected information on horse and rider demographics, rider weight management strategies and respondents’ views on the importance of rider weight on horse welfare. Kruskal-Wallis analyses with Mann Whitney U post-hoc tests identified whether differences in respondent views differed between RHBW groups. A total of 971 riders completed the survey; respondents were aged between 18-65+ years old and 88% (n=953) were experienced riders. RHBWs were calculated for 764 (79%) of respondents as 21.2% (n=206) did not know either their own and/or their horses’ weight. Weight tapes (44.5%; n=432) and weigh bridges (29.5%; n=286) were common horse weight estimation methods. RHBWs ranged from 4.9% to 21.88%, mean: 12.5%±2.7%. Riders with lower RHBW thought about their own weight less and measured their horses’ weight less often than those with higher ratios (P<0.005, P<0.0004, respectively). The majority of riders who participated were weight conscious and recognised potential detrimental impacts associated with increased rider weight. Development of RHBW guidelines supported by equestrian governing bodies would highlight the need for riders to consider the impact of weight and support them in choosing suitable horses.
Effect of 1-week Calendula officinalis consumption before high-intensity interval exercise on some delayed onset muscle soreness (DOMS) elements in male rowers
Authors: Mohammadi B. , Anoosheh L. , Rahmati-Ahmadabad S.
Published: August 2021

Previous studies showed that some medicinal herbs can prevent delayed onset muscle soreness (DOMS). The present study investigates the effect of Calendula officinalis supplementation on DOMS elements on male rowers. Thirty healthy adult male rowers were randomly chosen and equally divided into experimental and control groups. Blood samples, Sargent jumps (SJ), and pain perception tests were measured at the starting point. The experimental group consumed (twice a day, 200 μl each time) C. officinalis extract for a week while the control group received a placebo. After consuming the supplementations for a week, the second samples and tests were taken. All the athletes participated in the high-intensity interval exercise (HIIE – a muscle soreness protocol). Third, fourth, and fifth samples/tests were executed immediately, 24 and 48 h after HIIE. Statistical analysis was conducted and P≤0.05 was considered as the significant level. The results showed that HIIE induced a significant increase in the serum tumour necrosis factor-alpha (TNF-α) and creatine kinase-MB (CK-MB) values as well as the pain perception in both groups. TNF-α and pain perception were significantly lower in the experimental group immediately, 24 and 48 h after HIIE. CK-MB activity was significantly decreased in the experimental group during next 24 and 48 h after HIIE. The muscle soreness protocol and its preceding supplementation had no significant effect on SJ. The present study suggests that the consumption of C. officinalis based on the present study dose and timespan may be effective to attenuate inflammation and pain induced by HIIE in male rowers and probably has no functional impact on muscle.
Error analysis of forced discrete mechanical systems
Authors: Fernández Javier , Zurita Sebastián Elías Graiff , Grillo Sergio
Published: August 2021

The purpose of this paper is to perform an error analysis of the variational integrators of mechanical systems subject to external forcing. Essentially, we prove that when a discretization of contact order \begin{document}$ r $\end{document} of the Lagrangian and force are used, the integrator has the same contact order. Our analysis is performed first for discrete forced mechanical systems defined over \begin{document}$ TQ $\end{document}, where we study the existence of flows, the construction and properties of discrete exact systems and the contact order of the flows (variational integrators) in terms of the contact order of the original systems. Then we use those results to derive the corresponding analysis for the analogous forced systems defined over \begin{document}$ Q\times Q $\end{document}.
SKUPINE ČIMBENIKA I NJIHOV UTJECAJ NA VAŽNE ŽIVOTNE ODLUKE: BESKUĆNICI U PULI
Authors: Kostelić Katarina , Peruško Emanuel
Published: August 2021

