bluuebunny/crossref_metadata_2025 huggingface dataset:
Data-driven modeling and parameter estimation of nonlinear systems
Authors: Kumar Kaushal
Published: July 2023

Nonlinear systems play a significant role in numerous scientific and engineering disciplines, and comprehending their behavior is crucial for the development of effective control and prediction strategies. This paper introduces a novel data-driven approach for accurately modeling and estimating parameters of nonlinear systems utilizing trust region optimization. The proposed method is applied to three well-known systems: the Van der Pol oscillator, the Damped oscillator, and the Lorenz system, which find broad applications in engineering, physics, and biology. The results demonstrate the efficacy of the approach in accurately identifying the parameters of these nonlinear systems, enabling a reliable characterization of their behavior. Particularly in chaotic systems like the Lorenz system, capturing the dynamics on the attractor proves to be crucial. Overall, this article presents a robust data-driven approach for parameter estimation in nonlinear dynamical systems, holding promising potential for real-world applications.

Graphic Abstract
Investigating the connection between generalized uncertainty principle and asymptotically safe gravity in black hole signatures through shadow and quasinormal modes
Authors: Lambiase Gaetano , Pantig Reggie C. , Gogoi Dhruba Jyoti , Övgün Ali
Published: July 2023

The links between the deformation parameter$$\beta $$βof the generalized uncertainty principle (GUP) to the two free parameters$$\hat{\omega }$$ω^and$$\gamma $$γof the running Newtonian coupling constant of the Asymptotic Safe gravity (ASG) program, has been conducted recently in [Phys. Rev. D 105 (2022) 12, 124054. https://doi.org/10.1103/PhysRevD.105.124054] In this paper, we test these findings by calculating and examining the shadow and quasinormal modes of black holes, and demonstrate that the approach provides a theoretical framework for exploring the interplay between quantum gravity and GUP. Our results confirm the consistency of ASG and GUP, and offer new insights into the nature of black holes and their signatures. The implications of these findings for future studies in quantum gravity are also discussed.
Midwives’ and Diabetes Nurses’ Experience of Screening and Care of Women with Gestational Diabetes Mellitus: A Qualitative Interview Study
Authors: Köpsén Sofia , Lilja Mikael , Hellgren Margareta , Sandlund Jonas , Sjöström Rita
Published: July 2023

Background. Gestational diabetes mellitus (GDM) is increasing and is associated with adverse outcomes for both mother and child. The metabolic demands of pregnancy can reveal a predisposition for type 2 diabetes mellitus (T2DM), and women with a history of GDM are more likely to develop T2DM than women with normoglycemic pregnancies. Aim. The aim of this study was to explore midwives’ and diabetes nurses’ experience of their role in screening, care, and follow-up of women with gestational diabetes mellitus and, further, to explore their opinions and thoughts about existing routines and guidelines. Method. Individual interviews were performed with ten diabetes nurses and eight midwives working in primary and special care. Qualitative content analysis was done according to Graneheim and Lundman. Results. The analysis of the interviews resulted in the overall theme “An act of balance between normalcy and illness, working for motivation with dilemmas throughout the chain of health care.” Difficulties in carrying out the important task of handling GDM while at the same time keeping the pregnancy in focus were central. Women were described as highly motivated to maintain a healthy lifestyle during pregnancy with the baby in mind, but it seemed difficult to maintain this after delivery, and compliance with long-term follow-up with the aim of reducing the risk of T2DM was low. The women came to the first follow-up but did not continue with later contact. This was at a time when the women felt healthy and were focusing on the baby and not themselves. A lack of cooperation and easy access to a dietician and physiotherapist were pointed out as well as a wish for resources such as group activities and multiprofessional teams.
Distribution networks power loss allocation with various power factors
Authors: Mishra Debani Prasad , Senapati Rudranarayan , Sahoo Arun Kumar , Sahu Jayanta Kumar , Salkuti Surender Reddy
Published: July 2023

The users of power distribution and transmission networks are generally guided to sustain advanced power factor (PF) of load as it is affecting the power loss of a feeder network where it separately owns major influence on electric charges layout. Therefore, some cautious loss allotment schemes are to be incorporated and an acceptable satisfying/penalizing policy for advanced/less PF users, independently. Keeping this in view, the mentioned article proposed a new scheme, i.e., the active power loss allocation (APLA) procedure which allows power loss to the system distributors by considering the load demands, topographical localities, and PFs. A newly modified procedure assigns inducements hardly to all the involved utilizers against change in load PF continuously, where it is evaluated via proper mathematical and statistical study. The efficiency of the newly modified APLA scheme is explored in two dissimilar frameworks of low PF using 33 bus system radially distributed network (RDN). The interpretation is in favor of examined transmitted, distributed, and allows generated PF to be verified subsequently. Comparatively, the results achieved highlight the originality of the present method compared with different standard schemes/frameworks.
Fault analysis in grid-connected solar photovoltaic systems based on multi-objective grey wolf optimisation
Authors: Satyanarayana Vanam , Krishnamoorthy Vinoth
Published: July 2023

