bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical solution of generalized fractional Lane–Emden-Fowler equation using Haar wavelet method
Authors: Goswami Pranay , Kumar Ashish
Published: May 2024

This paper presents a numerical technique to solve the generalized fractional Lane–Emden–Fowler equation. We use the Haar wavelet technique to approximate the solution of the generalized fractional Lane–Emden–Fowler equation. In this method, a differential equation transforms into a system of nonlinear equations, and this system is further solved to obtain Haar coefficients. We also showed the convergence of this method by establishing an upper bound. The rate of convergence is also discussed in our algorithm. Many numerical examples have been taken, and the results of those numerical experiments have been written in tabular form. We also documented the experiments graphically to show the efficiency and accuracy of this method.
Effects of Brownian motion on solitary wave structures for 1D stochastic Poisson–Nernst–Planck system in electrobiochemical
Authors: Nan Tang , Baber Muhammad Zafarullah , Ahmed Nauman , Iqbal Muhammad Sajid , Demirbilek Ulviye , Rezazadeh Hadi
Published: May 2024

This study deals with the time fractional 1D stochastic Poisson–Nernst–Planck (TFSPNP) system under the effect of multiplicative time noise. The M-truncated derivative (MTD) takes into consideration the fractional order time derivative. This is a steady-state Poisson–Nernst–Planck (PNP) equations that have applications in bioelectric dressings and bandages. To obtain the soliton solutions of TFSPNP, we use the generalized exponential rational functional method. These findings are presented in the form of trigonometric, exponential, and hyperbolic functions. Moreover, to show the effect of multiplicative time noise and MTD, we construct the plot of some solutions in the form of three-dimensional, two-dimensional, and their corresponding contours. These plots clearly show the effect of randomness in the wave structures for the exact solitary wave solutions that are attained. In general, the solutions become more stable when a noise term disrupts their symmetry.
The effects of nonlinear perturbation terms on comparison principles for the p-Laplacian
Authors: Mohammed Ahmed , Vitolo Antonio
Published: May 2024

In this paper, we investigate various comparison principles for quasilinear elliptic equations of [Formula: see text]-Laplace type with lower-order terms that depend on the solution and its gradient. More specifically, we study comparison principles for equations of the following form: [Formula: see text] where [Formula: see text] is the [Formula: see text]-Laplace operator with [Formula: see text], and [Formula: see text] is a continuous function that satisfies a structure condition. Many of these results lead to comparison principles for the model equations [Formula: see text] where [Formula: see text] are non-decreasing and [Formula: see text]. Our results either improve or complement those that appear in the literature.
Chemi-Resistive Sensor for Ammonia Using Inkjet Printing of GO/PEDOT:PSS Composite at Room Temperature
Authors: Chhapia Pratik , Patel Harshad
Published: May 2024

This study describes an easy and cheap inkjet printing method for producing a paper-based gas sensor consisting of a composite film made of graphene oxide and poly(3,4-ethylenedioxythiophene) and poly(styrenesulfonate) (PEDOT:PSS). A glossy paper substrate is an inkjet printed with ink made by dispersing graphene oxide in a PEDOT:PSS conducting polymer solution to test its ability to detect ammonia ([Formula: see text] at ambient temperature. The presence of few-layer graphene oxide in the PEDOT:PSS copolymer and the existence of [Formula: see text]–[Formula: see text] interactions between graphene oxide and PEDOT:PSS are confirmed by Fourier transform infrared spectroscopy, UV–Visible spectrophotometer, and X-ray diffraction. In a small concentration range of 1–100 ppm at ambient temperature, the ink-jet printed graphene oxide-PEDOT:PSS gas sensor displays strong responsiveness and good selectivity to NH3. The study found that [Formula: see text] is a strong donor in the ammonia gas produced by a bubble system of ammonia water, with [Formula: see text] molecules being ideal candidates for molecular doping of graphene. The [Formula: see text] molecule can facilitate quick desorption by converting [Formula: see text] to [Formula: see text]. The interaction between graphene oxide and [Formula: see text] molecules is weak. The attained gas-sensing performance may be attributed to the increased specific surface area of graphene oxide and enhanced interactions between the sensing film and [Formula: see text] molecules via [Formula: see text] and lone pair electron network. The [Formula: see text]-sensing mechanisms of the flexible printed gas sensor are based on the competitive interaction of ammonia on the sensor, adsorption and dissociate ionization on the sensor surface.
Increase of Curie point of BaTiO3 ceramics by stoichiometry, point defects and doping processing
Authors: Qi Jianquan , Fang Hui , Wang Jiang , Han Xiumei , Liang Zizhou , Ma Jin , Shang Xunzhong , Gu Liuting , Chen Wanping
Published: May 2024

