bluuebunny/crossref_metadata_2025 huggingface dataset:
Screening of Islet Autoantibodies for Children in the General Population: A Position Statement Endorsed by the European Society for Paediatric Endocrinology
Authors: Chiarelli Francesco , Rewers Marian , Phillip Moshe
Published: July 2022

Background: Type 1 diabetes (T1D) is the most frequent chronic autoimmune disease in childhood and adolescence, its incidence is increasing particularly in toddlers and preschool children, and up to 60% of young patients present with diabetic ketoacidosis (DKA), a severe and life-threatening complication. So far, the majority of screening efforts have been performed in the at-risk group, i.e., relatives of people with T1D; anyhow, around 90% of young patients who eventually develop T1D do not have a family history. Summary: Some studies in Europe and the USA have clearly shown that a public health screening of children (with positive autoantibodies) is effective in reducing the prevalence of DKA by more than 10 times, decreasing the rate of hospitalization and its costs, providing psychological, emotional, and social support to children and their families. In addition, several treatments and trials are available for children with stage 2 and stage 3 T1D. There is still room for improvement of sensitivity, specificity, positive and negative predictive value in a population screening program; anyhow, there is vivid debate on the opportunity for a screening program in the general population of children at risk for developing T1D. Key Messages: This paper, endorsed by the European Society for Paediatric Endocrinology (ESPE), discusses the issues of a screening program in the general population with the hope that uncertainties and difficulties in this field will be overcome by better screening methods, improved cost-effectiveness, reliable treatments for secondary prevention, and relevant delay in clinically evident T1D in children and adolescents.
Electronic module as learning needs to write exposition texts for junior high school students
Authors: Charlina Charlina , Septyanti Elvrin , Mustika Tria Putri , Rahmi Annisa
Published: July 2022

This study was a step toward the creation of an e-module to creat flips book-based exposition texts for junior high schools. The purpose of this study was to offer an examination of students' demands when creating exposition papers. A survey was used for the investigation. The data for this inquiry was gathered through a questionnaire. In this study, a Likert scale was utilized to examine students' attitudes, opinions, and perceptions of the built electronic module. This research made use of a checklist-style questionnaire with a range of assessments of 1 to 5. The questionnaire was distributed to students from four junior high schools. This sampling technique was based on the sampling quota established by the researcher. The data analysis technique involved converting the category value into an assessment score and examining the result. According to the findings, 61.5% of students had difficulties in interpreting the material of exposition text, and the rest of 80.1% desired that the exposition text writing content be presented using entertaining, interactive, and innovative learning methods. This showed the need for the preparation of electronic modules for writing flip book-based exposition texts.
State defense internalization in a university: Theory of planned behavior approach
Authors: Azizah Nurul , Hapsari Nurul Retno , Farida Siti Ning
Published: July 2022

Universitas Pembangunan Nasional “Veteran” Jawa Timur (UPNVJT) is a university with state defense education’s characters. In practice, those character did not cover the academic field as a whole. Through the theory of planned behavior (TPB), the research carried out the process of internalizing state defense values in thesis writing as a form of character graduates. The research was conducted using a quantitative approach involving stakeholders at UPNJT, namely LP3M and head of department. Data were analyzed using partial least squares structural equation modeling (PLS-SEM) software. The results found that two TPB variables, namely attitudes and subjective norms in the organization, had an influence on the intention in implementing state defense values. The intention in implementing state defense values will influence perceived self-efficacy of state defense values. Meanwhile, the subjective norms of the perpetrators and the perception of behavioral control in accordance with the state defense values have no influence on the intention in implementing the state defense values.
Extensive reading among Agroecotechnology students: What and why they read?
Authors: Prasetianto Mushoffan , Maharddhika Rizkiana
Published: July 2022

Reading is a pivotal skill for non-English department students as a vehicle to update their knowledge. One of reading activity which is beneficial is extensive reading. Several studies have proved the advantage of extensive reading, but study regarding what reading material is read by students is under explored. To fill this gap, this research aimed to uncover what non-English department students read during extensive reading program and why they chose that theme. The participants were Agroecotechnology students (n=52). The data was collected from the reading log sheet and participant interview. The reading log sheet was analyzed by the researcher to find the theme of the text that students read. The interview was conducted in Indonesian to make students at ease. After the interview, the transcript was written and translated into English. The result shows that there are 32 types of themes with various frequency distributions. Theme that students read is mainly caused by their hobby, favorite idol, and a senior student who influence them to read certain theme.
Students’ preferences and challenges in learning English fully online with Google Classroom
Authors: Wahyuni Sri , Etfita Fauzul , Alkhaira Nadya
Published: July 2022

