bluuebunny/crossref_metadata_2025_split huggingface dataset:
Survey on Regenerative Braking in Electrical and Hybrid Vehicles
Authors: Stajilov Victor , Bujoreanu Carmen 
Published: February 2022

Abstract
Strict pollution norms make car’s manufacturers to promote electrical and hybrid vehicles (EVs and HEVs). Recuperation system that can capture about 8-25% of the energy is represented by the regenerative brakes, it converts losses of kinetic energy of the car during braking in form of heat to electrical or chemical energy. Regenerative brakes can provide a good increase in car’s autonomy, especially in city driving cycles with high frequency of braking. Also, they reduce friction brakes wear and offer more precisely control of wheel braking torque. A survey in this paper presents basics, uses, types and braking strategies for existing regenerative braking systems with the purpose to identify and detail their limitations. Identifying key factors that have influence on system efficiency allows to elaborate optimizing techniques, strategies and algorithms, applied to existing systems in order to develop future concepts that will overcome current limitations.
Methods of Carrying Out the Anticipative Maintenance of Fluid Hydrocarbons Transport Systems
Authors: Vlădescu Robert-Gheorghe 
Published: February 2022

Abstract
The scientific knowledge, transposed into the engineering practice, requires the collection, by using the most state-of-the-art and complete means of the information necessary for the decision to initiate the most appropriate measures of predictive maintenance.
In this context, the information provided as a result of the investigation of the pipelines intended for the transport of fluid hydrocarbons with smart pigging devices (cleaning, calibration, geometric, magnetic flux leakage) refers to those pre-existing in the questionnaire of the pipeline of the inspection operation. The values in the questionnaire are used to evaluate the anomalies in the inspection reports (preliminary and final).
A quantitative assessment of anomalies is based on, and limited exclusively to the results of the inspection, and does not include any numerical parameters (corrosion growth rates, anodic potential etc.), other than those from In-Line Inspection such as values Estimated Repair Factor (ERF) of anomalies.
The questionnaire (initial data provided) of the pipeline to be investigated with smart pigging devices includes at least: pipe diameter, wall thickness, pipe material, design pressure, Maximum Allowable Operating Pressure (MAOP), transported product, curve type, investigation history. The detection thresholds are applied in accordance with the manufacturing standards of the pipes.
Generally, the calculation results, namely ERF and safe pressure, based on ASME B31G (Manual for Determining the Remaining Strength of Corroded Pipelines) are used to present the pipeline condition.
There are several approaches that can be used to characterize the behavior of corrosion anomalies, both pierced and partial. ASME B31G is a very conservative criterion that helps operators avoid unnecessary cuts. It is based on an empirical adequacy to an extensive series of tests on a full scale on vessels with narrow ridges.
Depth-based histograms show the distribution of all metal loss characteristics detected along the entire length of the pipe relative to their location and surface.
The approach to the referred issue allows the collection of essential information about the pipeline, and presents summaries of any anomalies of the pipeline, having a comprehensive character.
Expressions of Euler Angles as Functions of the Directional Cosines of Three-Orthogonal Axes in Rigid Body Kinematics - II
Authors: Corduneanu Eugen 
Published: February 2022

Abstract
In the rigid body kinematics, the position of the mobile frame in relation to the fixed frame is given by the base-change matrix. The elements of this orthogonal matrix are given by the Euler’s angles. This paper establishes the reverse link relations between the Euler’s angles and the elements of the base-change matrix (directional cosines).
ANN Modelling on Vulnerabilities Detection in Code Smells-Associated Android Applications
Authors: Gupta Aakanshi , Sharma Deepanshu , Phulli Kritika 
Published: February 2022

Abstract
There has been a lot of software design concerns in recent years that come under the code smell. Android Applications Developments experiences more security issues related to code smells that lead to vulnerabilities in software. This research focuses on the vulnerability detection in Android applications which consists of code smells. A multi-layer perceptron-based ANN model is generated for detection of software vulnerabilities and has a precision value of 74.7% and 79.6% accuracy with 2 hidden layers. The focus is laid on 1390 Android classes and involves association mining of the software vulnerabilities with android code smells using APRIORI algorithm. The generated ANN model The findings represent that Member Ignoring Method (MIM) code smell shows an association with Bean Member Serialization (BMS) vulnerability having 86% confidence level and 0.48 support value. An algorithm has also been proposed that would help developers in detecting software vulnerability in the smelly source code of an android applications at early stages of development.
ReqTagger: A Rule-Based Tagger for Automatic Glossary of Terms Extraction from Ontology Requirements
Authors: Wiśniewski Dawid , Potoniec Jędrzej , Ławrynowicz Agnieszka 
Published: February 2022