The renewable energy resources depend on environmental concerns. Photovoltaic (PV) systems are an interesting form of renewable energy resource. The two main problems associated with PV systems are nonuniformity of irradiation and temperature change. PV achieving maximum power point tracking are dependent on power electronics converters. Emissions are a key challenge for the future of conventional renewable energy resources, which play an important role in the generation system. It is crucial in applications and industry because the primary goal of optimization is to discover specific research. We offer using the population of search agents based on fitness, the multi-objective grey wolf optimizer, a more modern meta-heuristic based on the hunting habits and social structure of grey wolves, for optimizing adaptive controllers for failures in grid analysis and power system integration various faults in the grid cause several power quality issues. Harmonics, voltage sag and swell imbalances, and many power conditioning topologies. This was carried out using MATLAB/Simulink, and the results showed a superior and flexible performance in reducing voltage sag and voltage swell problems and imperfections at various loading situations.
Area control error enhancement of two-area power system using hybrid intelligence optimal controller
Authors: Abdillah Muhammad , Setiadi Herlambang
Published: July 2023

Area control error (ACE) is a critical factor in linked power systems. When a disturbance occurs, ACE is utilized to determine how much power should be deployed. As a result, it is critical that the ACE have as little inaccuracy as feasible. This research provided a strategy for improving the dynamic response of ACE in a power system. A hybrid optimal controller is the name given to this technology. Coordination between the proportional-integral (PI) controller and the state feedback controller based on the linear quadratic regulator (LQR) is the concept of a hybrid optimum controller. All controller parameters are created utilizing artificial immune system (AIS) clonal selection to improve coordination. The proposed control mechanism is demonstrated using a two-area power system as a test system. To investigate the efficacy of the suggested strategy, time domain simulation is used. The simulation results show that the suggested method outperforms the previous situations in this work (the overshot of frequency deviation in areas 1 and 2 is 0.00029 and 0.00015, respectively)
Evaluation of CHB MLI based shunt APF using low pass filter and self-tuning filter
Authors: Yusup Lada Musa , Amran Mohd Radzi Mohd , Jasni Jasronita , Hizam Hashim , Jidin Auzani , Hisham Mohamad Syahrul
Published: July 2023

The increasing demand for high-rating power supply in the distribution system causes the conventional inverter topology, six step voltage source inverter (SSVSI) unsuitable for being applied as active power filter (APF). Multilevel inverter (MLI) is generally the best suitable inverter for APF, but not all types of MLI can be used for high-voltage applications. Among the MLIs topology, cascaded H-bridge (CHB) is the best choice since it can produce output voltage more than twice the amount of DC source. Moreover, CHB MLI topology uses fewer power devices and is simple in design. Low pass filter (LPF) is a common method used for harmonic extraction in this controller. However, this method faces various problems, such as an additional need for phase lock loop (PLL) algorithm and slow transient and steady-state responses. Therefore, self-tuning filter (STF) is introduced as a new filtering method to overcome this problem. This paper evaluates CHB MLI's performance for APF using STF as a harmonic extraction. The model was developed and verified in MATLAB/Simulink. The results show that harmonic extraction using STF performs better total harmonic distortion (THD) than conventional LPF. Nevertheless, both algorithms produce THD below 5%, defined as the permissible value stated in IEEE 519.
A unified power flow controller-based robust damping controller considering time delay in electrical power systems
Authors: Zadehbbagheri Mahmoud , Ildarabadi Rahim , Sutikno Tole
Published: July 2023

Nowadays, different power systems are connected to each other due to technical and economic reasons and form a complex developed network. Such networks measure and send system data to decision-making centers for control and protection. This information transmission is accompanied by a delay and causes the performance of the system’s damping controllers to be affected. To improve power system dynamic stability, the supplementary controller in flexible alternating current transmission system (FACTS) devices is designed to account for information transmission delays. In these methods, to increase the controllability and observability of the inter-area mode, the remote signals extracted from the wide area measurement system (WAMS) are used as the input of the modulator. WAMS systems’ time delay reduces power system stability and even causes instability, so it’s crucial to find the maximum delay margin that ensures stability. Therefore, it is necessary to carefully study the role of FACTS tools in stabilizing the power system and damping interregional fluctuations, considering the delay. This research shows that supplementary controller design can dampen frequency and load angle fluctuations in multi-zone power systems despite information transmission delays. The method works in power system analysis toolbox (PSAT) simulation and MATLAB programming.
Design thermohygrometer based on internet of things in clinical laboratory
Authors: Agus Mahardiananta I Made , Vierda Lya Suandari Putu , Agung Ngurah Devasya Putra Pratama I Gusti
Published: July 2023