The Coronavirus 2019 outbreak caused the world to experience a pandemic and paralyze human activities, including the education sector. Consequently, the teaching-learning system changed from face-to-face to online. This study aimed to determine how high school students' preferences and challenges in Pekanbaru city employing the Google Classroom to learn English. This descriptive study involved 30 high school and vocational high school students as the sample who obtained through purposive sample technique. Google Form and interviews with Zoom were employed to gather the data. This study found that Google Classroom was quite effective in helping students replace the learning process during a pandemic with an online learning system.
1×16 Rectangular dielectric resonator antenna array for 24 Ghz automotive radar system
Authors: Haddad Abderrahim , Aoutoul Mohssin , Essaaidi Mohamed , Sabri Khalid , Khoukh Abdelaziz , Errami Youssef , Had Anas , El Moukhtafi Fadwa , Jouali Redouane
Published: July 2022

This paper presents the design of a 1×16-elements RDRA array for anti-collision radar SRR application at 24 GHz. A single RDRA with high dielectric constant of 41, fed by a simple microstrip line feeding technique, is initially designed to operate around 24 GHz. The RDRA element is further used within an array network structure made up of 16 linear antenna elements to cover the same frequency band. The simulated 1×16 RDRA array can reach a high gain, up to18.6 dB, very high radiation efficiency (97%), and ensure enough directional radiation pattern properties for radar applications with a 3-dB angular beam width of 6°. To validate our design, RDRA array’ radiation pattern computed results are compared to an equivalent fabricated patch antenna array reported in the literature.
Machine learning in handling disease outbreaks: a comprehensive review
Authors: Riswantini Dianadewi , Nugraheni Ekasari
Published: July 2022

The changes in the global environment have made impact on the evolution of infectious diseases, virus mutations, or new diseases which are challenging to be tackled with new technological advances. This work aims to identify and analyze previous studies on machine learning applications in handling disease outbreaks. Bibliometric analysis was conducted on 3,447 scientific articles selected from the Scopus database. Further, latent dirichlet analysis (LDA) method was applied to identify the topic hotspots in attempting to deepen the analysis. The LDA results identified twelve topic hotspots that can be classified into three themes: COVID-19 disease, miscellaneous diseases, and public opinion on disease outbreaks for discussion. The study reveals that the scientific structure of this domain is dominated by machine learning research on COVID-19 diseases and miscellaneous diseases caused by pathogens or some genetic factors. A huge amount of multimodal medical data was used by previous studies for prediction, forecasting, classification, or screening purposes to resolve many problems of diseases, including epidemiological surveillance, diagnosis, treatment, health monitoring, epidemic management, viral infection, and pathogenesis. Public opinions toward new diseases are also an interesting topic in addition to the public perceptions in response to the health protocol and policies.
Privacy-preserving multi-factor authentication and role-based access control scheme for the E-healthcare system
Authors: Fareed Mohammad , A. Yassin Ali
Published: July 2022

E-healthcare assists medical specialists in remotely collecting patient health data and providing remote health diagnoses. The roles are distributed among the system's users, contrasted between admin to data entry within certain rules and policies. Role-based access control (RBAC) is a technique of advanced access control that restricts key operations of users (addition, deletion and modification) access based on a user's role within a healthcare system. This paper proposes a privacy-preserving using RBAC and smart multi-factor authentication for the healthcare system to overcome the limitation flaw in previous schemes such as security risk tolerance, scalability and dynamism. This work relies on low-complexity cryptographic hash functions and symmetric operations to authenticate users while using an asymmetric cryptosystem based on the Schnorr digital signature lightweight operation to authenticate the administrator to provide multi-factor authentication. The administrator represents the system's core, and any his information leak could attack the entire system and its components. The proposed scheme conducted two thorough formal security proofs for the proposed work based on informal analysis and the Scyther tool. Furthermore, comparisons with other schemes reveal that the proposed scheme provides greater security features, and resisting attacks than the others while also being efficient in computing and communication costs.
High efficiency dielectric resonator antenna using complementary ring resonator for bandwidth enhancement
Authors: Dheyaa Khaleel Al-Obaidi Aymen , Ghazali Osman , Mahmuddin Massudi , Jamal Abdullah Al-Gburi Ahmed , Najah Mahdi Al-Niamey Mohammed , Fais Mansor Mohd
Published: July 2022

A complementary ring resonator (CRR) technique is used to improve the bandwidth of the dielectric resonator antenna (DRA) while maintaining other parameters such as the efficiency and the gain. Parametric experiments were conducted in order to demonstrate the suggested antenna's working guideline. The bandwidth of the proposed Antenna is boosted by 769 percent as compared to the antenna without the CRR technique. The proposed antenna has high efficiency of 94 percent and a tiny dimension of around 30×30×12 mm. The suggested antenna has a frequency range from 2.61 to 3.65 GHz, which is suitable for S-band applications. Computer simulation technology (CST) was used to implement the design and obtain the results.
Trajectory tracking control for mecanum wheel mobile robot by time-varying parameter PID controller
Authors: Thai Nguyen Hong , Ly Trinh Thi Khanh , Dzung Le Quoc
Published: July 2022