GROUPS OF FACTORS AND THEIR INFLUENCE ON IMPORTANT LIFE DECISIONS: THE HOMELESS IN PULA The socially unfavorable status of the homeless is still not sufficiently supported by risk-reduction measures of homelessness in Croatia, which indicates the need for additional research of aggravating factors and development of prevention measures. Based on a review of current knowledge about the homeless, two opposing approaches are observed: the homelessness as a result of a set of circumstances and the homelessness as one’s own choice. The approach used in this paper is a combination of the above and refers to the review of groups of influencing factors and their role in respondents’ decision-making that preceded the situation of homelessness. The aim of this paper is to set the theoretical basis for investigation of influential factors in the context of decision-making that preceded homelessness and to present the results of exploratory research based on the purposive sampling (users of the »Homeless Shelter of the Red Cross Pula«). The questionnaire and semi-structured interviews were used for obtaining self-reported data based on respondents’ recollections of situations in which they made relevant socioeconomic decisions in their lives. The results indicate that the respondents’ homelessness situation was preceded by decision-making with a combination of at least three influential factors from different groups of aggravating influences. The observed regularities are the basis for further research. Key words: homelessness, influences on decision-making, individual factors, strudtural factors
Integrating the Webinar as a Tool to Support Adult Training: A Case Study on the Training for Entrepreneurs of SMEs in Thailand
Authors: Ariya Pakinee , Intawong Kannikar , Puritat Kitti
Published: August 2021

The COVID-19 pandemic has presented significant challenges for the education and training sector. We could have witnessed the rise of technology for webinars which are tools to deliver training and education through video and audio communication in the form of distance learning for instructors and participants. How-ever, commercial webinars such as zoom or webex may lack a management system for organizing the amount of participants for long term courses. The present study aimed to develop a webinar tool for the context of adult training for entrepreneurs of SMEs in Thailand. In order to develop a webinar tool, we proposed a general framework which consisted of three stages. The requirement stage aimed to explore the baseline survey from 411 participants and summarize the feature list of the webinar. The development stage employed the kanban methodology to develop each feature list and proposed the architecture of the system. Finally, the evaluation stage compares two groups of 110 participants between our webinar approach and zoom application with statistics of attendance regarding those who attended the course and also contains a satisfaction survey. The results show that the important feature to engage participants in long term courses were system notifications and the availability of a web-based platform for providing easy access to webinar.
Web-Based Learning Under Tacit Mining of Various Data Sources
Authors: Belazoui Abdelouahab , Telli Abdelmoutia , Arar Chafik
Published: August 2021

Nowadays, many platforms provide open educational resources to learners. So, they must browse and explore several suggested contents to better assimilate their courses. To facilitate the selecting task of these resources, the present paper proposes an intelligent tutoring system that can access teaching contents available on the web automatically and offers them to learners as additional information sources. In doing so, the authors highlight the description logic approach and its knowledge representation strength that underwrites the modulization, inference, and querying about a web ontology language, and enhanced traditional tutoring systems architecture using ontologies and description logic to enable them to access various data sources on the web. Finally, this article concludes that the combination of machine learning with the semantic web has provided a supportive study environment and enhanced the schooling conditions within open and distance learning.
Influence of Entrepreneurship Education on Employment Quality and Employment Willingness
Authors: Jia Chunxu , Zuo Jialin , Lu Wei
Published: August 2021

The entrepreneurship education of college students is an educational practice to train comprehensive talents with entrepreneurship qualities, who are willing and confident of employment and could conform to the needs of social development. Focusing on the entrepreneurship education of ordinary college students, this paper probes deep into the status quo of entrepreneurship education among college students, and thoroughly analyzes how this education model influences the employment quality and employment willingness of college students. The results show that: a good entrepreneurship education obviously enhances the employment quality of college students, and apparently boosts their employment willingness; entrepreneurship education guides the cognition of college students through multiple means, and promotes their employment ability. The research lays the basis for active exploration into to employment quality and employment willingness of college students.
Systematic Review of Enhancement of Artificial Bee Colony Algorithm Using Ant Colony Pheromone
Authors: Alaidi Abdul Hadi , Soong Der Chen S , Weng Leong Yeng
Published: August 2021