Clinical laboratory units must meet safety requirements such as temperature stability and room humidity because the materials and substances used are sensitive to changes in temperature and environmental conditions, so it is important to carry out routine monitoring. The purpose of this research is to design an internet of things (IoT)-based thermohygrometer that can make it easier for users to monitor temperature and humidity even though the user is outside the laboratory. This tool can also store the results of temperature and humidity measurements making it easier for the user to monitor changes in temperature and humidity that occur. The method used is descriptive exploratory with a prototype system, namely the system development process, users and the required data and results obtained through a tool that has been designed. The results of research conducted using an IoT-based thermohygrometer prototype after statistical testing, there was no significant difference between the reference thermohygrometer and the IoT-based thermohygrometer prototype and the readings from the thinkspeak web. For temperature and humidity measurements that have been carried out at the X clinical laboratory in Denpasar, it still does not meet the standards.
Enhancement of luminous efficacy for light-emitting diodes lamps by adding CaSr2(PO4)2:Eu3+ phosphor
Authors: Minh Trung Ho , Hanh Nguyen Thi My
Published: July 2023

Through employing the fluid ignition technique, we created the samples CaSr2(PO4)2:Eu3+ with Eu3+ incorporated then assessed them in the form of contactless optical heat measurement as well as solid-state illumination. We identified the attributes for these samples including X-ray diffraction (XRD), photoluminescent spectroscopy, Fourier transmute infrared spectroscopy (FTIS) along with photoluminescent spectroscopy correlating with temperature. XRD, along with FTIS, validates that the one-stage samples were formed via the orthophosphate anion (PO4)3- . In the case of these samples, nUV recreation under 395 nm generated potent, orange-red discharge lines under 592 nm as well as 615 nm, which is consistent with the standard shifts between 5D0 and 7F1 as well as 5D0 and 7F2 for the Eu3+ ions. The International Commission on Illumination (CIE) coordinates (0.65, 0.35) based on the hue scale validate the red discharge. For the task of attaining optical heat measurement, we took advantage of the fluorescent intenseness proportion technique that utilizes heat-incorporated discharge states of 5D1 as well as 5D0 for Eu3+ . The samples have maximum responsiveness reaching roughly 0.0023 K-1 under 323 K or small heat levels. According to the outcomes, it is possible to utilize the samples when it comes to contactless optical heat measurement as well as solid-state illumination.
Development of dam controller technology water level and alert system using Arduino UNO
Authors: Zin Mazratul Firdaus Mohd , Kamal Farid Zuhri , Ismail Syila Izawana , Noh Ku Siti Syahidah Ku Mohd , Kassim Abdul Hafiz
Published: July 2023

Recently, various water level detection monitoring systems integrations were implemented to various places such as rivers and reservoirs to avoid floods. Thus, it is determined to construct a project primarily focused on water level management, named dam controller technology (DCOTech). DCOTech is a system that controls the amount of water in a reservoir using a microcontroller ATMEGA328p and several functions to prevent flash floods. Water sustainability requires proper monitoring via sensors and a controller. Moreover, a buzzer is used in DCOTech to give a warning signal to the people around and the residents. The water level sensor was constructed with a metal plate attached at both the bottom and top edges of the reservoir. The results obtained met expectations; whenever the sensor detects the water level is low, the green light emitting diode (LED) is turned on; otherwise, when the sensor detects the water level is high, the drain valve is opened, and simultaneously, turned on the buzzer to alert the surrounding. The goal of this project is to integrate a control system into an autonomous water level controller. This study aims to provide a solution to unexpected floods and to notify inhabitants when the water level is dangerously high.
Design of inception architecture for skin melanoma classification
Authors: Manikandan Sankarakutti Palanichamy , Karthikeyan Vedanandam , Nalinashini Ganesamoorthy
Published: July 2023

The number of people diagnosed with skin cancer is increasing sharply. Both invasive and non-invasive methods of examination may be used to investigate it. However, the invasive method is more difficult for the patient because samples must be taken from the lesion itself, or the whole lesion must be cut out. It also requires more time and cost. To avoid invasive procedures, computer-based analysis and diagnosis have the potential to increase diagnostic accuracy and turnaround time. This study develops a unique discriminative deep learning architecture (DDLA) for dermoscopic image classification (DIC), called DDLA-DIC, which uses the concept of inception. Using this concept, the proposed DDLA-DIC system is designed wider and deeper and the network learns from various spatial patterns. The proposed DDLA-DIC system can extract image characteristics from dermoscopic images for skin cancer diagnosis in an effective and efficient way. The proposed DDLA-DIC system is evaluated by utilizing the dermoscopic images from the PH2 database, and the obtained classification results are based on a random split approach. The simulation results indicate that the framework has a great deal of potential with 99.79% accuracy.
Non-contact evaluation of pigs’ body temperature under various infrared sources
Authors: Nguyen Hoc Thai , Dao Tien Xuan , Ngo Duong Tri
Published: July 2023