The Curie point of barium titanate (BaTiO3) has been a focal point of research since the discovery of its ferroelectric properties. Exploring methods to elevate the Curie point without relying on Pb as a dopant presents fresh opportunities for lead-free dielectric and/or piezoelectric materials. It is essential to avoid introducing ions like K[Formula: see text] and Na[Formula: see text], which could jeopardize the functional ceramic characteristics. This study delves into the stoichiometry of barium titanate, examining how impurities, point defects and doping techniques influence its Curie point, focus on the potential of doping and processing to enhance this property. BaTiO3 nanopowders were synthesized directly with varying Ba:Ti ratios in an ethanol–water solution at 60∘C, followed by sintering at 1280∘C and characterization through dielectric spectroscopy. A comparison was made with samples doped with Si, vapor-doped with Bi and vapor-doped with Pb. Results revealed that even minimal Si doping could boost the ferroelectric properties and elevate the Curie point, while vapor-doping with trace amounts of PbO or Bi2O3 significantly increased the Curie point, particularly in samples with higher Ti content. The impact of vapor dopants of PbO and Bi2O3 was similar, with a nominal doping level of 1[Formula: see text]mol% shifting the Curie point above 140∘C. Notably, in samples with a Ba:Ti ratio of 0.95 vapor-doped with PbO, the Curie point rose to 146∘C, a notable increase of 16∘C, surpassing the traditional doping efficiency. This study offers fresh insights into enhancing the Curie point of barium titanate-based materials, exploring the intricate connections among chemical stoichiometry, dopants, point defects and dielectric properties. It highlights the significant influence of chemical composition, impurities, defects and doping strategies on the dielectric characteristics of barium titanate.
Structural, Thermal, Optical, Electrical, and Dielectric Properties of Complex Lead-Free Compound: [Bi1∕2Na1∕2][Fe1∕2W1∕2]O3
Authors: Hota Sudhansu Sekhar , Panda Debasish , Pratap Hitishranjan , Choudhary Ram Naresh Prasad
Published: May 2024

Some physical properties (structural, dielectric and optical) of a complex lead-free ceramic [[Formula: see text][Formula: see text]][[Formula: see text][Formula: see text]]O3 have been thoroughly examined in different experimental conditions in this study. It was fabricated via a solid-state reaction method. The crystal structure is monoclinic, according to the detailed analysis of the X-ray diffraction pattern. Also, the functional vibrational bands can be observed in the FT-IR and Raman spectra, which support the creation of the molecular structure. Scanning electron microscope (SEM) images of the sample clearly show the effects of [Formula: see text] and [Formula: see text] incorporation in morphology, and energy dispersive X-ray spectroscopy (EDX) indicates the existence of all constituents. The non-overlapping small polaron tunneling (NSPT) and correlated barrier hopping (CBH) model conduction mechanisms are examined through Jonscher’s power law. The contribution of the grain and grain boundary to the capacitive behavior is shown by Nyquist plots. According to a leakage current analysis, the compound exhibits Ohmic and space charge limited conduction (SCLC) conduction mechanisms. Electric field polarization was used to study the ferroelectric nature. The findings of this study show that the inclusion of [Formula: see text] and [Formula: see text] is an efficient technique to improve its dielectric and optical characteristics.
Key Information Extraction and Recognition from Rich Text Images
Authors: Do Tien , Doan Thuyen Tran , Le Khiem , Nguyen Thua , Le Duy-Dinh , Ngo Thanh Duc
Published: May 2024

Key information extraction and recognition from rich text images are crucial for various applications. There are two main tasks involved in this process: Line Item Recognition (LIR) and Key Information Localization and Extraction (KILE). LIR aims at identifying and interpreting data line items in a document. The essential information in each line item is then classified or extracted, a task known as KILE. A widely used approach for this problem is sequence based, which relies on the generalization of a language model and requires a significant amount of training time. We present an effective and reliable solution to the problem by using RoBERTa, a transformer model trained on a large corpus, along with the LION optimizer to improve the training process. A comprehensive evaluation was conducted on two different benchmarks, emphasizing two different languages, English and Vietnamese. Experimental results on DocILE indicate that the proposed framework significantly improves the KILE task with a 7.24% increase in accuracy compared to the baseline and also enhances the correct recognition rate at the LIR stage. On MCOCR, the method achieved a Character Error Rate (CER) of 28.6%, which is competitive with the state-of-the-art on this dataset.
Like Father, Like Daughter – Ectodermal Dysplasia-Syndactyly Syndrome: A Case Report
Authors: JITH Gopika , SUBA Santanu , GIRI Sanjay Kumar
Published: May 2024

Ectodermal dysplasia-syndactyly syndrome 1 (EDSS1) is an exceedingly rare condition associated with mutations in the PVL4 gene. It is characterised by sparse, brittle hair, eyebrows and eyelashes, abnormal dentition and nails, along with bilateral cutaneous syndactyly involving the fingers and toes. We report a 2-year-old girl who presented to us with bilateral complete simple syndactyly of the third and fourth web spaces of the hands, along with bilateral syndactyly of both feet involving the second to fourth toes. Upon examination, sparse hair and eyebrows, along with abnormal dentition, were noted. Thorough clinical examination and genetic analysis were conducted on the affected child and her father, who exhibited similar clinical features. Genetic analysis revealed a homozygous nonsense mutation in the PVL4 gene in both individuals. According to the literature, EDSS1 has been reported in only 10 families worldwide, and there are no reported cases from India.