Abstract
Glossary of Terms extraction from textual requirements is an important step in ontology engineering methodologies. Although initially it was intended to be performed manually, last years have shown that some degree of automatization is possible. Based on these promising approaches, we introduce a novel, human interpretable, rule-based method named ReqTagger, which can extract candidates for ontology entities (classes or instances) and relations (data or object properties) from textual requirements automatically. We compare ReqTagger to existing automatic methods on an evaluation benchmark consisting of over 550 requirements and tagged with over 1700 entities and relations expected to be extracted. We discuss the quality of ReqTagger and provide details showing why it outperforms other methods. We also publish both the evaluation dataset and the implementation of ReqTagger.
Position-Encoding Convolutional Network to Solving Connected Text Captcha
Authors: Qing Ke , Zhang Rong 
Published: February 2022

Abstract
Text-based CAPTCHA is a convenient and effective safety mechanism that has been widely deployed across websites. The efficient end-to-end models of scene text recognition consisting of CNN and attention-based RNN show limited performance in solving text-based CAPTCHAs. In contrast with the street view image and document, the character sequence in CAPTCHA is non-semantic. The RNN loses its ability to learn the semantic context and only implicitly encodes the relative position of extracted features. Meanwhile, the security features, which prevent characters from segmentation and recognition, extensively increase the complexity of CAPTCHAs. The performance of this model is sensitive to different CAPTCHA schemes. In this paper, we analyze the properties of the text-based CAPTCHA and accordingly consider solving it as a highly position-relative character sequence recognition task. We propose a network named PosConv to leverage the position information in the character sequence without RNN. PosConv uses a novel padding strategy and modified convolution, explicitly encoding the relative position into the local features of characters. This mechanism of PosConv makes the extracted features from CAPTCHAs more informative and robust. We validate PosConv on six text-based CAPTCHA schemes, and it achieves state-of-the-art or competitive recognition accuracy with significantly fewer parameters and faster convergence speed.
An Autoencoder-Enhanced Stacking Neural Network Model for Increasing the Performance of Intrusion Detection
Authors: Brunner Csaba , Kő Andrea , Fodor Szabina 
Published: February 2022

AbstractSecurity threats, among other intrusions affecting the availability, confidentiality and integrity of IT resources and services, are spreading fast and can cause serious harm to organizations. Intrusion detection has a key role in capturing intrusions. In particular, the application of machine learning methods in this area can enrich the intrusion detection efficiency. Various methods, such as pattern recognition from event logs, can be applied in intrusion detection. The main goal of our research is to present a possible intrusion detection approach using recent machine learning techniques. In this paper, we suggest and evaluate the usage of stacked ensembles consisting of neural network (SNN) and autoen-coder (AE) models augmented with a tree-structured Parzen estimator hyperparameter optimization approach for intrusion detection. The main contribution of our work is the application of advanced hyperparameter optimization and stacked ensembles together.We conducted several experiments to check the effectiveness of our approach. We used the NSL-KDD dataset, a common benchmark dataset in intrusion detection, to train our models. The comparative results demonstrate that our proposed models can compete with and, in some cases, outperform existing models.
The Mediaeval Background of Self-Identification in Relation to the Filioque Controversy
Authors: András Szabolcs 
Published: February 2022

Abstract
The study at hand is not focused on the mediaeval theological history of the Filioque controversy but aims to examine how the mediaeval (particularly the Palamite) doctrine of procession has become an ideological element of identity in presentday interpretation. Based on the assumption that religious elements have become part of the political identity primarily in south-eastern Europe, the present paper makes reference first of all to representatives of Orthodox theology, without seeking to criticize, however, the Orthodox standpoint on the Filioque. Provided that it can be demonstrated that contemporary authors make use of mediaeval sources not merely theologically but also ideologically, then we can ascertain that the mediaeval Filioque controversy inşuences the present-day interpretation of self-identity.
The Mobility of Iconographers and their Quest for Social Status Art and Signatures of Transylvanian Pre-Modern Greek-Orthodox Iconographers
Authors: Prelipceanu Raluca 
Published: February 2022

Abstract
The change in the status of Orthodox iconographers from Transylvania brought forward a change in their art during the eighteenth and early nineteenth centuries. During this period the condition of Orthodox painters changes from that of mere craftsmen to artists. Based on the work of several Transylvanian painters active during the eighteenth and early nineteenth centuries, an analysis of the signatures of the artists, visitation records and contracts between the artists and the patrons of the church, this article wishes to explore the changes in the status of these individuals who evolved from craftsmen to artists during their lives.
Internet Usage and Adolescents' Happiness
Authors: Kaur Sandeep 
Published: February 2022