The artificial bee colony (ABC) is a well-studied algorithm developed to solve continuous function optimization problems by Karboga and Akay in 2009. ABC has been proven to be more effective than other biological-inspired algorithms with good exploration. However, ABC suffers from low exploitation and slow convergence in some cases. The ABC algorithm study has risen significantly over the past decade, with many researchers trying to improve ABC performance and apply it to solve problems. One method to enhance ABC is to borrow exploration technique from other algorithms. Researchers use pheromone, which is a technique used by Ant Colony optimization algorithm, to enhance ABC and addressed several aspects of using a pheromone to enhance the ABC. This systematic review aims to review and analysis articles about using pheromone to enhance ABC. Articles on related topics were systematically searched in four major databases namely Scopus, Web of Science, Association for Computing Machinery ACM and Google Scholar. To ensure that all research articles were considered the start date is not restrictions the search carry out till February 2021.Five articles were selected based on our inclusion and exclusion criteria for the systematic review. The results show that the use Pheromone to enhance ABC can increase the ABC exploitation ability and overcoming the late convergence. This paper also illustrates several potential pheromone using for future work.
Using Machine Learning via Deep Learning Algorithms to Diagnose the Lung Disease Based on Chest Imaging: A Survey
Authors: Taha Ahmed Shaymaa , Malallah Kadhem Suhad
Published: August 2021

— Chest imaging diagnostics is crucial in the medical area due to many serious lung diseases like cancers and nodules and particularly with the current pandemic of Covid-19. Machine learning approaches yield prominent results toward the task of diagnosis. Recently, deep learning methods are utilized and recommended by many studies in this domain. The research aims to critically examine the newest lung disease detection procedures using deep learning algorithms that use X-ray and CT scan datasets. Here, the most recent studies in this area (2015-2021) have been reviewed and summarized to provide an overview of the most appropriate methods that should be used or developed in future works, what limitations should be considered, and at what level these techniques help physicians in identifying the disease with better accuracy. The lack of various standard datasets, the huge training set, the high dimensionality of data, and the independence of features have been the main limitations based on the literature. However, different architectures of deep learning are used by many researchers but, Convolutional Neural Networks (CNN) are still state-of-art techniques in dealing with image datasets.
Mobile Application to Detect Covid-19 Pandemic by Using Classification Techniques: Proposed System
Authors: Al-zubidi Azhar , F. AL-Bakri Nadia , K. Hasoun Rajaa , Hassan Hashim Soukaena , Alrikabi Haider Th.Salim
Published: August 2021

Various mobile applications such as Mobile Health (mHealth) have been developed and spread across the world which has played an important role in mitigating the Coronavirus pandemic (COVID-19). As the COVID-19 pandemic spreads, several people have drawn parallels to influenza. While both viruses cause respiratory infections, they propagate in very different ways. This has a major impact on the public health measures that can be used to fight each virus. These viruses are pandemic-causing in the same way. That is, they both cause respiratory disease, and can present themselves in several ways, ranging from asymptomatic to severe and deadly. A proposal is presented in this paper that uses two algorithms to define and classify these pandemics, they are: The Back Propagation (BP) classification algorithm and the Fuzzy C-Mean (FCM) clustering algorithm. Two stages are implemented in the proposed system: in the first step, the FCM algorithm is used to find out the type of virus, and this algorithm is capable of handling ambiguous features of viruses. In the second step, a BP neural network is used as a classifier to detect the pandemic class. The proposed system was trained and tested using a well-known dataset (covid-19 vs influenza). Information Gain (IG) is used to optimize the related features that affect the classification process to improve speed and accuracy.  The proposed mobile application is developed to support users easily detecting the COVID-19 infection by inputting the medical tests as significant features to the proposed system. The proposed system's accuracy is up to (89%), the framework was created using the Matlab programming environment and an Android Studio for Mobil application designing.
Intelligent Security Schema for SMS Spam Message Based on Machine Learning Algorithms
Authors: Alshahrani Ali
Published: August 2021