Level of Evidence: Level V (Therapeutic)
A novel approach on laplacian energy of σJ-dominating complex spherical fuzzy graph structures and with application
Authors: Bathusha S. N. Suber , Raj S. Angelin Kavitha , Mahamud Mufti , Jayakumar Sowndharya
Published: May 2024

The CSFS is an extension of CPFS and CPicFS. The design addresses vagueness more explicitly. It extends the real subset’s range to complex with the use of unit disc. Due to its coverage in three directions: complex membership functions, complex abstinence membership function, and complex non-membership functions, CSFS has more flexibility than CFSs, CIFSs, CPFSs, and CPicFS. It can be applied in various ways through fuzzy control. The primary objective of this study is to present CSFGS, which exhibits exceptional performance in tackling challenging problem, particularly ones that involve multiple relationships. GSs and CSFSs are combined in this concept. As a result, many problems are combined with different relations. The AM of CSFGS and degree of vertex presence have been found. The lower and upper constraints on the energy of CSFGS are derived by calculating the energy of CSFGS. Furthermore, we have provided some details regarding the LE of the [Formula: see text]-dominant CSFGS. We also propose the notion of isomorphic and identical [Formula: see text]-dominating CSFGS. Finally, we have discussed a real-world example based on temperature variation and climatic data analysis in an environment with a LE of the [Formula: see text]-dominant CSFGS, to demonstrate the applicability of the generated results. Also, an algorithm has been developed to clarify the fundamental workings of our application.
Local fractional Laplace transform iterative method for solving Korteweg–de Vries equation with the local fractional derivative
Authors: Ojo Gbenga O. , Olaifa John O.
Published: May 2024

The local fractional Korteweg–de Vries equations were considered in this paper. Series solutions for the linear and nonlinear case were examined using the local fractional Laplace transform iterative method. This proposed method is the coupling of the local fractional Laplace transform with the new iterative method. The existence and uniqueness of the solutions is considered using the principle of mathematical induction. Furthermore, illustrative examples were considered and the graphs are shown. The results obtained in this study reveal the benefit of this method and provide valuable insight into the behavior of complex phenomena in a precise and efficient manner with less computational work and implementation ease.
Unravealing the Relationship Between Traumatic Brain Injury and Parkinson’s Disease by Transcriptome Profiling
Authors: Dhanaraj Yazhini , Upadhyay Riddhi , Zainulabidin Ashiru Aliyu , Pitchaimuthu Xavier , Sevanan Murugan , Thirunavukkarasu Muthu Kumar
Published: May 2024

Traumatic brain injury (TBI) is caused by the disruption in the brain’s normal function due to some external forces like jolt or blow to the head. While, Parkinson’s disease (PD) is a neurodegenerative disorder which starts with tremor in one hand and gradually worsens over time. The connection between these two important diseases is not yet fully understood. Thus, we have proposed a transcriptome-based approach to identify the interrelation between TBI and PD. Determining the common over-or under gene expression pattern could reveal common pathobiological pathways that may explain the linkage between these two diseases. A total of 609 differentially expressed genes were discovered as commonly expressed genes for both TBI and PD. Further, the pathway studies reveal that nine genes such as NDUFA6, SLC17A7, EMXI, PLPPR1, FEZF2 and DUSP14, SERF1B, HBB and ABR made a significant impact on the disease progression of TBI and PD. In particular, SERF1B and HBB and ABR were considered as the top-ranked genes based on the pathway analysis and functional enrichment calculations. We believe that in-depth study on the identified biomarkers will provide possible treatments strategies to overcome TBI and PD.
Rights in China: Myths, Abuses, and Politics
Authors: Liu Sida , Li Sitao
Published: May 2024

This article presents a sociological perspective on understanding rights in China, examining the interplay between multiple myths of rights, rights abuses, and the politics of rights within various social and physical spaces. It highlights competing myths of rights held by the state, ordinary citizens, rights activists, and legal professionals. The article examines how rights abuses contribute to rights consciousness and mobilization across different human rights domains in a repressive political context. By analyzing the politics of rights in interconnected spaces, such as the street, the legal system, the global arena, and cyberspace, it emphasizes the importance of continuous engagement between domestic and overseas actors in shaping China's human rights future. The article encourages social science researchers to thoroughly examine the myths, abuses, and politics of rights before making normative judgments about China's human rights conditions.
Early-Life Exposures and Social Stratification
Authors: Torche Florencia , Nobles Jenna
Published: May 2024

Adverse environmental exposures—war and violence, natural disasters, escalating heat, worsening air quality—experienced in pregnancy are consequential for multiple domains of well-being over the life course, including health, cognitive development, schooling, and earnings. Though these environmental exposures become embodied via biological processes, they are fundamentally sociological phenomena: Their emergence, allocation, and impact are structured by institutions and power. As a result, consequential early-life environmental exposures are a critical part of the sociological understanding of social stratification, intergenerational mobility, and individual and cohort life course trajectories. We review theory and evidence on prenatal exposures, describe enduring methodological issues and potential solutions for elucidating these effects, and discuss the importance of this evidence for the stratification of opportunity and outcomes in contemporary societies.
Subnational Environmental Policy: Trends and Issues
Authors: Vasi Ion B. , Walker Edward T.
Published: May 2024