This paper presents the design method a proportional integral derivative (PID) controller with time-varying parameters for trajectory tracking of a mecanum-wheeled robot with a minor error. First, a nonlinear kinematic error model of the robot is established and linearized around the working point. Then a PID controller with time-varying parameters is designed based on this linear model. The coefficients of KP, KI, and KD control parameters are determined by trial and error technique to ensure that the robot moves along the desired trajectory with minimal error. A platform mecanum-wheeled mobile robot has been designed and manufactured to demonstrate the proposed controller. Simulation and experimental results are presented to verify the effective and accuracy of the proposed controller. It shows that can apply this research to control of a four mecanum-wheeled mobile robot in logistics services in practice.
Empowering secure transmission for downlink of multiple access system relying non-orthogonal signal multiplexing
Authors: Do Dinh-Thuan , Nguyen Minh-Sang Van
Published: July 2022

The growth of internet-of-things (IoT) inspired use cases in different run of the mill environments such as cities, industries, healthcare, agriculture, and transportation, has led to a greater desire for safer IoT data gathering and storage. However, securing IoT is challenging due to form-factor, complexity, energy, and connectivity limitations. Conventional coding-based security techniques are unsuitable for ultra-reliable low-latency and energy-efficient communication in IoT. Numerous research studies on physical layer security (PLS) techniques for fifth generation (5G) have emerged recently, but not all of the solutions can be used in IoT networks due to complexity limitations. Non-orthogonal multiple access (NOMA) is billed as a possible technology to solve connectivity and latency requirements in IoT. In this study, we exploit the power allocation characteristics of NOMA to enhance security in a downlink deviceto-device (D2D) decode and forward (DF) IoT network infiltrated by an eavesdropper. Our performance metric of choice is the secrecy outage probability (SOP). We formulate exact SOP results for different users. Simulation results demonstrate the positive impact of NOMA on SOP in a D2D IoT-NOMA network.
Characterization of a compact low cost 6.5kV Cockcroft voltage multiplier
Authors: Palati Madhu , Ananda Prashanth Narayanappa
Published: July 2022

Generation of high voltages is often necessary in Industrial, Medical, civilian and defense applications. One of the popular methods of generation of high voltage DC is using a Cockcroft voltage multiplier generator. Knowledge on characterization of the voltage multiplier circuit helps the designer to study the effect of various input parameters on output, saves lot of time and money. In this paper various methods of generation of high voltages, advantages and disadvantages of each method are discussed. Design of five stage voltage multiplier circuit, fabrication and characterization of the 6.5kV voltage multiplier generator are presented. Simulation was carried using PSPICE software under different load conditions. Effect on the output voltage, ripple voltage with different values of load, frequency was studied. Experiments were carried out on the proposed prototype model and validated by comparing the values obtained from experimentation with the simulation and theoretical values
Field-oriented control based on adaptive neuro-fuzzy inference system for PMSM dedicated to electric vehicle
Authors: Djelamda Imene , Bochareb Ilhem
Published: July 2022

Permanent magnet synchronous motor (PMSM) speed control is generally done using flux-oriented control, which uses conventional proportional-integral (PI) current regulators, but still remain the problem of calculating the coefficients of these regulators, particularly in the case of control hybridization, the development of artificial intelligence has simplified many calculations while giving more accurate, and improved results, this paper presents and compares the performance of the flux oriented control (FOC) of a PMSM powered by pulse width modulation (PWM) using PI regulator, fuzzy logic control (FLC) and adaptive neuro-fuzzy inference system (ANFIS), in this work we present another approach of a neuro ANFIS using the hybrid combination of fuzzy logic and neural networks. This ANFIS is a very powerful tool and can be applied to various engineering problems. To make up for the deficiency of fuzzy logic controller. To understand the performance, characteristics, and influence of each controller on the system response, we use MATLAB/Simulink to model a PMSM (0.5 kW) powered by a three-phase inverter and controlled by the FOC, FOC-FLC, and FOC-ANFIS.
Multi categorical of common eye disease detect using convolutional neural network: a transfer learning approach
Authors: Bitto Abu Kowshir , Mahmud Imran
Published: July 2022

Among the most important systems in the body is the eyes. Although their small stature, humans are unable to imagine existence without it. The human optic is safe against dust particles by a narrow layer called the conjunctiva. It prevents friction during the opening and shutting of the eye by acting as a lubricant. A cataract is an opacification of the eye's lens. There are various forms of eye problems. Because the visual system is the most important of the four sensory organs, external eye abnormalities must be detected early. The classification technique can be used in a variety of situations. A few of these uses are in the healthcare profession. We use visual geometry group (VGG-16), ResNet-50, and Inception-v3 architectures of convolutional neural networks (CNNs) to distinguish between normal eyes, conjunctivitis eyes, and cataract eyes throughout this paper. With a detection time of 485 seconds, Inception-v3 is the most accurate at detecting eye disease, with a 97.08% accuracy, ResNet-50 performs the second-highest accuracy with 95.68% with 1090 seconds and lastly, VGG-16 performs 95.48% accuracy taking the highest time of 2510 seconds to detect eye diseases.
Distributed denial of service attacks detection for software defined networks based on evolutionary decision tree model
Authors: Kamel Hasan , Zaki Abdullah Mahmood
Published: July 2022

