bluuebunny/crossref_metadata_2025 huggingface dataset:
On a class of constacyclic codes and MDS code construction over 𝔽pm[u,v] 〈u2−δu,v2−γv,uv−vu〉
Authors: Mishra Vipul , Shukla Awadhesh Kumar , Pathak Sachin , Pandey Om Prakash , Upadhyay Ashish Kumar
Published: September 2024

Let [Formula: see text] denote a finite field, where [Formula: see text] is a prime and [Formula: see text] is a positive integer. In this paper, we study idempotent decomposition of the finite, commutative, non-local ring, [Formula: see text], where [Formula: see text]. This paper consists of the structure of [Formula: see text]-constacyclic (CC) codes over [Formula: see text], where [Formula: see text]. The structure of dual of CC codes is used to determine the Euclidean hull of such codes. Then, the Hamming distance and symbol-pair distance for the [Formula: see text]-CC codes of length [Formula: see text] over [Formula: see text] is determined. Additionally, conditions for repeated root [Formula: see text]-CC code to be maximal distance separable (MDS) in terms of Hamming distance and symbol-pair distance are provided. Finally, we present examples of several linear and symbol-pair codes some of which are MDS with respect to Hamming and symbol-pair distance.
MDS and I-perfect codes in pomset block spaces
Authors: Shriwastva Atul Kumar , Selvaraj R. S.
Published: September 2024

In this paper, we establish the Singleton bound for pomset block codes ([Formula: see text]-codes) of length [Formula: see text] over the ring [Formula: see text]. An upper and a lower bound on the minimum distance of [Formula: see text]-Maximum distance separable (MDS) codes are derived. Moreover, we prove that an MDS [Formula: see text]-code is necessarily an MDS [Formula: see text]-code. We also investigate the relationship between the [Formula: see text]-perfect codes and [Formula: see text]-perfect codes. Given an ideal with partial count and full count, we investigate how MDS and [Formula: see text]-perfect codes relate to one another. Duality theorem is derived for an MDS [Formula: see text]-code when all the blocks are of same length, and the distribution of codewords among [Formula: see text]-balls is analyzed as well. Finally, for a chain pomset, we study the maximum distance separability, packing radius and minimum distance of pomset block codes.
Enhancing microfinance efficacy for socio-economic development: A fuzzy logic approach to Pradhan Mantri Mudra Yojana
Authors: Roy Neha Chhabra , Ramachandran Narayani
Published: September 2024

This study comprehensively explores the intricate dynamics between Microfinance (MF) scheme implementation and socio-economic development through rigorous empirical analysis. The focal point is to provide a well-structured, stakeholder-specific mitigation plan, empowering microfinance institutions and customers for judicious investment planning, catalyzing socio-economic development and ensuring scheme implementation efficacy. Socioeconomic development is examined specifically through the Pradhan Mantri Mudra Yojana, a prominent microfinance scheme in India that encompasses financial inclusion, employment generation, women empowerment and sustainable development. Indicators within each domain are meticulously categorized into push and pull classes, influencing customer engagement with MF schemes. Noteworthy indicators exert forces that repel or attract customers, creating a nuanced understanding. The Microfinance Scheme Effectiveness Index, computed through fuzzy logic theory, facilitates empirical assessment across states, stratifying them into levels of effective scheme implementation. Addressing ineffectiveness requires bespoke, state-specific development plans, necessitating a multi-dimensional approach involving diverse stakeholders. The study advocates for policy interventions linked to pivotal aspects such as women’s education, equal pay rights, start-up support, women representation promotion, customer training, awareness campaigns and enhanced governmental policies for structured customer involvement. In conclusion, despite robust planning systems, the effectiveness of scheme implementation faces challenges in a dynamic environment, requiring an iterative and adaptive monitoring approach.
Exploring the Genetic and Molecular Connection between Autism and Huntington’s Disease via Transcriptomics and Biological Interaction Networks Analysis
Authors: Naveed Muhammad , Cheema Sana Rehman , Aziz Tariq , Makhdoom Syeda Izma , Saleem Urooj , Jamil Hamza , Alhomrani Majid , Alsanie Walaa F. , Alamri Abdulhakeem S.
Published: September 2024