Policies relevant to many key sociological processes are often subnational, enacted at the regional, state/provincial, and/or local levels. This applies notably in the politics of the environmental state, where public and private subnational environmental policies (SNEPs) have major consequences for managing climate change, addressing environmental injustices, regulating land uses, greening energy markets, limiting pollution, and much more. While sociologists focus more on national policies, diverse sociological contributions emphasize the importance of SNEPs and their origins, diffusion, implementation, and sources of backlash. We begin by providing a typology of SNEPs. Next, we highlight not only environmental sociology (with its particular attention to climate change and energy) but also the sociologies of social movements, politics, the economy, science, risk, and organizations, which have each offered unique perspectives. Finally, we outline an agenda for how sociologists can further elaborate a distinctive perspective that highlights inequality, valuation, diffusion, scale shifts, and venue-shopping up to national and global policy systems.
Simultaneous Model Change Detection in Multivariate Linear Regression With Application to Indonesian Economic Growth Data
Authors: Somayasa Wayan , Djafar Muhammad Kabil , Muhtar Norma , Sutiari Desak Ketut
Published: May 2024

In this paper, we study asymptotic model change detection in multivariate linear regression by using the Kolmogorov–Smirnov function of the partial sum process of recursive residuals. We approximate the rejection region and also the power function of the test by establishing a functional central limit theorem for the sequence of the partial sum processes of the recursive residuals of the observations. When the assumed model is true, the limit process is given by the standard multivariate Brownian motion which does not depend on the regression functions. However, when the assumed model is not true (some models change), the limit process is represented by a vector of deterministic trend plus the standard multivariate Brownian motion. The finite sample size rejection region and the power of the test are investigated by means of Monte Carlo simulation. The simulation study shows evidence that the proposed test is consistent in the sense that it attains the power larger than the size of the test when the hypothesis is not true. We also demonstrate the application of the proposed test method to Indonesian economic growth data in which we test the adequacy of three‐variate low‐order polynomial model. The test result shows that the growth of the Indonesian economy is neither simultaneously constant nor linear. The test has successfully detect the appearance of a change in the model which is mainly caused by the COVID‐19 pandemic in 2020.
Kidney Cancer Incidence among Non-Hispanic American Indian and Alaska Native Populations in the United States, 1999 to 2020
Authors: Melkonian Stephanie C. , Jim Melissa A. , Haverkamp Donald , Lee Madeleine , Janitz Amanda E. , Campbell Janis E.
Published: May 2024

Background:

Non-Hispanic American Indian and Alaska Native (NH-AI/AN) people exhibit a disproportionate incidence of kidney cancer. Nationally aggregated data do not allow for a comprehensive description of regional disparities in kidney cancer incidence among NH-AI/AN communities. This study examined kidney cancer incidence rates and trends among NH-AI/AN compared with non-Hispanic White (NHW) populations by geographic region.

Methods:

Using the United States Cancer Statistics American Indian and Alaska Native (AI/AN) Incidence Analytic Database, age-adjusted incidence rates (per 100,000) of kidney cancers for NH-AI/AN and NHW people for the years 2011 to 2020 combined using surveillance, epidemiology, and end Results (SEER)∗stat software. Analyses were restricted to non-Hispanic individuals living in purchased/referred care delivery area (PRCDA) counties. Average annual percent changes (AAPCs) and trends (1999–2019) were estimated using Joinpoint regression analyses.

Results:

Rates of kidney cancer incidence were higher among NH-AI/AN compared with NHW persons in the United States overall and in five of six regions. Kidney cancer incidence rates also varied by region, sex, age, and stage of diagnosis. Between 1999 and 2019, trends in kidney cancer rates significantly increased among NH-AI/AN males (AAPC = 2.7%) and females (AAPC = 2.4%). The largest increases were observed for NH-AI/AN males and females aged less than 50 years and those diagnosed with localized-stage disease.

Conclusions:

Study findings highlight growing disparities in kidney cancer incidence rates between NH-AI/AN and NHW populations.

Impact:

Differences in geographic region, sex, and stage highlight the opportunities to decrease the prevalence of kidney cancer risk factors and improve access to preventive care.
Plasma versus Tissue Tumor Mutational Burden as Biomarkers of Durvalumab plus Tremelimumab Response in Patients with Metastatic Colorectal Cancer in the CO.26 Trial
Authors: Loree Jonathan M. , Titmuss Emma , Topham James T. , Kennecke Hagen F. , Feilotter Harriet , Virk Shakeel , Lee Young S. , Banks Kimberly , Quinn Katie , Karsan Aly , Renouf Daniel J. , Jonker Derek J. , Tu Dongsheng , O’Callaghan Chris J. , Chen Eric X.
Published: May 2024

Purpose:

Tissue-derived tumor mutation burden (TMB) of ≥10 mutations/Mb is a histology-agnostic biomarker for the immune checkpoint inhibitor (ICI) pembrolizumab. However, the dataset in which this was validated lacked colorectal cancers (CRC), and there is limited evidence for immunotherapy benefits in CRC using this threshold.