SMS spam messages represent one of the most serious threats to current traditional networks. These messages have been particularly prevalent overseas and are harmful to various types of devices. The current filtering scheme employed in conventional systems is unable to expose a large number of messages. To resolve this issue, a new intelligent security system is proposed to reduce the number of spam messages. It can detect novel spam messages that have a direct and negative impact on networks. The proposed system is heavily based on machine learning to explore various types of messages. The primary achievement of our study is the increase in the accuracy ratio as well as the reduction in the number of false alarms. According to the experimental results, it is clear that our system can realize outstanding results, detecting a massive number of massages.
Computational Thinking and Robotics
Authors: Munn Carol
Published: August 2021

This chapter explores a unique framework that expresses freshness and innovation within revolutionary learning experiences. The chapter focuses on the implementation of computational thinking skills as an essential element of a robotics education program that was driven by hands-on activities instilling the notion of imagination through innovative projects. Engineering design applications with robotics created an atmosphere in which students applied abstract mathematics and science concepts. The robot and its technology imploding in the field of education created excitement in the minds of students with renewed, revitalized interest, and curiosity stretching across the areas of science, technology, engineering, and mathematics (STEM). Robotics education along with computational thinking skills are primary keys for unlocking the unlimited creative and innovative potential with engaging hands-on activities. Robots, a fascinating learning instrument, rejuvenate, animate, and revive 21st century skills in tech-savvy language familiar with today's students.
Frameworks for Integration of Future-Oriented Computational Thinking in K-12 Schools
Authors: Garrigan Scott R.
Published: August 2021

Computational thinking (CT) K-12 curricula and professional development should prepare students for their future, but historically, such curricula have limited success. This chapter offers historical analogies and ways that CT curricula may have a stronger and more lasting impact. Two frameworks are central to the chapter's arguments. The first recalls Seymour Papert's original description of CT as a pedagogy with computing playing a formative role in young children's thinking; the computer was a tool to think with (1980, 1996). This “thinking development” framework emphasized child-centered, creative problem solving to foster deep engagement and understanding. Current CT seems to include creativity only tangentially. The second framework encompasses emergent machine learning and data concepts that will become pervasive. This chapter, more prescriptive than empirical, suggests ways that CT and requisite professional development could be more future-focused and more successful. It could be titled “Seymour Papert meets Machine Learning.”
Design and Development of an Instructional Program for Teaching Programming Processes to Gifted Students Using Scratch
Authors: Durak Hatice Yıldız , Güyer Tolga
Published: August 2021

This chapter examines practical applications of an educational program designed to teach Turkish gifted second, third, and fourth grade students programming using Scratch, an online programming website (https://scratch.mit.edu). This qualitative research study was conducted with gifted identified students in an elementary school in Ankara's Altındağ district. Qualitative data collection methods were used. The study found program strengths included practical orientation, student independence, student free expression, computer literacy, and interdisciplinary connections. Additionally, providing a variety of tools and equipment, using Scratch, having a course web site, and on-line resource sharing were also seen as strengths by the participants. Perceived weaknesses were technical difficulties, the limited number of course hours, some of Scratch's negative features, inadequate help at particular points, and negative situations caused by gender and grade level differences. Results indicate preliminary knowledge of participant computer literacy as important to programming success.
Spatial Thinking as a Path Towards Computational Thinking
Authors: Ham Derek Allen
Published: August 2021

Considering what we know about computational thinking, how much of this cognitive domain hangs on one's ability to think spatially? Is spatial thinking a hidden foundational property for developing strong computational thinking skills? If coding is the new literacy for 21st century thinking, educators must diversify their methodology of instruction. Mathematics must not be the only pathway to computational thinking, computer science, and coding. This book chapter opens up new insight into spatial reasoning, showing it as a new viable method to give students the computational thinking skills necessary to thrive in STEM fields. Finally, this chapter presents concepts found in shape grammars as a methodology used to teach students how to approach art and design computationally. With shape, grammars we find computational thinking at the center of creative activities.
The Use of 3D Technologies to Support Computational Thinking in STEM Education
Authors: Angelopoulos Panagiotis , Balatsoukas Alexandros , Nistor Adina
Published: August 2021