Autism Spectrum Disorder (ASD) and Huntington’s Disease (HD) are distinct neurodevelopmental and neurodegenerative disorders, respectively, characterized by significant genetic and molecular alterations. ASD primarily affects early childhood and is associated with genetic mutations impacting brain development, while HD, an autosomal dominant disorder, leads to progressive neurodegeneration due to mutations in the HTT gene. Despite their differences, both disorders share common genetic pathways and molecular mechanisms. This study aims to explore the genetic and molecular connections between ASD and HD through a comprehensive analysis of differentially expressed genes (DEGs) and protein–protein interaction (PPI) networks to uncover shared pathways and potential overlapping mechanisms. Transcriptomic data were acquired from the NCBI-GEO database, specifically GSE180185 for ASD and GSE1751 for HD. DEGs were identified using thresholds of log2 fold change (FC)>1 and an adjusted [Formula: see text]-value <0.05. Common DEGs between the two disorders were determined and analyzed using Cytoscape’s STRING app to construct a PPI network with a confidence level of 0.7. Functional enrichment was conducted through KEGG and Gene Ontology (GO) analyses. Key regulatory modules and hubs were identified using CytoNCA and MCODE plugins. The ASD dataset revealed 565 DEGs, with 206 upregulated and 347 downregulated, while the HD dataset had 1091 DEGs, with 743 upregulated and 202 downregulated. Twelve genes were common to both conditions, including 4 upregulated and 8 downregulated. The PPI network comprised 62 nodes and 215 edges, with significant pathways including ascorbate metabolism and steroid hormone biosynthesis. Notably, Module 3, containing 12 nodes, was linked to EGFR tyrosine kinase resistance and apoptosis. This study identifies shared genetic and molecular pathways between ASD and HD, highlighting common regulatory mechanisms and potential targets for further research. The use of transcriptomic data and PPI network analysis reveals significant overlaps in the molecular mechanisms underlying these disorders. Further experimental validation and expanded dataset analyses could elucidate specific interactions and enhance our understanding of the shared pathways. Investigating these common mechanisms may also provide insights into potential therapeutic approaches for both ASD and HD.
Identifying the risk of high-permeability zones in early field life: gas souring management in a Cretaceous carbonate barrier island reservoir, Miskar Field, offshore Tunisia
Authors: Barnett Andrew J. , Wright V. Paul , Khaldi Haifa
Published: September 2024

Robust upfront reservoir characterization is vitally important when problems arise later in the management of a field. In this case, thin high-permeability zones were mapped, even though no water injection was planned. This proved critical when, 10 years later, gas souring problems could be rapidly addressed. The Late Cretaceous R1 Inférieur reservoir comprises an upward-shallowing succession (
c.
60 m thick) of offshore to shoreface and foreshore carbonates, which passes conformably up-section into an anhydrite-bearing lagoonal–peritidal succession (
c.
13 m thick), the R1 Supérieur. H
2
S well monitoring confirmed the migration of H
2
S from the terrace sour gas area to the core sweet gas area of the field. High H
2
S concentrations are a safety hazard, and there are limitations on the concentration of H
2
S that the Miskar pipeline can handle. Understanding the distribution of high-permeability layers in the R1 reservoir is critical to identify preferential pathways for gas migration and resulting gas souring. Gas souring is controlled by a high-permeability layer formed by bioclastic rudstones deposited at the shoreface–foreshore interface. Identifying this thin interval in uncored wells and predicting its lateral continuity are essential to minimize the impact of gas souring on field development.
Breaking the Metric Voting Distortion Barrier
Authors: Charikar Moses , Ramakrishnan Prasanna , Wang Kangning , Wu Hongxun
Published: September 2024

We consider the following well-studied problem of metric distortion in social choice. Suppose that we have an election with
n
voters and
m
candidates located in a shared metric space. We would like to design a voting rule that chooses a candidate whose average distance to the voters is small. However, instead of having direct access to the distances in the metric space, the voting rule obtains, from each voter, a ranked list of the candidates in order of distance. Can we design a rule that, regardless of the election instance and underlying metric space, chooses a candidate whose cost differs from the true optimum by only a small factor (known as the
distortion
)?

A long line of work culminated in finding optimal deterministic voting rules with metric distortion 3. However, for randomized voting rules, there is still a significant gap in our understanding: even though the best lower bound is substantially lower at 2.112, the best upper bound is still 3, which is attained even by simple rules such as Random Dictatorship. Finding a randomized rule that guarantees distortion 3 - ɛ for some constant ɛ has been a major challenge in computational social choice, as prevalent approaches to designing voting rules are known to be insufficient. In particular, such a voting rule must use information beyond aggregate comparisons between pairs of candidates, and cannot only assign positive probability to candidates that are voters’ top choices.

In this work, we give a rule that guarantees distortion less than 2.753. To do so, we study a handful of voting rules that are new to the problem. One is
Maximal Lotteries
, a rule based on the Nash equilibrium of a natural zero-sum game that dates back to the 1960s. The others are novel rules that can be thought of as hybrids of Random Dictatorship and the Copeland rule. None of these rules can beat distortion 3 alone; however, a careful randomization between Maximal Lotteries and any of the novel rules can.
TrinitySLAM: On-board Real-time Event-image Fusion SLAM System for Drones
Authors: Cai Xinjun , Xu Jingao , Deng Kuntian , Lan Hongbo , Wu Yue , Zhuge Xiangwen , Yang Zheng
Published: September 2024

Drones have witnessed extensive popularity among diverse smart applications, and visual Simultaneous Localization and Mapping (SLAM) technology is commonly used to estimate the six-degrees-of-freedom pose for drone flight control systems. However, traditional image-based SLAM cannot ensure the flight safety of drones, especially in challenging environments such as high-speed flight and high dynamic range scenarios. The event camera, a new vision sensor, holds the potential to enable drones to overcome these challenging scenarios if fused with the image-based SLAM. Unfortunately, the computational demands of event-image fusion SLAM have grown manifold compared with image-based SLAM. Existing research on visual SLAM acceleration cannot achieve real-time operation of event-image fusion SLAM on on-board computing platforms for drones. To fill this gap, we present
TrinitySLAM
, a high-accuracy, real-time, low-energy consumption event-image fusion SLAM acceleration framework utilizing Xilinx Zynq, an on-board heterogeneous computing platform. The key innovations of
TrinitySLAM
  include a fine-grained computation allocation strategy, several novel hardware–software co-acceleration designs, and an efficient data exchange mechanism. We fully implement
TrinitySLAM
  on the latest Zynq UltraScale+ platform and evaluate its performance on one custom-made drone dataset and four official datasets covering various scenarios. Comprehensive experiments show that
TrinitySLAM
  improves the pose estimation accuracy by 28% with half end-to-end latency and 1.2× energy consumption reduction compared with the most comparable state-of-the-art heterogeneous computing platform acceleration baseline.
Spatio-Temporal Predictive Modeling Techniques for Different Domains: a Survey
Authors: Kumar Rahul , Bhanu Manish , Mendes-Moreira João , Chandra Joydeep
Published: September 2024