Abstract
Adolescence, a phase of 'stress and strain', is a crucial period for building a strong sense of self, personality, social connections, and identity. Happiness is also a critical issue concerning adolescents’ development. Adolescents are happy when they are satisfied with their lives and relationships. During the last two decades, the internet has been incorporated into the daily lives of adolescents to such an extent that it has become a magic wand for satisfying their psychological needs and making them happy. The present review seeks to explore the factors of internet usage affecting the happiness of adolescents in order to make recommendations for mindful usage of the internet that would eventually result in a happier adolescent. The review has established that time spent online and the purpose of using the internet are the influential factors of internet usage that impact the happiness of adolescents. It has also been revealed that adolescents use the internet for four main purposes: retrieving information, knowledge, communication, entertainment, and commerce, of which communication predominates. Though there are mixed results regarding the relationship between time spent online, the purpose of its usage, and happiness, as well as a hazy understanding of the relationships that exist between the obtained factors of internet usage, the evidence of the negative effects of prolonged and purposeless internet usage necessitates diplomatic strategy implications by policymakers for its mindful usage in order to promote its positive effects and mitigate the potential harm.
Anatomical changes of Ipomoea reptans due to mercury uptake and accumulation in contaminant soil
Authors: TAUHIDA NITA , HARNELLY ESSY , NASIR MUHAMMAD , BAHI MUHAMMAD 
Published: February 2022

Heavy metal contaminants like mercury is a serious problem to human, animals, and some plants’ health. Phytoremediation is an alternative technique, which can remediate the contaminants from soil using a hyperaccumulator plant. The goal of this research was to study anatomical changes of plant main organs (roots, stems, and leaves) of Ipomoea reptans which are assumed as a hyperaccumulator plant that grows in mercury contaminant. The mercury concentration of the growth medium was 0, 61.871, 92.258, and 107.046 ppb. Ipomoea reptans were harvested after 27 days. The anatomical changes of the plant’s main organs were observed by preparing the cross-section of roots, stems, and leaves of I. reptans. The result showed that mercury treatment has caused anatomical damage at the xylem vessel of the root, and decreased bulliform cell size. The anatomical damage was found only in the root of I. reptans. The mercury concentration in media decrease to 0 ppb (P0), 50,420 ppb (P1), 58,583 (P2), and 96,120 (P3).
Материальная культура городища Жайык (по результатам археологических исследований 2012-2015 гг.)
Authors: Калменов Мурат Дабылович , Ашыгалиев Бекжан Маратович 
Published: March 2022

В представленной статье рассматриваются объекты материальной культуры городища Жайык, расположенного в бассейне реки Жайык (Урал). Описываемые артефакты были обнаружены в ходе археологических изысканий в 2012–2015 гг. На основании полученных результатов раскопок установлено время строительства и функционирования объектов на изученных участках – погребальных и хозяйственно-бытовых сооружений в пределах начала XIII–XIV вв. Исследованиями установлено отсутствие более ранних культурных напластований, предшествовавших обнаруженным сооружениям. Основным полученным вещевым материалом являются фрагменты неполивной станковой керамики золотоордынского облика, среди которой особый интерес представляет повышенное содержание сосудов с примесями в тесте. Данный признак, который несет не только этнокультурную, но и хронологическую нагрузку, обычно характерен для памятников первой половины золотоордынского времени, охватывающего широкий ареал (Средняя Азия, Поволжье), а также для памятников аналогичного периода бассейна реки Жайык (Урал). Материал, полученный в результате исследования, дал возможность проследить динамику развития городищ бассейна реки Урал в средневековье. В результате анализа полученных раскопками археологической и нумизматической коллекций, а также сборов подъемного материала установлено, что время строительства и функционирования изученного участка городища, его хозяйственно-бытовых сооружений определяется в пределах XIII-XIV вв.
Железные Предметы С Багаевского селища
Authors: Недашковский Леонард Федорович , Шигапов Марат Баязитович 
Published: March 2022

В статье анализируются отдельные виды железных изделий с Багаевского селища второй половины XIII–XIV в., располагающегося в округе золотоордынского города Укека в Саратовском районе Саратовской области. Селище изучалось раскопками экспедицией Казанского университета под руководством Л.Ф. Недашковского в 2002–2003, 2006–2012, 2014–2016 и 2020–2021 гг. Багаевское селище является довольно крупным аграрным поселением; площадь памятника составляет 5,1 га, мощность культурного слоя местами достигает более 90 см. Монетные находки с поселения относятся к последней четверти XIII – началу 60-х гг. XIV в. Авторами рассмотрены железные штыри, пластины, ручки и неопределенные предметы, для которых приведены предположения об их функциональном назначении. Данный комплекс характеризует материальную культуру золотоордынского села Нижнего Поволжья.
Compliance With Legal and Other Requirements Related to the Environmental Licensing Processes in Companies Located in Rio De Janeiro - Brazil
Authors: Fragoso Silva Vanilson , Namen Anderson Amendoeira 
Published: February 2022