The purpose of this study is to verify the feasibility of using an infrared camera to measure the surface temperature and then estimate the core body temperature of pigs under various infrared sources. We first conducted experiments with pig-body temperature measurement by an infrared camera. Then we have tried to increase the accuracy rate in estimating the core body temperature of pigs by measuring the temperature of moving pixels. We concluded that the relation between the core body temperature and the estimated pig-body temperature was y = 1.0392x−0.6621 with no static infrared source in the field view of infrared camera. With the existence of heat lamps in the field of view of the infrared camera, the relation was y = 1.0248x − 0.0921. With both the root mean square error and the mean absolute error lower than 1.12 ◦C, the experimental simulation results show that the proposed method is feasible and effective in fast and non-contact evaluation of pigbody temperature under various infrared sources.
A 2 shape slot microstrip patch antenna for global positioning system satellite communication applications
Authors: Basar Md Rubel , Al-Amin Md , Mirza Effat , Debnath Partha Pratim , Awal Md Rabiul
Published: July 2023

In this paper, a compact two-shape slot microstrip antenna is proposed for global positioning system (GPS) satellite application. The proposed antenna is designed with FR 4 substrate with a height of 1.6 mm, a dielectric constant εr of 4.3 within a compact size 56 x 56 mm2 area. The design parameters are optimized to achieve good performance. At the optimum setting of design parameters, this antenna shows good characteristics to cover L1 band 1,575.42 MHz, ± 12 MHz frequency which is used for GPS satellites. At the 1,572 MHz resonance frequency, this antenna achieves a minimum return loss of -30 dB covering a frequency bandwidth of 50 MHz (1,550 MHz – 1,600 MHz) at -10 dB reference level which ensures 100% bandwidth coverage of the L1 band. Besides, the proposed antenna achieved a maximum gain of 8.3 dBi and a beam width of 1010 at -3 dB point. In terms of other performance, such as voltage standing wave ratio (VSWR), directivity, radiation pattern, the proposed antenna shows good performance for the application of GPS satellites.
Implementing and developing secure low-cost long-range system using speech signal processing
Authors: Alabed Samer , Alsaraira Amer , Mostafa Nour , Al-Rabayah Mohammad , Kotb Yehia , Saraereh Omar A.
Published: July 2023

In the proposed work, we present a secure low-cost speech communication system for long-distance communication. The system utilizes long range (LoRa) technology to transmit speech signals. LoRa technology uses spread-spectrum modulation to enable long-range communication with low power consumption. LoRa modulation allows for data transfer at a slow speed, typically below 22 kbps, which makes it infeasible for transmitting speech. To address this limitation, we suggest a speech coding technique that reduces the overall data rate of speech signals to below 7.5 kbps. This lower rate is more compatible with the LoRa module and ideal for transmitting speech. Moreover, this technique can improve the LoRa transmission range. Additionally, we have developed an encryption-decryption method to ensure the privacy of the messages and prevent unauthorized access by third parties.
Channel characterization and modeling for wireless communication link planning and design in the tropics
Authors: Famoriji Oluwole John , Shongwe Thokozani
Published: July 2023

Channel model provides basis in the link budgetary for planning and design of low margin systems of communication links. This paper proposed a simple and efficient channel model for wireless channel path loss characterization and modeling. Free space channel was characterized and modelled to account for both static and dynamic changes of signal that propagates through it. Correction factors in the model account for the losses due to refraction effects, as a result of abnormal refractivity condition frequent in tropical regions. The model was validated via measurement data from experiment conducted in a tropical region and a high level of agreement was observed. The proposed model can be deployed during link planning and budgetary for ultra high frequency (UHF) wireless radio services.
Energy efficient secured-quality of service routing protocol for mobile ad hoc network using multi-objective optimization
Authors: Ramasamy Veeramani , Ramalingam Madhan Mohan , Chitraivel Mahesh
Published: July 2023

This article proposed a hybrid energy-efficient secured quality of service (QoS) based multipath routing protocol. A modified crow search combined with the tunicate swarm butterfly optimisation algorithm (TSBO) with a density-based clustering technique strategy is proposed for the selection of cluster heads after the initial cluster formations. Among all the nodes, the cluster head is selected, and employing the collaborative trust-based approach (CTBA), which employs the trust factor for mobile ad hoc network (MANET) data transmission, a node's authentication is supplied. Finally, to implement the safe routing technique, this article suggested a hybrid multipath routing protocol combining multi-objective grey wolf optimisation (MO-GWO) with a fruit fly algorithm. The NS3 simulator is used to assess the proposed work. The packet delivery ratio metric performs 4% better than the current models. As a result, the suggested approach performs better for the end-to-end delay, energy consumption, packet delivery ratio (PDR), and throughput; it also uses less energy and has a shorter delay. Additionally, single-path nodes with the same energy value have lower throughput than multi-path nodes.
Islamic moderation in education and the phenomenon of cyberterrorism: a systematic literature review
Authors: Ma'arif Syamsul , Ibda Hamidulloh , Ahmadi Farid , Qosim Nanang , Muanayah Nur Alfi
Published: July 2023