Computational thinking (CT) is increasingly emerging as a thinking skill to support the development of 21st century skills such as critical thinking, creativity, collaboration, or technology literacy, essential for students to become successful in an increasingly complex society. Educators are always looking for new strategies for developing these skills in students. Three-dimensional (3D) printing and scanning technologies are sufficiently mature and economically accessible to be used at the school level. By using 3D technologies, students explore, invent, discover, and engage in real problems and situations. This study explores the use of 3D printing technologies in a secondary school in Athens over the course of two school years. The study investigates if 3D technologies can support the development of CT skills in students.
Blockchain and Green Networking Analytics in 5G Networks and Beyond
Authors: Light Janet
Published: August 2021

The objective of green networking is to minimize greenhouse gas emissions while maintaining the same level of performance. Green networking refers to all processes used to optimize networking and inter-networking functions to make it more energy efficient. Green networking concepts can be extended to cover any method that reduces latency, save bandwidth, and/or decrease computation time, as a reduction in these factors invariably leads to power savings. These savings can directly translate into lowering greenhouse gas emissions and reduce computing's carbon footprint and its impact on the environment. Energy-awareness is critical in the networking infrastructure, especially in wireless 5G networks and beyond. Research on blockchain for 5G wireless networks is still in its infancy. But it is obvious that blockchain will significantly uplift the shape and experience of future mobile applications and services. Identifying the green networking analytics will lead to sustainable energy policy planning for the future.
A Comparative Study on Symmetric and Asymmetric Key Encryption Techniques
Authors: Padhiar Sneha , Mori Kuldip Hiralal
Published: August 2021

With the rise in use of internet in various fields like education, military, government sector, banking, the security and privacy of the info has been the foremost concern. As in today's era, most of the handling of data and transactions are done online. When the data is transferred from the one end of sender to the other end of receiver online, it's eavesdropped by an intruder and thus could be a threat to the secrecy or confidentiality of the info. The hottest technique that protects the confidentiality of the data is cryptography which converts the plain text into scrambled form which is unreadable. Then the receiver applies a reverse mechanism to decrypt the unreadable data to readable form. This mechanism is known as encryption-decryption process or cryptography. Cryptography can be both symmetric and asymmetric. Here the authors discuss symmetric and asymmetric algorithms.
Design, Control, Management, and Performance Analysis of PV-Battery Supercapacitor DC-System Using Buck Converter
Authors: Amara Yasmine , Tebri Zoulikha , Larabi Zina
Published: August 2021

The intermittent nature of photovoltaic energy necessitates the incorporation of storage devices to ensure the continuality of loads feeding. In addition, it is important to model, control, and verify the operating of the designed system before implementation. Furthermore, the integration of power electronic interfaces plays a significant role in protecting the system and benefiting from solar energy. To this end, a buck converter is chosen to charge the battery and supply the supercapacitor. The control strategy is based on the maximum power point tracking techniques when the management algorithm recommends MPPT function mode. Otherwise, a feedback constant voltage PI controller is designed. Indeed, perturb and observe and incremental conductance are implemented and compared to analyze the system efficiency within the management strategy to charge the battery, switch between the controllers, and feed a supercapacitor in case of full battery charge. The obtained results using MATLAB/SIMULINK platform confirm the behaviour of the proposed strategy.
True Power Loss Reduction by Enhanced Tree Squirrel Search, Enhanced Salp Swarm, and Swim Bladder Operation-Based Shark Optimization Algorithms
Authors: Kanagasabai Lenin
Published: August 2021

In this chapter, enhanced tree squirrel search optimization algorithm (ETSS), enhanced salp swarm algorithm (ESS), and swim bladder operation-based shark algorithm (SBS) have been applied to solve the power loss reduction problem. Enhanced tree squirrel search optimization algorithm (ETSS) utilizes the jumping exploration method and progressive exploration technique—both possess winter search strategy—in order to preserve the population diversity and to perk up the convergence speed. A new-fangled winter exploration strategy is implemented in the jumping exploration technique. In enhanced salp swarm algorithm (ESS) an inertia weight ω∈ [0, 1] is applied, which picks up the pace of convergence during the period of exploration. Then swim bladder operation-based shark algorithm (SBS) is proposed to solve the problem. Based on contracting and expanding actions of the swim bladder in shark, SBS algorithm has been modelled.
Operation and Startup of Three-Phase Grid-Connected PWM Inverter for an Experimental Test Bench With DSPACE Real-Time Implementation of PQ Control
Authors: Elyaalaoui Kamal , Labbadi Moussa , Chigane Khalid , Ouassaid Mohammed , Cherkaoui Mohamed
Published: August 2021