Patients and Methods:

CO.26 was a randomized phase II study of 180 patients, comparing durvalumab and tremelimumab (D + T, n = 119 patients) versus best supportive care (BSC; n = 61 patients). ctDNA sequencing was available for 168 patients (n = 118 D + T; n = 50), of whom 165 had evaluable plasma TMB (pTMB). Tissue sequencing was available for 108 patients. Optimal thresholds for stratifying patients based on OS were determined using a minimal P value approach. This report includes the final OS analysis.

Results:

Tissue TMB ≥10 mutations/Mb was not predictive of benefit from D + T compared with BSC in microsatellite stable (MSS) metastatic CRC [HR, 0.71 (95% CI, 0.28–1.80); P = 0.47]. No tissue TMB threshold could identify a high TMB group that benefited from ICI. By contrast, plasma TMB (pTMB) ≥28 mutations/Mb was predictive of benefit from D + T [HR, 0.34 (95% CI, 0.13–0.85); P = 0.022], as was clonal pTMB ≥10.6 mutations/Mb [HR, 0.10 (95% CI, 0.014–0.79); P = 0.029] and subclonal pTMB ≥25.9/Mb [HR, 0.20 (95% CI, 0.061–0.69); P = 0.010]. Higher pTMB was associated with length of time on cytotoxic agents (P = 0.021) and prior anti-EGFR exposure (P = 2.44 × 10−06).

Conclusions:

pTMB derived from either clonal or subclonal mutations may identify a group likely to benefit from immunotherapy, although validation is required. Tissue TMB provided no predictive utility for immunotherapy in this trial.
A Bioinformatically Initiated Approach to Evaluate GATA1 Regulatory Regions in Samples with Weak D, Del, or D– Phenotypes Despite Normal RHD Exons
Authors: McGowan Eunike C. , Wu Ping Chun , Hellberg Åsa , Lopez Genghis H. , Hyland Catherine A. , Olsson Martin L.
Published: May 2024

Introduction: With over 360 blood group antigens in systems recognized, there are antigens, such as RhD, which demonstrate a quantitative reduction in antigen expression due to nucleotide variants in the non-coding region of the gene that result in aberrant splicing or a regulatory mechanism. This study aimed to evaluate bioinformatically predicted GATA1-binding regulatory motifs in the RHD gene for samples presenting with weak or apparently negative RhD antigen expression but showing normal RHD exons. Methods: Publicly available open chromatin region data were overlayed with GATA1 motif candidates in RHD. Genomic DNA from weak D, Del or D– samples with normal RHD exons (n = 13) was used to confirm RHD zygosity by quantitative PCR. Then, RHD promoter, intron 1, and intron 2 regions were amplified for Sanger sequencing to detect potential disruptions in the GATA1 motif candidates. Electrophoretic mobility shift assay (EMSA) was performed to assess GATA1-binding. Luciferase assays were used to assess transcriptional activity. Results: Bioinformatic analysis identified five of six GATA1 motif candidates in the promoter, intron 1 and intron 2 for investigation in the samples. Luciferase assays showed an enhancement in transcription for GATA1 motifs in intron 1 and for intron 2 only when the R2 haplotype variant (rs675072G>A) was present. GATA1 motifs were intact in 12 of 13 samples. For one sample with a Del phenotype, a novel RHD c.1–110A>C variant disrupted the GATA1 motif in the promoter which was supported by a lack of a GATA1 supershift in the EMSA and 73% transcriptional activity in the luciferase assay. Two samples were D+/D– chimeras. Conclusion: The bioinformatic predictions enabled the identification of a novel DEL allele, RHD c.1–110A>C, which disrupted the GATA1 motif in the proximal promoter. Although the majority of the samples investigated here remain unexplained, we provide GATA1 targets which may benefit future RHD regulatory investigations.
Smart home automation towards the development of smart cities
Authors: Alam Tanweer
Published: May 2024

The home automation system is indeed a system that offers a mobile application to monitor it through the smartphone or tablet. It can control home appliances like light, fans, air conditions, and smart security locks, etc. Bluetooth or Wi-Fi is used for remote control of things. The smart home is essentially how it looks: automating with such an easy touch of a button or a voice command the ability to manage things across the home. Several operations were both simple and extremely low-cost, such as setting up a light to turn on and off at the time of your moment. Others need much more money and resources, including advanced spy cameras. Some people thought that technology is taking a really huge part of our lives. It does! we’re living in a modern generation where smart and intelligent systems are necessary to be there wherever we are to make our lives easier and much better, for example, we can do many things faster, better, and more accurate.
An optimized encryption algorithm and F function with Dynamic substitution for creating S-box and P-box entries for Blowfish Algorithm
Authors: Rekha C.  , Krishnamurthy G. N.
Published: May 2024

In the field of cryptography, there has been a massive amount of enhancement in manipulating the plaintext which is unreadable, less prone to crackers and hackers, again manipulating this unreadable form to get back plaintext in some way. The Blowfish algorithm is a block cipher, has complex in structure in generating P-box and S-box entries using encryption algorithm. By simplifying the structure of encryption algorithm as well as F function with dynamic substitution, this can improve the performance by generating P-box and S-box entries of blowfish algorithm. In this paper, the proposed method simplifies the structure to produce P-box and S-box entries in order to reduce computational cost and demonstrates the performance of blowfish. The approach considers different security aspects namely EQ analysis, KS analysis, AV analysis, Entropy, Floating Frequency analysis and correlation of horizontally adjacent pixels in an encrypted image.
MLGrafViz: multilingual ontology visualization plug-in for Protégé
Authors: Merlin Florrence
Published: May 2024