The software defined networks (SDN) system has modern techniques in networking, it separates the forwarding plane from the control plane and works to collect control functions in a central unit (controller), and this separation process leads to many advantages, such as cost reduction and programming ability. Concurrently, because of its centralized architecture, it is prone to a variety of attacks. Distributed denial of service (DDoS) attack has a significant impact on SDN, it is characterized by its ability to consume network resources as well as its ability to turn off the entire network. The work in this study aims to improve and increase the security and robustness of SDN systems against the attack or intrusion, by using a machine learning model to detect attack traffic and classify traffic of SDN as (attack or normal), and optimization algorithm (genetic algorithm) for improving the accuracy of the classification. After preparing and preprocessing the dataset, we used the genetic algorithm (GA) to optimize the hyperparameters of the decision tree (DT) model, and the proposed evolutionary decision tree (EDT) model was used to classify traffic into normal and attack traffic. The results indicate that the suggested model achieved a high classification accuracy of 99.46.
Implementation of energy-efficent routing protocol within real time clustering wireless sensor networks
Authors: Mahdi Azooz Salam , H. Majeed Jaber , Khalid Ibrahim Raed , Hussein Ali Adnan
Published: July 2022

Wireless sensor networks (WSNs) are characterized by huge sensors that are having a limited amount of energy and specifying their behavior. Sensor networks combine distributed sensing, processing, and communication capabilities to create a powerful system. There are issues with the length of sensors connected to the network since features inside the sensors frequently require energy, which is likely to limit WSN performance. In creating WSN application architectures, extending network longevity, scalability, and load balancing are important factors. Using clustering techniques, the challenge of prolonging overall network lifetime and increasing the first dead node duration in the network may be tackled. Clustering is a valuable approach for breaking a network into parts known as clusters and giving solutions for energy consumption concerns including data collection, aggregating, and routing to sink nodes by cluster heads (CHs). In this paper, we suggest optimum clustering in multi-path and multi-hop protocols as a feasible option for reducing energy consumption and extending the lifetime of wireless sensor networks. In compared to the low energy adaptive clustering hierarchy (LEACH) clustering method, simulation results show that the new technique, optimal real time clustering (ORTC), is promising in terms of extending network lifetime.
The effects of silica-coated Y2O2S:Eu3+ red phosphor on the lighting properties of the light-emitting diode
Authors: Dang Huu Phuc , Xuan Le Phan
Published: July 2022

The red phosphor Y2O2S:Eu3+ coated with silica (SiO2) nanocomposite was synthesized using the sol-gel method with dip-coating technique. The purpose of coating the poly (methyl methacrylate) (PMMA)-SiO2 composite on Y2O2S:Eu3+ phosphor’s surface is to protect the phosphor and improve its scattering ability. The three primary ingredients of coating composition include methyl methacrylate (MMA) monomer, tetraethyl orthosilicate (TEOS), and SiO2 nanoparticles. Via Mie scattering theory, the scattering of SiO2 is examined, which primarily determines the scattering of PMMA-SiO2-coated Y2O2S:Eu3+. The larger particles of SiO2 in the coating composite leads to better scattering properties. When being applied in the dual-film remote phosphor configuration of a LED, SiO2@Y2O2S:Eu3+ considerably enhances the CRI and the color quality scale (CQS). The highest CRI and CQS can be observed at approximately 85 and 74 with 23 %wt. and 26 %wt. the concentration of SiO2@Y2O2S:Eu3+, respectively. Neverthless, the illuminating beam of the package gradually declines as the concentration of SiO2@Y2O2S:Eu3+ go up, which might be ascribed to excessive scattering occurrences in the double-layer remote package.
An innovative vigorous outlier recognition placed on LROAD for fix-amplitude impulsive noise
Authors: Patanavijit Vorapoj , Thakulsukanant Kornkamol
Published: July 2022

Due to large current applications on digital images in these recent years, outlier suppression is one of the primary stages for modern computer vision implementations thereupon there are tremendously invented for creating an efficient and practical outlier suppression, which ordinarily are composed of outlier recognition stage and outlier rebuilt stage. The localised rank ordered difference (LROAD) approach, which is progressed from rank-ordered absolute differences (ROAD), has been invented since 2016. Later, the LROAD approach evolved to be one of the efficient outlier recognition stages from its eminent effectiveness. The paper focus to propose the innovative vigorous outlier recognition placed on localised rank-ordered logarithmic differences (LROLD) approach, which is progressed from LROAD and rank-ordered logarithmic differences (ROLD), which is higher effectiveness than the ordinary LROAD, for applying on FAIN. From the computer experiments, which are examined on many depictions such as Girl, Pepper F16 and Lena, the innovative vigorous outlier recognition placed on LROLD approach has higher eminent effectiveness then the stage-of-art approach such as LROAD and ROAD approaches at numerous consistencies of FAIN.
Improved customer churn prediction model using word order contextualized semantics on customers’ social opinion
Authors: Ibitoye Ayodeji O. J. , Onifade Olufade F. W.
Published: July 2022