The main objective of this chapter is the experimental validation of active and reactive power control at the connection point for a three-phase grid connected inverter. It gives an overview on the adopted vector control strategy, regulation of the angle of orientation of the blades (pitch control), synchronization grid side converter to the power network using phase closed loop (PLL). Once the experimental test bench is described, the authors devote a first part to the design of the block circuit diagram of the experimental platform and the control strategy implemented in the DSPace DS1104, and they suggest some steps to associate the inverter to the electrical network. Subsequently, they discuss the experimental results validating the proposed power control. The purpose of this experimental results is the DSPACE real-time implementation of PQ control using three-phase inverter and development of a startup algorithm of the experimental test bench.
Flying Capacitor Inverter Integration in a Renewable Energy System
Authors: Hamida Mohamed Lamine , Fekik Arezki , Denoun Hakim , Ardjal Aghiles , Bokhtache Aicha Aissa
Published: August 2021

This chapter presents a three-cell flying capacitor converter photovoltaic (PV) system. This system consists of a DC-DC boost power converter connected in series with a multicell inverter. The perturb and observe MPPT technique has been used to extract the maximum power from the solar panel and generate the duty signal to control the switch of the DC-DC converter. The three-cell flying capacitor inverter ensures the conversion of the output voltage of the boost chopper to the alternative voltage. This topology is made up of hybrid association of commutation cells, which makes it possible to share the voltage constraint on several switches. A closed loop control based on PWM has been proposed to control the capacitor voltages of the inverter. The output current is controlled using a PI regulator. The aim of the proposed three cell inverter is to produce an approximate sinusoidal output current with a very low THD. The simulation results assess the effectiveness of the control.
Complex Trauma
Authors: Parker Susan Wuchenich
Published: August 2021

Defining trauma is an individualized process that includes looking at events, experiences, and effects. Best practices explicitly state the importance of an individual's experiences when defining trauma. Therefore, solely utilizing a professional lens for discussion is often inappropriate. The purpose of this chapter is to examine trauma and trauma-informed care through both a professional and personal lens. Research on outcomes for children internationally adopted or living in foster care will be intertwined with personal narrative. Erikson's theory of psychosocial development will be the lens to examine how trauma affects life and learning as children grow and mature. Finally, specific anecdotal strategies will be shared that either provided or negated support on how potentially to navigate public and higher education systems in the United States.
Out of Trauma Comes Strength
Authors: Funfar Michael George
Published: August 2021

Trauma occurs in a variety of forms including abuse, violence, neglect, or witness to any of these events. In the past, some have viewed trauma as a deficit that needs to be repaired. While this healing approach has value, new research has garnered a great deal of attention in shifting this paradigm to a strengths-based methodology. One such representation is the trauma-informed positive education (TIPE) model. This chapter provides an overview of the TIPE model and its three domains (i.e., repairing regulatory abilities, repairing disrupted attachment, and increasing psychological resources); discusses relevant pedagogical practices including emotional intelligence, mindfulness, grit, and growth mindset; and gives practical examples for educators to implement.
Self-Care is Not Selfish
Authors: Boivin Jacquelynne Anne , Melito-Conners Theresa
Published: August 2021

This chapter defines and outlines many aspects of self-care and renewal and how various practices have tremendous benefits to both teachers and students. Furthermore, self-care and renewal practices when promoted consistently can have a great impact on the school climate as a whole, but especially for students impacted by trauma. Both authors provide personal anecdotes pertaining to self-care and renewal to dive deeper into the topic. The role of the school leader as well as the teacher/leader relationship is explored including aspects of leadership that promote self-care and renewal. To round out the chapter, controversies and opposing viewpoints to self-care and renewal practices in schools are examined. The overall purpose of this chapter is to illustrate the importance of self-care and renewal and the dramatic impact promoting it can have on the school and all those in the school environment.
OMNeT++ Framework for Simulation of Centralized and Distributed Algorithms in Multi-Hop Networks
Authors: Demirci Sercan , Ileri Serhat Celil , Duraki Sadat
Published: August 2021