Natural language processing (NLP) is rapidly increasing in all domains of knowledge acquisition to facilitate different language user. It is required to develop knowledge-based NLP systems to provide better results. Knowledge based systems can be implemented using ontologies where ontology is a collection of terms and concepts arranged taxonomically. The concepts that are visualized graphically are more understandable than in the text form. In this research paper, new multilingual ontology visualization plug-in MLGrafViz is developed to visualize ontologies in different natural languages. This plug-in is developed for Protégé ontology editor. This plug-in allows the user to translate and visualize the core ontology into 135 languages.
Comparison of ESP programming platforms
Authors: Filip Rak  , Józef Wiora
Published: May 2024

The growing popularity of ESP boards has led to the development of several programming platforms. They allow users to develop applications for ESP modules in different programming languages, such as C++, C, Lua, MicroPython, or using AT Commands. Each of them is very specific and has different advantages. The programming style, efficiency, speed of execution, level of advancement, or memory usage will differ from one language to another. Users mostly base their choice depending on their programming skills and goals of the planned projects. The aim of this work is to determine, which language is the best suitable for a particular user for a particular type of project. We have described and compared the mentioned languages. We have prepared test tasks to indicate quantified values. There is no common rule because each of the languages is intended for a different kind of user. While one of the languages is slower but simpler in usage for a beginner, the other one requires broad knowledge but offers availability to develop very complex applications.
Designing a secured audio based key generator for cryptographic symmetric key algorithms
Authors: Avinash Krishnan Raghunath  , Dimple Bharadwaj  , M. Prabhuram  , Aju D.
Published: May 2024

Cryptography is a technique to secure data transmissions and ensure confiden-tiality, authenticity and integrity of data exchanged over the digital networks by utilizing mathematical algorithms to transform the plain text (original message) to cipher text (encrypted message) using a key or seed value. The general con-sensus regarding the use of non-deterministic true random numbers (TRN) which are generated from the physical environment such as entropy keys, at-mospheric noise, as a public or private key has received limited encour-agement due to the demanding hardware requirements needed to extract the necessary data from the environment. Therefore, this research aims at design-ing and developing a lightweight program to generate a true random number (TRNG) key using live audio recordings which is further randomized using system date and time. These TRNs can be used to replace the deterministic pseudo random number cryptographic keys that are presently used by indus-tries for a symmetric key encryption algorithm which devolves the algorithm to being conditionally secured. Using the audio based TRNG key would render the same encryption algorithm as unconditionally secured.
Less computational approach to detect QRS complexes in ECG rhythms
Authors: Tariq M. Younes  , Mohammad Alkhedher  , Mohamad Al Khawaldeh  , Jalal Nawash  , Ibrahim Al-Abbas
Published: May 2024

Electrocardiogram (ECG) signals are normally affected by artifacts that require manual assessment or use of other reference signals. Currently, Cardiographs are used to achieve basic necessary heart rate monitoring in real conditions. This work aims to study and identify main ECG features, QRS complexes, as one of the steps of a comprehensive ECG signal analysis. The proposed algorithm suggested an automatic recognition of QRS complexes in ECG rhythm. This method is designed based on several filter structure composes low pass, difference and summation filters. The filtered signal is fed to an adaptive threshold function to detect QRS complexes. The algorithm was validated and results were checked with experimental data based on sensitivity test.
Internet of things: review, architecture and applications
Authors: Tanweer Alam
Published: May 2024

Devices linked to the internet of things (IoT) may communicate with one another in several settings. Furthermore, rather of relying on an existing centralized system, users may develop their own network by using wireless capabilities. This kind of network is known as a wireless mobile ad hoc network. The mobile ad-hoc network (MANET) enables IoT devices to connect with one another in an unstructured networked environment. IoT devices may connect, establish linkages, and share data on a continuous basis. In this system, the cloud's purpose is to store and analyze data acquired from IoT devices. One of the most significant challenges in cloud computing has been identified as information security, and its resolution will result in an even bigger increase in cloud computing usage and popularity in the future. Finally, the goal of this project is to create a framework for facilitating communication between IoT devices in a Cloud and MANET context. Our major contribution is a ground-breaking research initiative that combines cloud computing with the MANET and connects the internet of things. This research might be used to the IoT in the future.
Development of a web application to share hobbies activities
Authors: Antonio Sarasa Cabezuelo
Published: May 2024