Spatio-temporal prediction tasks play a crucial role in facilitating informed decision-making through anticipatory insights. By accurately predicting future outcomes, the ability to strategize, preemptively address risks, and minimize their potential impact is enhanced. The precision in forecasting spatial and temporal patterns holds significant potential for optimizing resource allocation, land utilization, and infrastructure development. While existing review and survey papers predominantly focus on specific forecasting domains such as intelligent transportation, urban planning, pandemics, disease prediction, climate and weather forecasting, environmental data prediction, and agricultural yield projection, limited attention has been devoted to comprehensive surveys encompassing multiple objects concurrently. This article addresses this gap by comprehensively analyzing techniques employed in traffic, pandemics, disease forecasting, climate and weather prediction, agricultural yield estimation, and environmental data prediction. Furthermore, it elucidates challenges inherent in spatio-temporal forecasting and outlines potential avenues for future research exploration.
Ethanol Oxidation Reaction on Electrodeposited Pd and Sb‒Pd Catalysts in Alkaline Solution Containing Na or Li Cations
Authors: Košević Milica G. , Nikolić Nebojša D. , Rakočević Lazar Z. , Lović Jelena D.
Published: September 2024

This work reports the galvanostatic electrodeposition of Pd and Sb‒Pd catalysts on rotating glassy carbon (GC) electrode using surfactant-free electrolytes. The prepared catalysts were tested in the electro-oxidation reactions in alkaline solutions. Characterization of Pd and Sb‒Pd catalysts was performed with scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray photoelectron spectroscopy (XPS) technique. Cyclic voltammetry (CV) and chronoamperometry were applied to study the electrocatalytic behavior of Pd and Sb‒Pd catalysts in the ethanol oxidation reaction (EOR) in an alkaline solution containing Na+ or Li+ cations from the point of the impact of the selected alkali metal cations on the electrocatalytic activity. The peak current of EOR at Pd and Sb‒Pd catalysts in the solution with Li+ cations is 2.5 times higher compared to the values obtained in the solution with Na+ cations. EOR starts at rather negative potentials in LiOH solution regarding NaOH for approximately 0.03 V indicating the active role of OHad and the impact of the nature of alkali metal cations which consequently arises from the formation of OHad ‒ cation clusters. The role of Sb in bimetallic catalyst was established by adjusting the extent and persistence of OHad surface coverage.
Effects of Cycloergometer on Cardiopulmonary Function in Elderly Patients after Coronary Artery Bypass Grafting: Clinical Trial
Authors: Cordeiro André Luiz Lisboa , Barbosa Hayssa De Cássia Mascarenhas , Vaz Kaliane Pereira , Souza Layla Souza E. , Souza Laura Brandão De , Matos Thayná De Oliveira , Guimarães André Raimundo França
Published: September 2024

Introduction. Despite all the improvements in surgical and anesthetic techniques, this procedure is still associated with pulmonary and cardiovascular complications in the postoperative period, and early rehabilitation, done through the use of cycloergometer, can minimize such complications, besides reducing the length of hospital stay. Objective. Therefore, the aim of the study was to assess the impact of cardiovascular exercise on lung function, respiratory muscle strength, and functional capacity in elderly patients after heart bypass surgery. Methods. To this purpose, a randomized and controlled clinical trial was conducted. Research participants were randomized to the cycle ergometer group (CEG) or to the control group (CG). The CG was managed based on the institution’s protocol. The CEG also carried out all the activities of the control group, but there was the inclusion of cycle ergometry through a device built by the researchers. Pulmonary function (vital capacity (VC) and peak expiratory flow (PEF)), ventilatory muscle strength (maximum inspiratory pressure (MIP) and maximal expiratory pressure (MEP)), and functional capacity (six‐minute walk test) were evaluated before surgery, at ICU, and hospital discharge. Results. During the research period, 122 patients were evaluated, 61 in each group. The MIP of the cycle ergometry group was higher at discharge from the ICU 95% CI 8 (5.46 to 10.54) and at hospital discharge 95% CI 14 (16.89 to 11.11). MEP was higher in the cycle ergometry group at discharge from the ICU with 95% CI 6 (8.18 to 3.82) and at hospital discharge with 95% CI 9 (11.69 a 6.31). Vital capacity at ICU discharge with 95% CI 6 (7.98 to 4.02) and at hospital discharge with 95% CI 7 (8.98 to 5.02), as well as peak flow at ICU discharge with 95% CI 43 (75.27 to 10.73), showed relevance, being higher in the group that used the cycle ergometer. The CEG showed improvement in functional capacity at the time of hospital discharge with a 95% CI 56 (30.37 to 81.63). Conclusion. We conclude that application of cycloergometry after CABG decreases the loss of pulmonary function, muscle strength, and functional capacity. This trial is registered with RBR-39yrht6.
Characterization of Virulence Genotypes, Antimicrobial Resistance Patterns, and Biofilm Synthesis in Salmonella spp Isolated from Foodborne Outbreaks
Authors: Soltan Dallal Mohammad Mehdi , Nasser Ahmad , Karimaei Samira
Published: September 2024