This article presents a systematic literature review on Islamic moderation in education to prevent cyberterrorism in the latest literature. The method used is the systematic literature review and preferred reporting items for systematic reviews and meta-analyses protocol with the stages of identification, screening, eligibility, inclusion, abstraction, and data analysis assisted by PoP 7, VOSviewer, and NVIVO 12 plus. The search results in Scopus contained 1,252 articles, then filtered according to compatible themes into 54. The topic findings are the concept of Islamic moderation, Islamic moderation in preventing cyberterrorism in education, cyberterrorism, cyberterrorism phenomenon, terrorism, religious moderation, wasatiyyah, peaceful coexistence, and counter-terrorism. The findings of the results mention that Islamic moderation is a way of religion according to the principles of the Quran and Sunnah, namely ummah wasatan, which is applied to education. Cyberterrorism phenomenon curs in various parts of the world, including in education, which is spread through cyberspace to intimidate, spread fear, and destroy the order of life in terrorist groups. Islamic moderation plays a role in preventing cyberterrorism in education through ideological approaches to radical organisations, accommodation of local culture, digital literacy, counter-narrative and deradicalisation, digital media mastery, digital media peaceful, and soft power deterrence. Future research needs to explore Islamic moderation according to the times.
Application of artificial neural networks for personality traits prediction based on handwriting
Authors: Remaida Ahmed , Abdellaoui Benyoussef , Lafraxo Mohamed Amine , Sabri Zineb , Nouib Hamza , Idrissi Younes El Bouzekri El , Moumen Aniss
Published: July 2023

The automatization of personality traits prediction still brings considerable research these days, especially when the detection could be achieved without administrating personality assessment instruments. With the evolution of computational intelligence, a variety of deep machine learning techniques were developed and proposed for that purpose. Nevertheless, proposing robust and rapid systems to solve this problem remains a challenging task. The process of feature extraction is the main key. This paper presents an effective method for extracting five graphological features from handwriting ensuring the prediction of personality traits based on the big five personality traits model. We started by collecting both handwriting samples and big five questionnaires, then the feature extraction process, after that the data preparation and finished with the application of several popular deep machine learning models to achieve the prediction. Experimental results indicate the remarkable performance of the multi-layer perceptron (MLP) compared to other classifiers, the model was 100% precise and classification accuracy attained 100% for trained data and 72.73% for new tested data. With only 100 participants, we strongly believe that our proposed method is simple and promising, and better results will be attained with a larger dataset.
Image classification using machine learning
Authors: Mishra Debani Prasad , Mishra Sanhita , Jena Smrutisikha , Salkuti Surender Reddy
Published: July 2023

The objective of this paper is to implement different tools available in machine learning/artificial intelligence to classify faces and identify different features, highlights, and correlations or similarities between different celebrity faces which can apply in everyday security purposes to identity virtually if the authorized personnel is using certain access or not. The material present in this paper is a literature review of a machine learning model developed by the students. This is a classical problem of machine learning executed using a support vector machine. Images are separated based on sub-images. Each sub-image has been classified into a responsive class by an artificial neural network. The website then fetches the data from the back end and classifies the image into the corresponding personal.
Cluster analysis of socio-economic factors and academic performance of school students
Authors: Devi Kapila , Ratnoo Saroj
Published: July 2023

The objective of the paper is to examine the academic performance of students’ vis-a-vis socio-economic factors using clustering analysis. The grades obtained in the 10th class are taken as the measure of academic performance. The variables such gender, caste, parental education and occupation. are considered as the socio-economic indicators. Three clustering algorithems are employed. The K-medoid performs better in the validation process to form the groupings based on intra-cluster homogeneity and inter-cluster heterogeneity. The clustering analysis results in two interesting groups of the students. One of the clusters is dominated by the students of general category and the other one by the scheduled caste category. Next, the appropriate statistical tests are applied to determine the factors that significantly differ in the two clusters. Cluster analysis shows that caste, parents' education and occupation, and family income are the differentiating factors between the two groups. However, we are unable to establish significant difference between the academic performance of the two groups of students at a 5% significance. The research carried out in this paper may be beneficial for making policies to bridge the gap in the educational attainment of the students from deprived sections of society.
Identification of medicinal plant using hybrid transfer learning technique
Authors: Ghosh Sukanta , Singh Amar , Kumar Shakti
Published: July 2023

Ayurveda is one of the oldest holistic treatment systems in the world. Finding an accurate and correct plant is the key to the working of Ayurvedic treatment. Identification of medicinal plants is a tedious job due to the look-alike feature and availability issue of medicinal plants with other plants. This paper emphases on the ideal identification and classification of plants of medicinal use using deep learning approaches. Previously researchers have used traditional machine learning techniques to identify medicinal plants, which lead to mixed results. Such results are good but not enough as the identification of medicinal plants may lead to a worsening situation for patients. This research is conducted to get results closer to an ayurvedic expert. The dataset used for this research has been taken from Mendeley Data. The dataset comprises 30 different species of medicinal plants. Hybrid transfer learning has been applied to this dataset. The model has generated a test accuracy of 95.25% which is better than the other popular transfer learning techniques.
Quantifying quantitative correlation of provider selection influences cloud security
Authors: Aziz Azlinda Abdul , Osman Salyani , Widyarto Setyawan , Marjudi Suziyanti , Suradi Nur Razia Mohd , Handan Rahayu
Published: July 2023