Purpose: This work aims to analyse the compliance with legal and other requirements related to the environmental licensing processes in some Brazilian companies. The work also aims to assess the degree to which these companies define and execute action plans to address unmet requirements as well as their risk management.
Theoretical framework: The article presents an overview of the legal questions related to the theme. In addition, a literature review was conducted on works related to the Environmental Impact Assessment Process and environmental risk management in organizations in Brazil and worldwide.
Method/design/approach: Based on a qualitative-quantitative and descriptive approach, six medium and large-sized companies located in the state of Rio de Janeiro were analysed. The companies operate in the chemical, pharmaceutical, hospitality, engineering, and metallurgical segments. The following data was collected: number of legal and other applicable requirements, which were assessed, met and unmet; number of risks identified; number of action plans drawn up to mitigate risks; number of action plans overdue, completed and on time.
Results and conclusion: Results indicate significant amounts of non-assessed and unmet requirements, weak identification of risks by companies and a considerable number of overdue action plans. It can be concluded that environmental control bodies did not demonstrate effectiveness in the execution of their attributions. Furthermore, the main stakeholders involved in the licensing process have not played their roles and fulfilled their responsibilities adequately.
Research implications: It is believed that this work presents relevant information about the behaviour of Brazilian companies regarding their environmental licensing processes, compliance obligations and risk management. Thus, it can contribute to the reflection and proposition of initiatives that bring positive results for organizations and, especially, for the environment and society.
Originality/value: Similar studies generally focus on specific companies in specific industries. The main differential of this study is its broad analysis, carried out in different segments of activity and involving companies of different sizes and levels of environmental risk.
Reframing The Siop Model To Boost Teachers' Self Efficacy In Bilingual-Like Program: A Practical Concept Of An Alternative Model
Authors: Rozanah Katrina Herda  , Angga Damayanto  
Published: February 2022

The need to communicate through English and the desire to practice English in the teaching process has turned a public junior high school in Wonosobo, Indonesia, into one of the schools that hold an "English on Wednesdays" program to implement bilingual-like nuance. This conceptual paper highlights a natural phenomenon that occurs in that institution dealing with the desire to improve the competence of teachers and students in communication by programming "English on Wednesdays." The dilemmas related to teaching are felt by teachers, especially non-English teachers who do not have an English background, yet they are enthusiastic about this program. Thus, this paper will propose a framework called "The Alternative SIOP Model" that will help teachers overcome the dilemmas in teaching the "English on Wednesdays" program that emphasizes self-efficacy to develop teachers' competencies on lesson preparation and communication. This conceptual paper used the systemic review to gain information from theories and research findings related to the topic.
Keywords: teachers' dilemmas; teachers' self-efficacy; the alternative SIOP Model
Field Description and Lithostratigraphic Study of Sargelu Formation in Rania and Sargelu sections, Northern Iraq
Authors: Al-Tarim Haider Ahmed Falih , Al-Shakiri Ahmed Jawad 
Published: March 2022

The Sargule Formation was deposited during the Middle Jurassic, representing one of the most important source rocks in Iraq and surrounding areas.
Jurassic successions are commonly exposed as an isolated patch at some eroded anticline’s cores and limbs in the High Folded Zone, Imbricate Zone, and Thrust Zones of northern Iraq. The Sargelu section is located in Sargelu village at Surdash anticline, while the Rania section is located in Rania city near Hanjira village at Shaweri anticline. Fieldwork in Rania and Sargelu Sections allow to divide Sargelu Formation lithostratigraphically into many subdivisions as follow:
The Sargelu Formation in the Rania section is about 40 m and can be divided into two lithologic units; the upper thin to medium bituminous limestone beds alternated with thin chert beds, and the lower thin to medium bituminous limestone beds alternated with fissile gray shale beds.
the The Sargelu section comprises 180m and is divided into three units; the upper unit consists of dark gray limestone beds and thin brownish-black of laminated shale. The middle unit includes dark chert alternated with dark gray bituminous limestone and brownish-black laminated shale. At the same time, the lower unit consists of dark gray bituminous limestone beds alternated with medium brownish-black laminated shale beds.
Plants Leaf Diseases Detection Using Deep Learning
Authors: Al-Akkam Reem Mohammed Jasim , Altaei Mohammed Sahib Mahdi 
Published: March 2022

Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes. The data augmentation techniques have been used. In addition to dropout and weight regularization, which leads to good classification results by preventing the model from over fitting. The model was optimized with the Adam optimization technique. The obtained results in terms of performance were 98.08% in the testing stage and 99.24% in the training stage. Next, the baseline model was improved using early stopping, and the accuracy increased to 98.34% on the testing set and 99.64% on the training set. The substantial success rate makes it a valuable advisory method to detect and identify transparently.