Theoretical applications and practical network algorithms are not very cost-effective, and most of the algorithms in the commercial market are implemented in the cutting-edge devices. Open-source network simulators have gained importance in recent years due to the necessity to implement network algorithms in more realistic scenarios with reasonable costs, especially for educational purposes and scientific researches. Although there have been various simulation tools, NS2 and NS3, OMNeT++ is more suitable to demonstrate network algorithms because it is convenient for the model establishment, modularization, expandability, etc. OMNeT++ network simulator is selected as a testbed in order to verify the correctness of the network algorithms. The study focuses on the algorithms based on centralized and distributed approaches for multi-hop networks in OMNeT++. Two network algorithms, the shortest path algorithm and flooding-based asynchronous spanning tree algorithm, were examined in OMNeT++. The implementation, analysis, and visualization of these algorithms have also been addressed.
A Survey on Explainability in Artificial Intelligence
Authors: Dutta Prarthana , Muppalaneni Naresh Babu , Patgiri Ripon
Published: August 2021

The world has been evolving with new technologies and advances everyday. With learning technologies, the research community can provide solutions in every aspect of life. However, it is found to lag behind the ability to explain its prediction. The current situation is such that these modern technologies can predict and decide upon various cases more accurately and speedily than a human, but has failed to provide an answer when the question of “how” it arrived at such a prediction or “why” one must trust its prediction, is put forward. To attain a deeper understanding of this rising trend, the authors surveyed a very recent and talked-about novel contribution, “explainability,” which would provide rich insight on a prediction being made by a model. The central premise of this chapter is to provide an overview of studies explored in the domain and obtain an idea of the current scenario along with the advancements achieved to date in this field. This survey aims to provide a comprehensive background of the broad spectrum of “explainability.”
Impact of Social Media Network Data on Conservation of Bioresources
Authors: Depuru Bharathi , Padmavathi Pydipati Lakshmi , Latha Anchapakula Suvarna , Sree Kolaru Subramanyam Shanthi
Published: August 2021

The effectiveness of the transmission and sharing of data and information among people has been revolutionized by the internet and digital technology. Social networks have shortened the communication space among the technology users. Their relatively easy access through computers, cell phones, and many other devices has made them easy to use, so they are probably the most widely used today. Social network and internet media (SIM) has revolutionized providing useful resources for scientific research, especially in engaging citizen scientists in research. There are also various possible drawbacks in spite of the benefits of the SIM. With the increasing use of social media worldwide, sites with rich species diversity face potentially the greatest anthropogenic threats (resulting from high numbers of visitors), which results in the extinction of valuable species from the native area. Despite shortcomings, SIM can provide conservation education and awareness and also reconnect to the natural world.
Telugu News Data Classification Using Machine Learning Approach
Authors: Priya G. Bala Krishna , Sultana Jabeen , M. Usha Rani
Published: August 2021

Mining Telugu news data and categorizing based on public sentiments is quite important since a lot of fake news emerged with rise of social media. Identifying whether news text is positive, negative, or neutral and later classifying the data in which areas they fall like business, editorial, entertainment, nation, and sports is included throughout this research work. This research work proposes an efficient model by adopting machine learning classifiers to perform classification on Telugu news data. The results obtained by various machine-learning models are compared, and an efficient model is found, and it is observed that the proposed model outperformed with reference to accuracy, precision, recall, and F1-score.
Unified Website Accessibility Assessment Framework
Authors: Altuntaş Zehra , Onay Durdu Pınar
Published: August 2021