The cloud computing has been able to help users to access the data easily and effectively. However, cloud security is highly emphasized to cloud users to ensure data is securely stored. The cloud security can be handled well by chosen trusted cloud service provider in getting high impact on the cloud security. The relationship between cloud security with the provider selection is much needed to ensure the extent to which data is securely stored in a cloud. Therefore, in this paper the quantitative method was conducted to measure the correlation between the selected the right cloud service provider influence the cloud security. Thus, knowledgeable person in having the experiences in using the cloud service was taking from two institution of higher learning (IHL) as a respondent. In addition, variability and normality data analysis was firstly conducted to obtain the consistency of the data. Then, the correlation between cloud security factor and provider selection factor was conducted using spearman correlation matrix and scatter graph in identifying the closely and significant the value in influencing between the factors. Thus, the correlation relationship analysis result shown the selected the right cloud provider’s give higher impact to cloud security.
The blockchain internet of things: review, opportunities, challenges, and recommendations
Authors: Al-Shareeda Mahmood A. , Saare Murtaja Ali , Manickam Selvakumar
Published: July 2023

A new technology known as the internet of things (IoT) allows both physical and virtual items to be linked and communicated with one another, creating new digital services that enhance our fineness of sustenance. The IoT system has a number of benefits, but because of its present centralized architecture, there are several problems with regard to data integrity, security, privacy, and single points of failure. The future development of IoT applications is hampered by these difficulties. To tackle these problems, it might be best to integrate the Internet of Things with one of the distributed ledger solutions. The blockchain is one of the most frequent and well-liked varieties of distributed ledger technologies. Numerous advantages can result from integrating blockchain technology with the IoT called blockchain internet of things (BIoT). In this paper, we show a brief overview of blockchain, its components of blockchain, and its features of blockchain. Meanwhile, we describe the architecture of BIoT, Issues of BIoT, and BIoT applications. Additionally, this paper provides a future research challenge and open issues.
Categorical encoder based performance comparison in pre-processing imbalanced multiclass classification
Authors: Yustanti Wiyli , Iriawan Nur , Irhamah Irhamah
Published: July 2023

The contribution of this study is to offer suggestions for coding techniques for categorical predictor variables and comprehensive test scenarios to obtain significant performance results for imbalanced multiclass classification problems. We modify scenarios in the data mining process with the sample, explore, modify, model, and assess (SEMMA) framework coupled with statistical hypothesis testing to generalize the model performance evaluation conclusions as enhanced-SEMMA. We selected four open-source data sets with unequal class distributions and categorical predictors. Ordinal, nominal, dirichlet, frequency, target, leave one, one hot, dummy, binary, and hashing encoder methods are used. We use the grid-search technique to find the best hyperparameters. The F1-Score and area under the curve (AUC) are evaluated to select the optimal model. In all datasets with 10-fold stratified cross-validation and 95% to 99% accuracy for each dataset, the results show that support vector machine (SVM) outperforms the decision tree (DT) K-nearest neighbor (KNN), Naïve Bayes (NB), logistic regression (LR), and random forest (RF) algorithms. Probability-based or binary encodings, such as target, Dirichlet, dummy, one-hot, or binary, are best for situations with less than 3% of minor class proportions. Nominal or ordinal encoders are preferred for data with a minor class proportion of more than 3%.
Enhancing attendance tracking using animated QR codes: a case study
Authors: Mohammed Mustafa Saad , Zidan Khamis A.
Published: July 2023

This research paper explores the effectiveness of quick response (QR) code-based attendance systems with the added security measure of generating two QR codes per second. With traditional attendance tracking methods being time-consuming and inefficient, QR codes have become increasingly popular as a quick and efficient alternative. However, one concern with QR code-based attendance systems is the potential for fraud and misuse. To address this issue, this study proposes generating two QR codes per second to ensure that only the current and legitimate QR code is recognized. The purpose of this study is to assess the impact of this technology on student attendance rates, the accuracy and reliability of attendance data, and the overall user experience for both students and instructors. Through data analysis and surveys, we found that the use of QR codes with the added security measure resulted in increased student attendance rates, improved accuracy and reliability of attendance data, and a positive user experience for both students and instructors. This research provides practical insights for educational institutions considering the implementation of QR code-based attendance systems and contributes to the growing body of literature on the use of QR codes in education.
Evaluation of machine learning techniques for hypertension risk prediction based on medical data in Bangladesh
Authors: Asadullah Md. , Hossain Md. Murad , Rahaman Sabrina , Amin Muhammad Saad , Sumy Mst. Sharmin Akter , Parh Md. Yasin Ali , Hossain Mohammad Amzad
Published: July 2023