Salmonella is the main bacterial pathogen that causes foodborne disease, particularly in developing countries. Nontyphoidal Salmonella (NTS) include Enteritidis and Typhimurium as the most prevalent strains which are one of the significant causes of acute gastroenteritis in children. Therefore, identifying the most predominant serovars, types of common contaminated food, and paying attention to their antibiotic resistance are the main factors in the prevention and control strategy of salmonellosis. This study was undertaken to evaluate the prevalence rate of serovars, the biofilm formation, antimicrobial resistance (AMR) status, and phenotypic virulence factors of Salmonella strains isolated from diarrhea samples in some cities of Iran. A total of 40 (10.41%) Salmonella isolates were recovered from 384 diarrhea samples processed and the most common serovar was Salmonella serovar Typhimurium (82.5). Also, all isolates belonging to serovar Typhimurium showed more virulence factors compared to other serovars. The isolates showed a high resistance rate to ampicillin (95%) and nalidixic acid (87.5%), while a low resistance rate was found for chloramphenicol (2.5%). Moreover, significant variances in the capacity of biofilm formation were found between different Salmonella serotypes. The resistance of NTS to extant choice drugs is a potential public health problem. Constant monitoring of AMR pattern and virulence profile of NTS serovars is suggested for the prevention of salmonellosis in humans.
Identification and Validation of an Invasion-Related Disease-Free Survival Prognostic Model for Tongue Squamous Cell Carcinoma
Authors: Fang Wei , Chen Shan , Wan Di , Peng Yanhui , Yang Xiaoqin
Published: September 2024

Introduction: Tongue squamous cell carcinoma (TSCC) is a common malignant tumour type with aggressive invasion and a poor prognosis. To date, invasion-related gene expression signatures for the prognostic stratification of TSCC patients are unavailable in clinical practice. This study aimed to assess the impact of invasion-related genes on the prognosis of TSCC patients. Methods: We obtained mRNA profiles and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases (TCGA-TSCC and GSE41116, respectively). The TSCC samples from the TCGA-TSCC cohort were randomly divided into TCGA training and TCGA test datasets at a 7:3 ratio. Next, a disease-free survival (DFS) prognostic risk model was established on the basis of univariate and stepwise multivariate Cox regression analyses of the TCGA training cohort. Moreover, prognostic genes were screened. The model was subsequently evaluated and validated using the TCGA test and GSE41116 datasets. In addition, the prognostic genes were validated in the human TSCC cell line UM1 and the human oral keratinocyte (HOK) cell line using quantitative real-time polymerase chain reaction (qRT-PCR) analysis. Results: A total of 70 candidate genes related to invasion were identified in the TCGA-TSCC cohort. DFS data were subsequently constructed, and 6 prognostic genes, HMGN2, MYL12B, ACTB, PPP1CA, PSMB9, and IFITM3, were identified. The TSCC samples were divided into high- and low-risk groups in the TCGA training, TCGA test, and GSE41116 cohorts, respectively. In particular, patients with TSCC in the low-risk group had longer DFS than those in the high-risk group. Furthermore, qRT-PCR analysis confirmed that the expression levels of the 6 prognostic genes were significantly greater in the TSCC cell line UM1 than in the HOK cell line. Conclusion: This study identified new invasion-related target genes related to poor prognosis in TSCC patients, providing new insights into the underlying mechanisms of TSCC invasion.
Successful Treatment of Unresectable BRCA1 L63*-Mutated Basal Cell Carcinoma Invading the Parietal Bone with Cisplatin and Fluorouracil: A Case Report
Authors: Yoshida-Akai Saaya , Fujimura Taku , Amagai Ryo , Kambayashi Yumi , Hashimoto Akira , Terui Hitoshi , Oka Kenta , Watanabe-Takahashi Manami , Yamazaki Emi , Ohuchi Kota , Asano Yoshihide
Published: September 2024