Through the hype in digital marketing and the continuous increase in volume and velocity of opinions about an organization’s brands, churn prediction now requires advanced analytics in opinion mining for effective customer behavioral management beyond keywords sentiment analysis (SA). Earlier, by analyzing customers’ opinions using SA models, the extracted positive-negative polarity is used to classify customers as churners or non-churner. In those methods, the impact of word order, context, and the inherent semantics of the clustered opinion set were oftentimes overlooked. However, with the consistent creation of new words with new meanings mapped to existing words on the web, the research extended the fuzzy support vector model (FSVM) to show that the dependency distance between the headword, its dependent, and tail word can be weighted by using information content derived from a corpus to generate four-classed social opinion categories as a strongly positive, positive, negative, and strong negative. These opinion classes formed the basis for the churn category as a premium customer, Inertia customer potential churner, and churner in customer behavioral management. In performance evaluation, aside from engendering quadrupled churn class against the existing churn binary pattern, better accuracy, precision, and recall values were obtained when compared with existing SA works in support vector machine and fuzzy support vector machine (FSVM), respectively.  
Privacy of biofeedback human interfacing devices
Authors: Beauchamp Brendan Philip , Corneal Lindsay , Kandalaft Nabeeh
Published: July 2022

The public and governmental focus have been shifted increasingly onto data and privacy due to Facebook’s standoff with Apple and several Nations’ Governments. An imperative for the discussion of data handling has been made, while Biofeedback human interfacing device (HID) companies such as CTRL-labs and Neuralink introduce new risks in the access, use, and control of personal health information. This paper combines the lexicon of digital self-extension with line drawing analysis to help visualize the industry use of personally identifiable information (PII). Through this analysis encapsulation methods of users' PII have been identified such that discussion of encrypting personal health information (PHI) can be facilitated through analogy. To reduce the likelihood that companies generating biometric hardware are subject to future legal action through laws analogous to European Privacy Law, it is in their best interest to be transparent with their users about data sharing, and educate them on how the companies encrypt their PHI. Should users consent to the use of biometric hardware, this process validates the user control of their own PHI.
The concurrent upshot of optical path-length and pressure on O3 absorption cross-section in relation to green communication
Authors: David Michael , Enenche Patrick , Alenoghena Caroline O. , Ibrahim Mohd Haniff , M. Idrus Sevia , Marcus Tay Ching En
Published: July 2022

Ozone gas is a greenhouse gas. Accurate measurement of its concentration is dependent on the right value of the ozone gas absorption cross-section. In the literature, discrepancies and inconsistencies have been however linked with ozone gas absorption cross-section. In the literature, information on the pressure effect on pressures less than 100 mbar and greater than 100 but less than 1000 mbar is not available for the visible spectrum. Thus, creating an information gap which this manuscript is intended to fill up. This is the problem that has been addressed in this present work. The method of simulation with SpectralCalc is the method adopted for the present work. HITRAN 2012 simulator, available on spectralcalc.com, was used in simulating the ozone gas absorption cross-section to determine the simultaneous effect of optical path length and pressure at two peak wavelengths in the visible spectrum. Simulation outcomes were obtained for an optical path length of 10 cm to 120 cm shows that the optimum absorption cross-section value of 5.1084×10-25 m2/molecule at 603 nm and 4.7182×10-25 m2/molecule at 575 nm for gas cells length between 10 cm and 120 cm are obtained at peak points. Pressure values at which ozone gas absorption cross-section becomes a constant value of 5.1058×10-25 m2/molecule at 603 nm and 4.7158×10-25 m2/molecule at 575 nm is optical path length dependent. The percentage difference between 5.1084×10-25 m2/molecule and 5.1058×10-25 m2/molecule is 0.05% for all lengths of gas cells considered. Similarly, the percentage difference between 4.7182×10-25 m2/molecule and 4.7158×10-25 m2/molecule is also 0.05% for all lengths of gas cells considered. These results are relevant for high accuracy and high precision ozone gas measurements. Furthermore, efficient measurement of ozone gas is a direct enhancement of green communication.
Microstrip antenna optimization using evolutionary algorithms
Authors: Behera Kalpa Ranjan , Salkuti Surender Reddy
Published: July 2022