Hypertension in Bangladesh is a leading cause of cardiovascular diseases, stroke, and kidney failure, resulting in significant morbidity and mortality. Preventive measures and simple health practices can effectively reduce hypertension and its complications. This study utilizes machine learning algorithms (Naive Bayes, support vector machine, logistic regression, random forest) to predict hypertension in high-risk individuals. The proposed hybrid model achieves a prediction accuracy of 78.17%, surpassing other machine learning methods. Random forest has the highest accuracy among the individual algorithms at 73.86%. Classification performance is evaluated using sensitivity, specificity, precision, and F-score, along with receiver operating characteristic analyses and confusion matrices through 10-fold cross-validation. These findings emphasize the importance of managing risk factors for better population health and highlight the efficacy of the hybrid model in hypertension prediction. The study underscores the significance of preventive measures in reducing the burden of hypertension-related diseases and improving overall well-being.
Technology integration through acceptance of e-learning among preservice teachers
Authors: Sulistiani Ika Ratih , Setyosari Punaji , Sa'dijah Cholis , Praherdhiono Henry
Published: July 2023

The rapid evolution of online learning necessitates the agility of future educators. Future teachers’ technological attitudes and abilities will be affected by the explication of the role of technology in learning in teacher education. Therefore, preservice teachers must be prepared to implement technology in their future classrooms. This study investigated the effect of technological pedagogical content knowledge (TPACK) competency on the technology acceptance model (TAM)-measured intention to use from two perspectives: self-confidence and self-regulation. Thus, six hypotheses are proposed to investigate the relationship between TPACK proficiency and the intent to use technology. The population of 224 preservice teachers at one Indonesian tertiary institution was analyzed using structural equation modeling (SEM) to confirm five of the six hypotheses. It is stated that attitudes toward TPACK competence positively correlate with self-regulation, self-efficacy, and intent to use technology. In addition, the derived model can account for approximately 53.8% of the intention to integrate technology in the classrooms of preservice teachers.
Species nomina corrections in the Cerambycidae (Insecta, Coleoptera), concerning specific epithets based on letters used to refer to characters of taxa
Authors: LIN MEI-YING , TAVAKILIAN GÉRARD LUC
Published: July 2023

This paper proposes to distinguish three Cases regarding the grammatical gender of species nomina which are composed of an isolated letter connected by a hyphen to a word. [Case 1] The first element is a Latin letter, the second element is another noun: the nomen is a noun in apposition, and its ending is unchanged. [Case 2] The first element is a Latin letter used to denote descriptively a character of the taxon, the second element determines the first and answers the question of its nature: the nomen is a noun in apposition, so its ending must not be changed to agree with the generic nomen but is always neuter, as the Latin letter. [Case 3] The first element is a Latin letter, the second element is a regular adjective which is specified by the first element: the nomen is an adjective, its ending must agree in gender with the generic nomen with which it is combined. Accordingly, 50 species nomina in the family Cerambycidae (Coleoptera) are analyzed and corrected when necessary.
Calotes megapogon (Squamata, Agamidae, Draconinae): nomenclatural and taxonomic ramifications of the naming of an undescribed species
Authors: DENZER WOLFGANG , DONDORP ESTHER
Published: July 2023

During a field expedition to New Guinea in 1828, Salomon Müller discovered a new agamid lizard that was described in his notebook and accompanied by an illustration. He named the species Calotes megapogon, but a formal description was never published. Duméril & Bibron (1837) listed the name as a synonym of Lophyrus dilophus (comb. nov. pro Tiaris dilophus Duméril & Bibron, 1836), and later Gray (1845) treated Tiaris megapogon as a valid species. Through Gray’s action, the name became nomenclaturally available according to Article 11.6.1 of the International Code of Zoological Nomenclature. We rediscovered the type specimens of Calotes megapogon in the collection of the Naturalis Biodiversity Center and studied the unpublished notes from Müller as well as the illustration. By comparison with morphologically similar species, we conclude that Calotes megapogon Duméril & Bibron, 1837 constitutes a senior subjective synonym of both Hypsilurus auritus (Meyer, 1874) and Hypsilurus spinosus (Duméril & Bibron, 1851), and that the name Hypsilurus megapogon (Duméril & Bibron, 1837) needs to be applied to this biological species.
Why Toxicocalamus longhagen Roberts, Iova & Austin, 2022 (Serpentes, Elapidae) is a taxonomic nomen dubium
Authors: KRAUS FRED , O’SHEA MARK , KAISER HINRICH
Published: July 2023

Roberts et al. (2022) presented a taxonomic decision, in which they proposed the species name longhagen for a single, poorly preserved specimen of elapid New Guinean snake in the species assemblage known as the Toxicocalamus loriae Group. Geographically widespread populations in this species group had long been united under a single name even though some character variation had been noted, and only a thorough morphological study by Kraus et al. (2022), published shortly after the description of T. longhagen, confirmed additional species-level diversity and the detail of character analysis needed to differentiate species in this group. Their work made clear that only examination of many specimens would allow an assessment of interspecific variation and species boundaries, and this had been explained to the authors of the Roberts et al. paper ahead of their manuscript submission. The authors of the Kraus et al. paper had examined the specimen used to diagnose T. longhagen, as well as a series of similar specimens, and found it impossible to make a reliable species-level determination. Our detailed evaluation of the taxon longhagen reveals that it is insufficiently differentiated from the now-known species of the T. loriae Group, that it cannot confidently be assigned to any of these species, and that none of the existing specimens of snakes in this group can be assigned to T. longhagen. It follows that T. longhagen as currently defined is a taxonomic nomen dubium. It will retain this status until such time when additional data or additional material can lead to a resolution of its taxonomy.
Systematic sexism: gender-neutral rule changes are needed
Authors: HARRIS D. JAMES , MARSHALL JONATHON C. , GUTIÉRREZ LETICIA ALVAREZ , XAVIER RAQUEL
Published: July 2023