Introduction: Basal cell carcinoma (BCC) is a common skin cancer that rarely metastasizes but can deeply infiltrate local tissues. The small number of unresectable BCC cases makes it difficult to conduct clinical trials, resulting in delays in the development of effective drugs for BCC. Cancer gene panel testing has led to an increasing number of new treatment proposals for patients with solid tumors for whom no standard treatment is available. Case Presentation: We described a case of unresectable BRCA1 L63*-mutated BCC invading the parietal bone, which was successfully treated with cisplatin and fluorouracil. Conclusion: Our present case suggests that comprehensive mutation analysis by gene panel testing is important in advanced BCC because genes other than those involved in the hedgehog signaling pathway can be driver genes.
The Association between Aminoglycoside Exposure and Ototoxicity in Children with Cystic Fibrosis
Authors: Yilmaz Yegit Cansu , Ergenekon Pinar , Yanaz Mürüvvet , Ozturk Akar Nezafet , Toktas Yavuz Fatma , Molla Kafi Hale , Çollak Abdülhamit , Bal Nilüfer , Gedik Toker Özge , Meral Özge , Ataş Ahmet , Çetin Kara Halide , Ayhan Yetkin , Guliyeva Aynur , Yuksel Kalyoncu Mine , Selçuk Balcı Merve , Karabulut Şeyda , Taştan Gamze , Uzunoglu Burcu , Karasu Nesibe , Oruc Yesim , Acar Melda , Yumuşakhuylu Ali Cemal , Dogan Remzi , Gozen Tan Emine Deniz , Ata Pinar , Kılınç Sakallı Ayşe Ayzıt , Girit Saniye , Cakir Erkan , Gokdemir Yasemin , Erdem Eralp Ela , Ciprut Ayca , Karakoc Fazilet , Karadag Bulent
Published: September 2024

Introduction: Pulmonary exacerbations increase the requirement of aminoglycoside (AG) antibiotics in people with cystic fibrosis (pwCF). Several studies have shown that AGs have a cumulative effect on ototoxicity. We aimed to investigate the relationship between AG exposure and ototoxicity by using 3 different methods in patients with CF. Materials/Methods: The multicenter study included 121 pwCF aged between 5 and 18 years with a history of parenteral AG exposure. Standard pure-tone audiometry, extended high-frequency pure-tone audiometry (EHF-PTA), and distortion-product otoacoustic emissions (DPOAE) tests were performed. Mitochondrial mutation analysis for m1555G>A was performed in 61 patients. Results: Median age was 12.85 years and 52.1% (n = 63) were male. 18.2% (n = 22) of the patients had received parenteral AGs more than 5 courses/lifetime. Ototoxicity was detected in at least one of the tests in 56.2% (n = 68) of the patients. Only 10.7% (n = 13) of the patients had reported a symptom indicating ototoxicity. 30.3% (n = 30) of the patients had ototoxicity in the low exposure group, while it was 45.5% (n = 10) in the high exposure group according to EHF-PTA (p > 0.05). Median number of parenteral amikacin courses was significantly higher in the ototoxic group (2 [1.25–5.75] vs. 2 [1–3]; p = 0.045). No m1555A>G mutation was detected in 61 patients who screened for mitochondrial mutation analysis. Conclusion: As AG ototoxicity occurs primarily at high frequencies, EHF-PTA is important in early detecting ototoxicity. EHF-PTA and DPOAE detected ototoxicity in some patients with normal PTA results. All pwCF with a history of AG exposure should be evaluated for hearing loss since symptoms may only be noticed in the late period.
Random sample consensus-based room mapping using light detection and ranging
Authors: Latukolan Merlyn Inova Christie , Pramudita Aloysius Adya , Armi Nasrullah , Hamdani Nizar Alam , Susilawati Helfy , Satyawan Arief Suryadi
Published: September 2024

Light detection and ranging (LiDAR) is a high-accuracy data source for geospatial providers that is displayed in two dimensions (2D) or three dimensions (3D). It is used to measure the distances or 2D or 3D maps of the environment. This study examines a random sample consensus (RANSAC)-based room mapping approach utilizing LiDAR. The RANSAC is used to achieve line fitting as a solution to acquire missing or incomplete point cloud data during the process of room scanning. The maximum x-y distance is proposed to achieve a proper model to fix the missing line during the LiDAR scanning process. Data retrieval uses ground-based LiDAR located in the middle of a certain room with the dimension of 5.76×4.95 m2. To explore a room mapping, a 2D LiDAR YDLIDAR G4 with an operating frequency of 7 Hz is used. The derived raw data is then visualized with MATLAB. The results show that the RANSAC can perform line-fitting for missing or illegible LiDAR point cloud data during the scanning process due to reflection or obstacles. The increase in the amount of data used is then directly proportional to the probability of the number of correct models.
A frequency adaptive multiple complex coefficient filter for grid connected applications
Authors: Boumediene Bachir , Araria Rabah , Chedjara Zakaria , Mekhloufi Belkacem , Bey Mohamed , Wira Patrice
Published: September 2024

In the realm of synchronization techniques, the dichotomy between open loops (OLSs) and closed loops (CLSs) presents a perennial challenge: how to enhance dynamic performance without sacrificing stability and disturbance rejection. While OLS techniques offer rapid dynamic response and unwavering stability, they often falter in non-nominal frequency scenarios. Conversely, CLS techniques grapple with the delicate balance of bolstering dynamic performance while maintaining robust stability. To surmount these obstacles, this study proposes an innovative approach: the integration of a frequency locked loop (FLL) as a secondary frequency detector within synchronization structures, coupled with the multiple-complex coefficient-filter (MCCF). This amalgamation bestows notable advantages. Firstly, from a control perspective, the resultant synchronization technique resembles a quasi-OLS, obviating the need for intricate stability analyses. Moreover, it exhibits commendable disturbances rejection alongside swift dynamic response. Through comprehensive simulation, our proposed technique showcases superiority over existing counterparts, evidencing enhanced settling time, disturbances rejection, and efficiency in the face of frequency drifts.
A review on interferometry lightning mapping system and its deployment in Palembang Indonesia
Authors: Oktaviani Wiwin A. , Sidik Muhammad Abu Bakar , Ahmad Mohd. Riduan , Jambak Muhammad Irfan
Published: September 2024