Different structures of microstrip antenna optimization using different algorithms are the important field of wireless communications. Rectangular microstrip antenna, inverted E-shaped antenna, tulip shaped antenna are some examples of microstrip antennas. The antenna dimensions are optimized by different algorithms. The operating frequencies for different antenna structures depend on antenna dimensions. The frequency of operation is 3-lS GHz for rectangular antenna, IMT-2000 for invelted E-shaped antenna, 8 to 12 GHz for tulip shaped antenna, 2.16 GHz for miniaturized antenna structure. The dimensions of microstrip antennas are modified to get minimum reflection coefficient maximum gain and bandwidth. The dimensions are modified using different algorithms such as evolutionary algorithm, particle swarm optimization (PSO), artificial neural network (ANN), and genetic algorithms (GA).
Graph transformer for cross-lingual plagiarism detection
Authors: Hourrane Oumaima , Benlahmar El Habib
Published: July 2022

The existence of vast amounts of multilingual textual data on the internet leads to cross-lingual plagiarism which becomes a serious issue in different fields such as education, science, and literature. Current cross-lingual plagiarism detection approaches usually employ syntactic and lexical properties, external machine translation systems, or finding similarities within a multilingual set of text documents. However, most of these methods are conceived for literal plagiarism such as copy and paste, and their performance is diminished when handling complex cases of plagiarism including paraphrasing. In this paper, we propose a new graph-based approach that represents text passages in different languages using knowledge graphs. We put forward a new graph structure modeling method based on the Transformer architecture that employs precise relation encoding and delivers a more efficient way for global graph representation. The mappings between the graphs are learned both in semi-supervised and unsupervised training mechanisms. The results of our experiments in Arabic–English, French–English, and Spanish–English plagiarism detection show that our graph transformer method surpasses the state-of-the-art cross-lingual plagiarism detection approaches with and without paraphrasing cases, and provides further insights on the use of knowledge graphs on a language-independent model.
Hypergraph convolutional neural network-based clustering technique
Authors: Tran Loc H. , Trinh Nguyen , Tran Linh H.
Published: July 2022

This paper constitutes the novel hypergraph convolutional neural networkbased clustering technique. This technique is employed to solve the clustering problem for the Citeseer dataset and the Cora dataset. Each dataset contains the feature matrix and the incidence matrix of the hypergraph (i.e., constructed from the feature matrix). This novel clustering method utilizes both matrices. Initially, the hypergraph auto-encoders are employed to transform both the incidence matrix and the feature matrix from high dimensional space to low dimensional space. In the end, we apply the k-means clustering technique to the transformed matrix. The hypergraph convolutional neural network (CNN)-based clustering technique presented a better result on performance during experiments than those of the other classical clustering techniques.
A multi-scale dual-stage model for PV array fault detection, classification, and monitoring technique
Authors: Ghazali Siti Nor Azlina Mohd , Sujod Muhamad Zahim
Published: July 2022

The output generated by photovoltaic arrays is influenced mainly by the irradiance, which has non-uniform distribution in a day. This has resulted in the current-limiting nature and nonlinear output characteristics, and conventional protection devices cannot detect and clean faults appropriately. This paper proposes a low-cost model for a multi-scale dual-stage photovoltaic fault detection, classification, and monitoring technique developed through MATLAB/Simulink. The main contribution of this paper is that it can detect multiple common faults, be applied on multi-scale photovoltaic arrays regardless of environmental conditions, and be beneficial for photovoltaic system maintenance work. The experimental results show that the developed algorithm using supervised learning algorithms mutual with k-fold cross-validation has produced good performances in identifying six common faults of photovoltaic arrays, achieved 100% accuracy in fault detection, and achieved good accuracy in fault classification. Challenges and suggestions for future research direction are also suggested in this paper. Overall, this study shall provide researchers and policymakers with a valuable reference for developing photovoltaic system fault detection and monitoring techniques for better feasibility, safety, and energy sustainability.
Scientific tools for forming professional competence of patrol police officers
Authors: Bondarenko Valentyn , Okhrimenko Ivan , Piaskovskyi Vadym , Antoshchuk Andrii , Marchuk Alla
Published: July 2022

In this paper, the scientific sources analysis was presented. The peculiarities of the professional competence formation of the future patrol officers were determined. Moreover, the specifics of the service activity of patrol officers were considered. The original method for the formation of professional competence of modern police officers was substantiated and tested its effectiveness. The essence of this methodology was to introduce simulated situational tasks, aimed at forming the professional skills and abilities of future police officers. The pedagogical experiment involved students of the primary vocational training course applied in 2018 (n=183) who were studying at the center of primary vocational training “Police Academy” of the National Academy of Internal Affairs (Kyiv, Ukraine). An experimental (EG, n=93) and control (CG, n=90) group were formed. Cognitive and operational criteria evaluated the efficiency of the original methodology. The results of the pedagogical experiment indicated the greater efficiency of the original methods compared to the traditional one. A significant (р<0.05-0.001) improvement of the indicators “Knowledge of professional and practical course”, “Professional and practical skills formation” and “The effectiveness of solving scenarios” was designated. 
Assessment on disposal practices of unused and expired medications
Authors: Alice Amritha , Sunil Athira , Nallasamy Venkateswaramurthy , Ramanathan Sambathkumar
Published: July 2022