The development of an inventory of earth’s biodiversity—identifying and naming all living species—is a central tenet of biological science. For over 250 years, the Linnean system has been the predominant naming approach, with new species designated by a unique Latinized binomina following rules laid out by the International Code of Zoological Nomenclature (Anonymous 1999; “the Code” below) for animal taxa, while the International Code of Nomenclature for algae, fungi and plants (Turland et al. 2018) is the set of rules dealing with formal botanical names.
Water temperature and the growth of Ameletus inopinatus (Ephemeroptera: Ameletidae) in the Cairngorms, Scotland
Authors: MACADAM CRAIG R. , KITCHEN LOUIS , YEOMANS W. E.
Published: July 2023

Ameletus inopinatus Eaton, 1887 is the only arctic-alpine mayfly species found in the British Isles. Previous research in Europe using climate models has shown that the geographical range of this species is likely to contract as water temperatures increase. As such, A.inopinatus is particularly vulnerable to the impacts of climate warming. The impact of water temperature on the development of A.inopinatus larvae was investigated in the Cairngorms National Park in Scotland. We closely linked larval development to water temperature with snow cover playing an important role in ensuring emergence occurs before watercourses cease to flow in early summer. The results of this study confirm the vulnerability of A. inopinatus to rising water temperatures and provide new information to help target mitigation measures to prevent further losses of this species.
Inter-annual and habitat variation of the mayfly assemblage in grassland and pine afforested headwater streams (Córdoba, Central Argentina)
Authors: MONTILLA VICTORIA , MÁRQUEZ JAVIER ANDRÉS , PRINCIPE ROMINA ELIZABETH
Published: July 2023

Mayflies are widely used as indicators of stream conditions since their presence and abundance are closely associated with changes in environmental characteristics. We aim to analyze the richness and abundance patterns of mayflies in headwater streams of the Ctalamochita river basin in central Argentina, where some sub-basins have been fully afforested with exotic pines. We sampled 3 grassland streams and 3 pine afforested streams in 2008, 2012, 2014, and 2015. We took Surber samples in riffles and in 2012 we also sampled 2 additional habitats: pools and macrophyte patches. We found ten mayfly genera. Americabaetis and Leptohyphes were the most frequent and abundant and Cloeodes and Tricorythodes were rare, with a relative frequency < 3%. Richness and abundance were higher in grassland streams (ANOVA, p < 0.05), but the abundance pattern of different mayfly genera varied. In 2012 mayfly abundance was higher in pools and macrophytes in the afforested streams (ANOVA, p < 0.05), but it was similar among habitats in grassland streams. Different species dominated different habitats and stream types, and some shared the same habitat. In riffles and pools, the dominant genera was similar for afforested and grassland streams, while in macrophyte the dominance varied according to the riparian vegetation. Distribution patterns are influenced by microhabitat characteristics, which may be conditioned by changes in riparian land uses.
Systematics and updated range alter the conservation status of the Louisiana Needlefly, Leuctra szczytkoi Stark & Stewart, 1981 (Plecoptera: Leuctridae)
Authors: GRUBBS SCOTT A. , DEWALT R. EDWARD , HART LILY V. , LAYER MADISON R.
Published: July 2023

The Louisiana Needlefly, Leuctra szczytkoi Stark & Stewart, 1981, was one of 404 species petitioned in 2010 by the Center for Biological Diversity for inclusion and protection under the United States Endangered Species Act. There were only four known locality records in northern and central Louisiana before the start of this project, all collected between 1973 and 1997. Prior published research, however, provided tangible evidence that L. paleo Poulton & Stewart, 1991 could be a junior synonym of L. szczytkoi. The type localities of these two species (L. paleo—southern Arkansas; L. szczytkoi—northern Louisiana) are only separated by approximately 120 km. The primary objective of this study was to use mitochondrial cytochrome C oxidase subunit 1 gene sequences to assess the taxonomic validity of L. paleo using tree- and genetic distance-based phylogenetic analyses. Results of all analyses provide consistent and strong evidence that L. paleo is a junior synonym of L. szczytkoi. Hence, L. szczytkoi has nomenclatural priority with an expanded known distribution now from southern Arkansas southward to central Louisiana and southwestward to east Texas with 20 unique locations. Additional notes on other members of the L. ferruginea (Walker, 1852) group are provided.