Climate change effects influence the sustainability of wind and photovoltaic energies as renewable sources. Similarly, infrastructure for renewable energy is structurally vulnerable to lightning strikes. Hence, a system for detecting and monitoring lightning activity is necessary to predict and adapt to climate change trends and to enhance the lightning protection system's capability. One such system for observing and locating lightning is very high frequency (VHF) interferometry. Various factors, such as the baseline distance between sensors, the frequencies used, and the quality of the analyzed signal, will influence the system's accuracy. This paper discusses these factors through an extensive literature review. This study aims to identify the factor that most significantly affects the system's accuracy and to determine the technical adjustments required to improve this accuracy. Enhanced precision in the interferometry system will provide a more detailed view of lightning activity, thereby aiding in the climate change prediction that could impact electricity generation from renewable sources. Accurate lightning location detection can also serve as a basis for designing effective lightning protection systems for renewable energy infrastructure.
Wideband coupled-line BPF with high-selectivity based on parallel transmission line signal interference technique for cellular base stations applications
Authors: Firmli Maroua , Zatni Abdelkarim
Published: September 2024

This paper presents a novel approach involving a modified wideband parallel coupled line bandpass filter (BPF). The proposed modification aims to achieve both enhanced skirt selectivity and simplified configuration, while ensuring the prevention from discontinuities between adjacent segments. The improvements in the performance of the filter’s structure are achieved through the integration of a signal-interference filtering model using parallel transmission line with distinct impedance values and electrical lengths at the input/output of the filter. This integration gives rise to the generation of multiple transmission zeros (TZs), thereby bolstering attenuation within both in-band and out-of-band frequency ranges. For the purpose of concept validation, a 3𝑟𝑑 wideband band-pass filter with 𝑓0=2.45 Ghz, accompanied by a fractional bandwidth of 50% was designed and simulated using microstrip RO6010 substrate. The outcomes of the simulation exhibit good performance, characterized by minimal insertion loss, wide bandwidth and the presence of seven TZs within the passband, resulting in high selectivity and sharp stopband rejection level.
A stacked ensemble approach to identify internet of things network attacks through traffic analysis
Authors: Rawashdeh Adnan , Alkasassbeh Mouhammd , Alauthman Mohammad , Almseidin Mohammad
Published: September 2024

The internet of things (IoT) has increased exponentially in connected devices worldwide in recent years. However, this rapid growth also introduces significant security challenges since many IoT devices have vulnerabilities that can be exploited for cyber-attacks. Anomaly detection using machine learning algorithms shows promise for identifying abnormal network traffic indicative of IoT attacks. This paper proposes an ensemble learning framework for anomaly detection in IoT networks. A systematic literature review analyzes recent research applying machine learning for IoT security. Subsequently, a novel stacked ensemble model is presented, combining multiple base classifiers (random forest, neural network, support vector machine (SVM)) and meta-classifiers (gradient boosting) for improved performance. The model is evaluated on the IoTID20 dataset, using network traffic features to detect anomalies across binary, multi-class, and multi-label classifications. Experimental results demonstrate that the ensemble model achieved 99.7% accuracy and F1 score for binary classification, 99.5% accuracy for multi-class, and 91.2% accuracy for multi-label classification, outperforming previous methods. The model provides an effective anomaly detection approach to identify malicious activities and mitigate IoT security threats.
Modified multicarrier sinusoidal pulse-width modulation for three-phase open-load five-level inverter
Authors: Suroso Suroso , Prasetijo Hari , Susilawati Hesti , Murdyantoro Am Eko , Mubyarto Agung
Published: September 2024

Five-level voltage source inverter (VSI) is a power inverter topology generating a five-level output voltage waveform. This inverter topology can reduce harmonics distortion to be lower compared to a conventional two-level inverter. In practical, delay of gating signals is unavoidable during switching operation of power semiconductor switches. Adding dead time in the gating signals of VSI’s power switches is mandatory to avoid short circuit during switching operation. However, the dead time of the inverter’s switching signals causes low frequency harmonics and distortion of inverter’s output waveforms. In this paper, a different multicarrier sinusoidal pulse-width modulation (SPWM) method with harmonics suppression capability was proposed and applied in the three-phase open-connection load five-level inverter. The proposed modified SPWM was tested using computer simulation of Powersim (PSIM) software. The measured output waveforms of the five-level VSI at different power factor conditions are presented and analyzed. The total harmonics distortion (THD) values of inverter’s output current were suppressed using the proposed SPWM method to be less than 1%. The test results showed that the proposed modified SPWM method was able to reduce the distortion (THD) of alternating current (AC) waveform, and increase the quality of the inverter’s output power.
A systematic review of radar technologies for surveillance of foreign object debris detection on airport runway
Authors: Nugraha Eka Setia , Apriono Catur , Zulkifli Fitri Yuli
Published: September 2024