Pharmaceutical disposal practices have become a global issue that has caught the concern of health authorities, pharmaceutical firms, healthcare practitioners, and the general public. The current study aimed to assess the disposal practices of unused and expired medications among the households Namakkal district, Tamil Nadu, India. The qualitative, cross-sectional study was conducted using a well-structured questionnaire form. A total of 400 responses were obtained from each member of the family. Participants under the age of 18 were excluded from the study. Respondents who refused to participate were not included in the study. More than 50% of the study population reported that they stored unused and expired medications at home. Most of the participants revealed that the unused medications they stored costs approximately ≤₹300. Majority of participants dispose unused/expired medications by means of trash can (53.1%). A significant population (71.2%) was unaware of novel disposal practices like drug take-back system. The study concluded that there is an inappropriate disposal practice among households which has to be rectified by providing awareness among the public. Further studies should be conducted for the development of well formalized protocol regarding proper disposal practices.
Mandatory COVID-19 vaccination in human rights and utilitarianism perspectives
Authors: Zaid Zaid , Hernowo Wempy Setyabudi , Prasetyoningsih Nanik
Published: July 2022

Departing from the mandatory vaccination had been debated and received a lot of rejection which has caused intense emotions. In this study, the authors tried to evaluate the mandatory regulation of coronavirus disease 2019 (COVID-19) vaccination from a human rights and utilitarianism perspective. By conducting normative research method, this study revealed that indeed the obligation that tends to be coercive for COVID-19 vaccination seems to violate individual human rights which each individual has the right to decide for themselves whether they want to participate in the program or not without coercion. However, mandatory vaccination is still justified, from a human rights perspective, to protect other people's rights not to be infected with infectious diseases. This is also in line with a utilitarian perspective that departs from the argument that vaccines provide a myriad of benefits for many people in the midst of a pandemic, therefore to create benefits for the majority of society, the mandatory COVID-19 vaccination is something that is needed. Even if necessary, both sanctions and punishments can be justified in utilitarianism to achieve the greatest utility for the society.
Psychometric evaluation of community advancing resilience toolkit assessment survey Indonesian version
Authors: Saifudin I Made Moh Yanuar , Noviana Uki , Haryanti Fitri
Published: July 2022

This study aimed to conduct a psychometric evaluation of the Indonesian version of the Communities Advancing Resilience Toolkit Assessment Survey (CART-AS) instrument with validity and reliability testing. A cross-sectional study was conducted among 280 respondents. The translation was done using the Beaton method. The psychometric test process was conducted by testing the construct validity and reliability. Confirmatory factor analysis (CFA) values indicated that the model fits the previous model with the Chi-square/df=1.37 conformity indicator; comparative fit index (CFI)=0.99; goodness of fit index (GFI)=0.90; root mean square of approximation (RMSEA)=0.03; and standardized root mean square residual (SRMR)=0.03. In the CFA measurement, the convergent validity value or the loading factor value of each indicator was also found in the range of 0.55-0.99. The average variance extracted (AVE) values on the five constructs of the CART-AS instrument show values in the range of 0.55-0.98. The results of the reliability test showed the Cronbach alpha value of 0.94. The Indonesian version of the CART-AS instrument is a valid and reliable instrument to measure the resilience of disaster-affected communities in Indonesian culture.
Satisfaction with life during the COVID-19 pandemic: the role of affect balance and self-concept clarity
Authors: Sow Qing Erh , Prihadi Kususanto Ditto , Tjahjani Ida Kusnawati
Published: July 2022

As one significant indicator of mental wellbeing, satisfaction with life plays important roles in the society and among individuals. Nevertheless, studies have stated that the formation of life satisfaction was different between before and during the pandemic. Among most people, the differences were caused by the implication of social distancing protocols, where people were not fully connected to one another without the help of electronic media; therefore, some of their social roles were altered or became less meaningful. Such changes affected the clarity of how individuals see themselves, as well as the balance of their negative and positive emotional experiences (affect balance). We hypothesized that self-concept clarity predicts life satisfaction through affect balance. We collected our data from 139 Malaysian adults aged between 18 to 60 years through various social media platforms to complete the self-concept clarity scale (SCCS), satisfaction with life scale (SWLS), and scale of positive and negative experience (SPANE). Results of the bootstrap analysis with a 95% confidence interval indicated that the affect balance partially mediated the relationship between self-concept clarity and life satisfaction.
Holistic self-management behavior among urban patients with type 2 diabetes
Authors: Tran An Ha Thi , Tran Ngoc Nguyen
Published: July 2022