The widespread use of the web as a form of interaction has influenced the way people socialize. In this sense, this phenomenon has favored the development of web applications that offer user services aimed at sharing certain personal aspects such as photos, videos, or music. In particular, there is a growing demand for applications that allow users to search for other people who share the same hobbies intending to establish friendly relationships. The architecture for developing an application of this type is generally complex since it requires the manipulation of varied data, the storage of large amounts of data, or the possibility of communication between users in the application. This article presents an example of the design and development of a web application aimed at sharing activities among users who have common hobbies. For this, an ecosystem of different heterogeneous technologies has been used in a multilayer architecture, to optimize the management of the application information.
Wi-Fi fingerprinting-based floor detection using adaptive scaling and weighted autoencoder extreme learning machine
Authors: Atefe Alitaleshi  , Hamid Jazayeriy  , Javad Kazemitabar
Published: May 2024

In practical applications, accurate floor determination in multi-building/floor environments is particularly useful and plays an increasingly crucial role in the performance of location-based services. An accurate and robust building and floor detection can reduce the location search space and ameliorate the positioning and wayfinding accuracy. As an efficient solution, this paper proposes a floor identification method that exploits statistical properties of wireless access point propagated signals to exponent received signal strength (RSS) in the radio map. Then, using single-layer extreme learning machine-weighted autoencoder (ELM-WAE) main feature extraction and dimensional reduction is implemented. Finally, ELM based classifier is trained over a new feature space to determine floor level. For the efficiency evaluation of our proposed model, we utilized three different datasets captured in the real scenarios. The evaluation result shows that the proposed model can achieve state-of-art performance and improve the accuracy of floor detection compared with multiple recent techniques. In this way, the floor level can be identified with 97.30%, 95.32%, and 96.39% on UJIIndoorLoc, Tampere, and UTSIndoorLoc datasets, respectively.
Designing the operation monitor of battery of the generator in the base transceiver station
Authors: Nguyen Thị Xoan  , Tran Văn Bình  , Hà Ngọc Thuan  , Bạch Van Nam
Published: May 2024

The base transceiver station (BTS)'s continuous power supply has been the subject of a lot of research. The majority of research focuses on increasing power usage effectiveness or adding solar battery systems for BTS stations. Due to the geographical conditions in the North of Vietnam, solar cell efficiency is rather poor and the investment cost is quite high, therefore BTS stations are still relying mostly on battery and generator backup systems. This article presents a design solution to designing the operation monitor of battery of the generator in the base transceiver station. From solution design, the authors designed the hardware and software. The device allows communication and sends alarms to the base transceiver station (BTS) manager. Through the testing process, the system has met the requirements of the problem and is easily integrated into the BTS.
Self-quadplexing slot antenna for S and C-band applications
Authors: Padmini Nigam  , Arjuna Muduli  , Sandeep Sharma  , Amrindra Pal
Published: May 2024

This paper demonstrates a novel kind of cavity-backed self-quadplexing slot antenna for the S and C-band applications. The proposed antenna consists of 4 distinct “U”-shaped slots of different lengths and produces the quad frequency band for wireless communication systems. These slots are excited through the separate and orthogonal placed microstrip feed lines of 50 Ω; generates four distinct operating bands at 3.2 GHz, 4.1 GHz, 5.8 GHz, and 7.2 GHz. Due to the perturbation of different U-shaped slots over the substrate integrated waveguide (SIW) cavity with defined positions, the high intrinsic port isolation value is better than 30.5 dB. Thus, the proposed unique antenna structure combines the four independent operating bands with minimum mutual coupling and negligible interference among input ports, which shows the self-quadplexing feature of the antenna. The proposed antenna also has the property of frequency tunability with uni-directional radiation pattern and gain of 5.8 dBi, 5.4 dBi, 4.01 dBi, and 3.47 dBi at corresponding operated frequency. The cross-polarization is 17.3 dB and the front-to-back ratio higher than 21.5 dB at all operating quad bands. There is a good agreement between simulated |S|-parameters results and equivalent circuit model results.
Improved authenticated elliptic curve cryptography scheme for resource starve applications
Authors: Esau Taiwo Oladipupo  , Oluwakemi Christiana Abikoye
Published: May 2024

Elliptic curve cryptography (ECC) remains the best approach to asymmetric cryptography when it comes to securing communication among communication partners in low-computing devices such as wireless sensor networks (WSN) and the Internet of Things (IoT) due to its effectiveness in generating small keys with a strong encryption mechanism. The ECC cuts down on power use and improves device performance, so it can be used in a wide range of devices that don't have a lot of resources. However, most of the existing ECC implementations suffer from implementation flaws that make them vulnerable to cryptanalysis attacks. In this study, flaws in the existing implementation of ECC are identified. A new scheme where the identified flaws are remedied was developed. The results of the security analysis show that the new scheme is an indistinguishable authenticated adaptive chosen ciphertext attack (IND-CCA3), resistant to malleability and man-in-the-middle attacks (MIMA). The results of comparative security analysis show that the mapping scheme employed in the new scheme maps any blocks of plaintext to distinct points on an elliptic curve, which makes it resistant to all attacks that the existing schemes are vulnerable to without having a negative effect on its encryption and decryption time, throughput, or power consumption.
The antecedent e-government quality for public behaviour intention, and extended expectation-confirmation theory
Authors: Hariguna Taqwa , Rahardja Untung , Aini Qurotul
Published: May 2024