In this chapter, a unified web accessibility assessment (UWAA) framework and its software has been proposed. UWAA framework was developed by considering Web Content Accessibility Guideline 2.0 to evaluate accessibility of web sites by integrating more than one evaluation approach. Achecker tool as an automated evaluation approach and barrier walkthrough (BW) as an expert-based evaluation approach were integrated in the UWAA framework. The framework also provides suggestions to recover from the problems determined to the evaluators. The websites of three universities were evaluated to determine the framework's accuracy and consistency. It was revealed that the results obtained from automated and expert-based evaluation methods were consistent and complementary with each other. Furthermore, it has been demonstrated that problems which cannot be determined by an automated tool but which can be detected by an expert can be identified by BW method.
Evaluation of the Accessibility of Elderly Individuals to Airline Company Websites
Authors: Özdağoğlu Aşkın , Keleş Murat Kemal , Işıldak Barış
Published: August 2021

Technological and social developments cause the birth and death rates to decrease. This has a direct effect on the increase in the rate of old age in the total population. In Turkey like in other countries, they face various problems in transportation in addition to education, health, justice, and social security. Therefore, the airline companies should provide some special services to elderly individuals in terms of accessibility and usability for their websites. This chapter aims to examine the accessibility of websites of airline companies for 65 and older individuals. Then, the second aim of this chapter is to determine the criteria for accessibility and alternatives. Then the next aim of this chapter is to determine the weights of these criteria and evaluate the alternatives with multi-criteria decision-making methods. The best airline company for airline website according to OWA, WASPAS, WSM, and WPM methods is Alternative 1.
Leading Institutions Through Change to Improve Learning
Authors: Bartelson Gretchen
Published: August 2021

Student success in higher education depends on a complex set of services that must be integrated seamlessly and delivered to students. This chapter looks at the complex, and often competing, interests of students, faculty, administration, and external stakeholders as they seek to improve student success in higher education. Administrators, mid-level managers, change agents, faculty and ancillary student support services all need to understand the importance of their role in working together to make the changes necessary to improve teaching and learning. The great challenge is managing the change that this will require. Educational institutions in the 21st century need to become agile and able to manage change imposed by both internal and external pressures.
Assessment for Learning
Authors: Heyman Errin
Published: August 2021

Advances in technology have been integrated into many facets of education, creating both opportunities and challenges for learning and assessment. This chapter provides an overview of effective assessment practices, largely targeted to higher education, with the mindset of using assessment for learning, rather than a more traditional view of assessment of learning. A brief theoretical background is presented as well as specific approaches for implementing learner-centered assessment strategies. Using assessment as a motivator and as a way to deepen, not just demonstrate, learning is discussed. Additionally, the chapter presents future considerations for assessment, especially as assessment can be enhanced by technology—“Education 3.0.”
Symptomatology and Clinical Features of Human COVID-19
Authors: Echchakery Mohamed , El Mouahid Souad , El Baz Soraia , Mountassir Maryam , Hakkoum Ahmed Taoufik , Klevor Raymond , Keita Ansumana Mohammed , El Hizazi Said , Ahmed Draoui , Zouhairi Nadia , Aimrane Abdelmohcine , Benksim Abdelhafid , Chatoui Redouane , Zemrani Yassin , Lamrani Hanchi Asmae , Alouani Mohamed
Published: August 2021

Severe Acute Respiratory Syndrome Virus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19), which was identified at the end of December 2019 in China. Symptoms of COVID-19 can appear after an incubation phase of the virus of 2 to 14 days, the most common being fever, cough, and asthenia. Other specific symptoms may include shortness of breath or difficulty breathing, muscle pain, sore throat, chills, loss of smell or sensation, chest pain, headache, nausea, rash, diarrhea, and vomiting. The severity of these symptoms can be mild or even extreme causing serious damage to several organs, directly and indirectly, namely pulmonary, renal, hepatic, cardiac, digestive, neurological. Some people have only mild symptoms, while others are asymptomatic. Seniors or those at risk for certain chronic diseases, such as massive obesity, diabetes, heart disease, lung disease, kidney disease, immune system abnormalities, and liver disease are more susceptible to COVID-19 and can develop more serious and fatal complications.