This study aimed to measure the self-care practices of type 2 diabetes mellitus (T2DM) patients managed in an urban hospital in Hanoi, Vietnam. An observational cross-sectional study was performed. The adherence of self-care practices was measured by using the Condition-specific Recommendations and Adherence scale. Among 165 T2DM patients, nobody adhered to all self-care practices. The average number of adhered behavioral recommendations was 6.0 (SD=1.6). Gender, education and overweight/obesity were associated with self-care practice adherence. Repeated educational sessions should be provided to patients, especially male patients, and those with low education levels, overweight/obese, to improve their self-care ability.
Appreciative joy, nostalgia and prosocial behavior: a different approach on mental wellbeing maintenance
Authors: Chong Jia Cheng , Prihadi Kususanto Ditto , Hong Susanna Poay Lin , Purwaningrum Evy Kurniasari
Published: July 2022

The effect of maintaining mental wellbeing by conducting prosocial behavior has been established for quite some time and is supported by many theories. Nevertheless, prosocial behavior might not easily be done by individuals with negative feelings due to certain emotional burdens. The current study examined the mediating effect of appreciative joy in the relationship between nostalgia and prosocial behavior. There were 123 undergraduate students with an average age of 21.2 years old recruited from a Malaysian private university using the purposive sampling method. Employing an experimental single-factor independent design; the experiment was conducted online. Multiple regression analysis showed that only the relationship between appreciative joy and prosocial behavior is statistically significant in this study, without being mediated by appreciative joy. In conclusion, nostalgia did not significantly inflict any appreciative joy that eventually drove people to conduct any prosocial behavior. Further implications and suggestions are discussed.
Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
Authors: EKER İSMAİL , TANIŞ EZGİ
Published: July 2022

This paper comprehensively discusses anatomical features of the genus Tulipa (Liliaceae) in Turkey. These are compared with the current subgeneric classification.   Anatomical structures, including transverse sections of the root, stem (scape) and leaf, and surface sections of the leaves are illustrated based on the 420 preparations obtained from 42 OTUs (populations) belonging to 18 taxa. Densities of stomata and epidermis cells per unit leaf area (mm2), stomatal index and ratio of stomata index on the leaf surfaces were also calculated. Cluster and principal component analyses (PCA) were employed, and all results were compared at the population level. In this anatomical study, some significant differences were found among Tulipa taxa, especially at the infrageneric and interspecific levels. The results of anatomical investigations are consistent with published results of previous morphological and molecular analyses. The results of cluster analysis and PCA support the classifications of Veldkamp & Zonneveld and Christenhusz et al. including three subgenera, Eriostemones, Tulipa and Clusianae, but subgenus Orithyia was not included in this study because it is absent from Turkey. Subgenus Eriostemones is divided into two sections, Sylvestres and Saxatiles, following treatments by Baker and Eker et al. In subgenus Tulipa, although morphometric analyses partially supported the taxonomic grouping previously proposed as three separate sections, Tulipa, Tulipanum and Eichleres, it also clearly indicates that considering them as a single section (Tulipa) is perhaps a better option.
Evaluating Tropical Precipitation Relations in CMIP6 Models with ARM Data
Authors: Emmenegger Todd , Kuo Yi-Hung , Xie Shaocheng , Zhang Chengzhu , Tao Cheng , Neelin J. David
Published: July 2022

A set of diagnostics based on simple, statistical relationships between precipitation and the thermodynamic environment in observations is implemented to assess phase 6 of the Coupled Model Intercomparison Project (CMIP6) model behavior with respect to precipitation. Observational data from the Atmospheric Radiation Measurement (ARM) permanent field observational sites are augmented with satellite observations of precipitation and temperature as an observational baseline. A robust relationship across observational datasets between column water vapor (CWV) and precipitation, in which conditionally averaged precipitation exhibits a sharp pickup at some critical CWV value, provides a useful convective onset diagnostic for climate model comparison. While a few models reproduce an appropriate precipitation pickup, most models begin their pickup at too low CWV and the increase in precipitation with increasing CWV is too weak. Convective transition statistics compiled in column relative humidity (CRH) partially compensate for model temperature biases—although imperfectly since the temperature dependence is more complex than that of column saturation. Significant errors remain in individual models and weak pickups are generally not improved. The conditional-average precipitation as a function of CRH can be decomposed into the product of the probability of raining and mean precipitation during raining times (conditional intensity). The pickup behavior is primarily dependent on the probability of raining near the transition and on the conditional intensity at higher CRH. Most models roughly capture the CRH dependence of these two factors. However, compensating biases often occur: model conditional intensity that is too low at a given CRH is compensated in part by excessive probability of precipitation.
Looking Back, Looking Forward: A Personal Reflection
Authors: White Jonathan R.
Published: July 2022

This article contains a personal reflection of experiences in terrorism research over the past few decades. It begins by discussing early academic struggles to recognize the legitimacy of terrorism research, especially in the field of criminal justice. This is followed by a selective description of events where the author correctly predicted events as well as those where he was blindsided by surprises. It closes with an appeal to both the academy and the American public to move beyond ideology and populist understandings of terrorism to grapple with the multiple forms and complexities of terrorist violence.