The main objective of the study is to identify the antecedent of leadership quality, public satisfaction and public behaviour intention of e-government service. Also, this study integrated e-government quality to expectation-confirmation model. In order to achieve these goals, observational research was then carried out to collect primary information, using the method of data dissemination and obtaining the opinion of 360 from the public using the e-government service and some of the e-government and software quality experts. The results of the study show that the positive association among the e-government services quality and public perceived usefulness, public expectation confirmation, leadership quality and public satisfaction that also play a positive role on the public behavior intention.
Optimization of bakery production by using branch and bound approach
Authors: Rahimullaily  , Darwas Rahmadini , Purwasih Ratih
Published: May 2024

Mommy Ai Kitchen is one the businesses specializing in the bakery business, producing cupcakes, birthday cakes, brownies, and donuts. However, it does not optimally determine each bakery’s production quantity, so it offers fewer profits and becomes a problem. This research aims to find the optimal production quantity so that this business maximizes profits. The method used was integer programming using the branch and bound approach, which counts the decision variable value using the simplex method. This research was based on the number of raw materials on hand wheat flour, sugar, eggs, modal, and the profits of each bakery. Based on the analysis of the branch and bound approach, it was known that the maximum profit value was IDR 253,200, with eight alternative options for the bakeries that were produced. One of them was Mommy Ai Kitchen, which could produce three cupcakes, five birthday cakes, one brownie, and nine donuts to get that maximum profit. Meanwhile, Mommy Ai Kitchen’s estimation could produce one cupcake, one brownie, and six donuts using available materials with a profit of IDR 78,800. As a result, the profit difference before and after integer programming was IDR 174,400.
Key-frame extraction based video watermarking using speeded up robust features and discrete cosine transform
Authors: Bhagyashri S. Kapre , Archana M. Rajurkar
Published: May 2024

Due to advancements in the internet and multimedia technologies, unauthorised users can easily modify video content. As a result, video authentication has been established as a viable solution for ensuring multimedia security. We propose a key-frame based video watermarking scheme based on discrete cosine transform (DCT). First, the Pearson correlation coefficient (PCC) is used to detect the shot boundaries of the input video. To reduce the difficulties created by traditional video watermarking systems; an entropy measure is employed to detect key-frames from input video. Traditional schemes entail embedding the entire watermark into all frames of the video, which is inefficient and time-consuming. To improve the security, robustness, and imperceptibility of the proposed video watermarking scheme, speeded up robust feature points are extracted from each key-frame of the shot and used as reference points for embedding and detection of watermark. The embedded watermark is extracted blindly without using the original data during the extraction process. The results of the experiments reveal that the proposed technique effectively detects shot boundaries under a variety of camera operations and outperforms in terms of imperceptibility and resilience.
An ensemble approach for the identification and classification of crime tweets in the English language
Authors: Siddiqui Tooba , Hina Saman , Asif Raheela , Ahmed Saad , Ahmed Munad
Published: May 2024

Twitter is a famous social media platform, which supports short posts limited to 280 characters. Users tweet about many topics like movie reviews, customer service, meals they just ate, and awareness posts. Tweets carrying information about some crime scenes are crime tweets. Crime tweets are crucial and informative and separate classification is required. Identification and classification of crime tweets is a challenging task and has been the researcher’s latest interest. The researchers used different approaches to identify and classify crime tweets. This research has used an ensemble approach for the identification and classification of crime tweets. Tweepy and Twint libraries were used to collect datasets from Twitter. Both libraries use contrasting methods for extracting tweets from Twitter. This research has applied many ensemble approaches for the identification and classification of crime tweets. Logistic regression (LR), support vector machine (SVM), k-nearest neighbor (KNN), decision tree (DT), and random forest (RF) Classifier assigned with the weights of 1,2,1,1 and 1 respectively ensemble together by a soft weighted Voting classifier along with term frequency – inverse document frequency (TF-IDF) vectorizer gives the best performance with an accuracy of 96.2% on the testing dataset.
Hybrid transformation with 1’st order statistics for medical image analysis and classification
Authors: George Loay E. , Abdullah Maryam Yaseen , Abdulhassan Raghad K. , Al Qaisi Asmaa Abdulrazzaq
Published: May 2024

Skin cancer, one of the most critical forms of cancer, required early detection and documentation for efficient treatment, especially as certain types are fatal. In this study, an artificial neural network (ANN) was utilized to discover and index diverse melanomas using the ISIC 2018 dataset. The pre-processing phase is stringent as it insulates the cancerous fraction of a skin image, involving removing, trimming, thinning, and normalizing. In this phase, unwanted hair pieces on the image are eliminated in this phase. Feature extraction from the clipped image is achieved using a discrete cosine transform (DCT) and a gradient transform to transform it into frequency domain coefficients. Statistical feature extraction is used to reduce the amount of data required for ANN training. A dataset from ISIC 2018 that consists of seven different images from dermoscopic procedures for classification purposes is used in the empirical investigation. An accuracy of 85.44% for DCT in the sub-bands and 76.07% for the sub-band gradient transform was achieved by the applied ANN. The hybrid system's mean squared error (MSE) was discovered to be 3.52×10-4. The work highlights the potential of ANN in the early detection of skin cancer, supporting more efficient treatment and preventing advanced cases.