Flights are projected to reach eight billion globally by 2037, demanding airport operators manage operations effectively, including safety on the runway due to the high number of aircraft movements. One crucial issue is any foreign object, commonly known as foreign object debris (FOD), that must be detected and cleaned immediately to ensure aircraft safety when taking off, landing, and taxing. The International Civil Aircraft Organization (ICAO) reported that FOD causes 10.08% of aviation accidents. Most airports manually monitor and detect FOD, which could be more effective and dangerous. Therefore, it is important to provide FOD detection systems with proper technologies. Radar technologies are potential FOD detection techniques that offer robustness to weather fluctuation. However, some factors must be considered properly to provide an effective FOD system. This paper reviews radar technologies for FOD detection on airport runways by considering factors, including types of debris, detection coverage, mode of radars, frequencies, and attenuation. It was found that all critical factors considered contribute to the quality of detection. This paper will provide guidelines for developing FOD detection based on radar technologies regarding airport necessities and its specific environment.
Sustainability dimensions in enhancing the energy and resource efficiency of big data systems
Authors: D/O Arunachalam Aishwharya Raani , Jusoh Yusmadi Yah , Abdullah Rusli , Umarova Zhanat , Akhmetova Sabira , Iztayev Zhalgasbek , Zhumatayev Nurlybek
Published: September 2024

Big data systems are essential for many businesses to grow, leveraging the vast amounts of data they generate and access. However, big data systems are plagued by significant sustainability challenges. Thus, this study aims to identify metrics that can measure the sustainability of big data systems. This research conducted a comprehensive literature review to identify five key sustainability dimensions: technical, environmental, economic, social, and individual. Then, a set of 29 metrics corresponding to these dimensions was developed. To ensure the relevance and applicability of these metrics, an expert validation session was carried out with five experts in the big data field. The validation process confirmed the appropriateness of our proposed metrics and modification take place. The findings of this study present 30 metrics upon experts’ validation that could enhance the sustainability of big data systems, offering meaningful insights for researchers and practitioners aiming to enhance resource and energy efficiency in this domain.
A study on observing, detecting, and determining objects in low earth orbit using optical telescope system
Authors: Le Xuan Huy , Nguyen Tien Su , Trinh Hoang Quan , Le The Soat , Trinh Van Khang , Tran Anh Tu , La Thuy Linh
Published: September 2024

Problems of space debris, space security threats and space accidents are an escalating topic that is drawing attention from scientists and researchers worldwide. Based on the practical demand for detecting and surveilling objects in Earth's orbit in the Vietnam's sky area, the research group has designed a space monitoring system to detect and identify orbiting objects using optical telescopes. The idea of this system is to utilize wide and narrow field-of-view (FOV) optical telescope systems to observe and identify the trajectory of orbiting objects. After an image of an unknown object is captured with a wide FOV telescope, an analyzing algorithm will process and predict the trajectory of it, with support of artificial intelligence, and determine whether there is the appearance of an uncataloged object. If it is affirmative, the narrow telescope system will adapt to a new attitude to track the object from predicted trajectory and gather information for future use. Constructing and validating of this monitoring system deployed by the research group are described in this paper.
Improving Arabic handwritten text recognition through transfer learning with convolutional neural network-based models
Authors: Lamtougui Hicham , El Moubtahij Hicham , Fouadi Hassan , Satori Khalid
Published: September 2024

Arabic handwritten text recognition is a complex and challenging research domain. This study proposes an offline Arabic handwritten word recognition system based on transfer learning. The system exploits four pre-trained convolutional neural network (CNN) architectures, namely VGG16, ResNet50, AlexNet, and InceptionV3. In addition, a specialized image recognition model derived from the ImageNet dataset is incorporated. A combination strategy is designed to combine transfer learning with specific fine-tuning techniques, aiming to improve recognition accuracy. The study is conducted on the IFN/ENIT dataset, which includes images of Tunisian City and village names. The results show that the proposed system achieves a recognition accuracy of 94.73%, which is significantly higher than the accuracy rates achieved by previous approaches. These results suggest that the proposed system is a promising approach for Arabic handwritten text recognition.
Understanding explainable artificial intelligence techniques: a comparative analysis for practical application
Authors: Bhatnagar Shweta , Agrawal Rashmi
Published: September 2024

Explainable artificial intelligence (XAI) uses artificial intelligence (AI) tools and techniques to build interpretability in black-box algorithms. XAI methods are classified based on their purpose (pre-model, in-model, and post-model), scope (local or global), and usability (model-agnostic and model-specific). XAI methods and techniques were summarized in this paper with real-life examples of XAI applications. Local interpretable model-agnostic explanations (LIME) and shapley additive explanations (SHAP) methods were applied to the moral dataset to compare the performance outcomes of these two methods. Through this study, it was found that XAI algorithms can be custom-built for enhanced model-specific explanations. There are several limitations to using only one method of XAI and a combination of techniques gives complete insight for all stakeholders.
Neuroscience for early childhood education: impact on virtual settings and teaching practice
Authors: Ledesma-Pérez Fernando , Cruz-Montero Juana , Holguin-Alvarez Jhon
Published: September 2024

The research allowed us to measure the impact of neuroscience from the transfer carried out by practicing education teachers, who received university training based on neuroscience. We performed comparative inferential analyzes on 1,341 students from public and private schools in Lima who acted as an informant sample. The study sample was made up of 71 university students who worked as teachers with university training with neuroscientific content. Traceability was carried out between the macro and microprogramming of the university students and its effect on the school was calculated. Instruments were used to assess university content and measure school learning. It was found that 25% of the credits were transversal neuroscience subjects. In microplanning, more than 50% of the activities incorporated contributions from neuroscience, demonstrating significant effects on children’s learning. The limitations demonstrated the low scope focused on the number of teachers evaluated, the permeability of the neuroscientific concepts that could be delivered to school students due to the time delay involved in executing this type of activities. It is concluded that the activities were moderately significant in the development of the neuroscience curriculum for university students.
Enhancing the scientific argumentation skills of prospective chemistry teacher using integrated chemical literacy strategy
Authors: Sulistina Oktavia , Rahayu Sri , Dasna I Wayan , Yahmin Yahmin
Published: September 2024

This research aims to enhance prospective chemistry teachers’ scientific argumentation skills through integrated chemical literacy strategy (ICLS) learning and to examine the patterns of relationship between students’ scientific argumentation skills in terms of content and socio-scientific issues (SSI). The study used mixed methods: the embedded design with embedded experimental model. The research sample was 88 students, the control and the experimental groups each consisted of 44 students. The research instrument used scientific argumentation skills test: an open and closed essay test, and interviews with 10 students as selected respondents. Data analysis used descriptive analysis, N-gain, Mann-Whitney test, effect size test, and qualitative analysis. The results showed that ICLS significantly had a great influence on enhancing students’ scientific argumentation skills. The interview results show that: the level of scientific argumentation skills related to SSI is not consistently related to content-related scientific argumentation skill; students who have scientific argumentation skills related to SSI levels 4, 3, and 2 can provide the correct claim, data, warrant, backing, and rebuttal to scientific arguments related to content if guided by guiding questions; student that had higher level of scientific argumentation skills need fewer guiding questions.
Examining the trends of research on educators’ readiness in online teaching & learning (2013-2022): a bibliometric analysis
Authors: Mohd Nasir Farah Damia , Ghazali Norliza , Wah Yap Bee
Published: September 2024

Despite recent emphasis, the usage of online and blended learning as instructional methodologies in higher education is still unequal, leading to variations in students’ learning experiences across structures, areas, and programs. Research on the aspects concerning educators’ adoption and adaptation of online teaching is crucial to overcome this limitation. By using the terms ‘Educators AND Online Learning AND Readiness’, 391 journal articles were listed for further analysis. Microsoft Excel was used for frequency analysis, VOSviewer to visualize data, Harzing’s Publish or Perish to compute and evaluate citation metrics, and Words Cloud to create a cluster of words that were shown in various sizes. The bibliometric criteria used in this study to summarize results includes language, topic area, research trends by year of publication, top contributors by nation, most significant institution, and name of the active source and others. This research includes a citation analysis, an authorship analysis, and keyword analysis. The results show that from 2013 to 2022, the rate of publication increased, and a spike was seen from 2019 to 2020 due to the COVID-19 epidemic. Identification of the important blended learning outcome predictors will help with the initial planning of this creative pedagogical strategy.
Facilitating students’ readiness for blended learning during the COVID-19 pandemic
Authors: Farani Rizki , Budiningsih C. Asri , Rohman Arif
Published: September 2024

Blended learning during COVID-19 pandemic creates diverse combination of face-to-face synchronous and asynchronous activities. However, there is still limited exploration on students’ readiness in terms of finishing their tasks. Most studies only focus on general description of students’ learning preparation. To complete the existing literature, we investigated the use of training, tutorials, and simulations to facilitate students’ readiness for blended learning during the COVID-19 pandemic. Three iterative phases of preparation, learning implementation, and investigating findings were employed in a frame of design-based research (DBR) method. The data consists of classroom’ observations, students’ reflective notes, and students’ achievements reports. All data were coded and analyzed statistically and qualitatively to determine the benefits of training, tutorials, and simulations in supporting students’ readiness to complete tasks. The results show that training, tutorials, and simulations facilitate extra asynchronous interaction and time to help students prepare their drafts for submission. Students can achieve all predefined learning goals at the end of the semester. The results imply that educators need to explore more initial activities prior blended learning to facilitate students’ readiness.
New and conventional media to senior high school student’s reading motivation
Authors: Alda Rivika , Lopez Jessa Rose , Alburan Kent Vincent
Published: September 2024

Motivation has long been established as an important factor that affects reading among students. With the advent of technology, reading motivation has become more nuanced as new reading media alongside conventional media surfaced. The study explored the relationship between senior high school students’ new and conventional media preferences and their reading motivation. A descriptive correlational research design was employed to analyze the data and determine correlations between variables. Results revealed that students generally have a stronger preference for books (physical books, school books, and pocketbooks) as reading media. Students also have a stronger preference for reading academic texts in print formats. In terms of the amount of time spent on reading electronic and print texts, students generally spend longer time reading electronic texts. The results also showed higher intrinsic motivation to read than extrinsic motivation among students. Finally, significant positive relationships were found between most intrinsic motivation scales and students’ new media preferences. Few significant positive relationships were found between extrinsic motivation scales and students’ new media preferences. Implications of these findings highlighted the need to utilize both conventional and new media and consider students’ preferences vis-à-vis classroom reading tasks.