bluuebunny/crossref_metadata_2025 huggingface dataset:
Nonlinearities correlation of n-alkanes and n-alcohols physicochemical properties
Authors: Tregubov Dmytro , Kireev Oleksandr , Kyazimov Kyazim , Trefilova Larisa , Slepuzhnikov Yevhen , Vavreniuk Sergei
Published: February 2025

The combustible liquid modulating parameter was established to predict the foam glass fire-extinguishing layer as the primary means for liquids ensuring reliable fire extinguishing in combination with other fire-extinguishing means. The formation peculiarities and buoyancy indicators of dry and wet foam glass in polar and non-polar liquids (alkanes and alcohols) were investigated. It is shown that the foam glass buoyancy increases with an increase in the liquid density. The foam glass buoyancy in polar and non-polar liquids was described depending on the liquid density by an approximate linear dependence separately for dry and wet foam glass. The deviation from the linear trend is explained by the foam glass different wettability, some alcohols water solubility, and liquid mixtures peculiarities. The buoyancy relation with flash point was established, which works separately for n-alkanes, n-alcohols and glycols, which was described mathematically. A formula was developed to describe the relationship between flash temperatures and the liquids density. Correlations with a fire-extinguishing layer of dry foam glass for molar mass, molecule or cluster length, stoichiometric combustion reaction coefficient, burning rate on a free surface, density, flash point, boiling point, autoignition temperature were studied. The forecasting possibility the dry foam glass fire-extinguishing layer based on the description of flammable liquids clusters has been established. Mathematical dependences were obtained for the dry foam glass fire-extinguishing layer depending on the expected clusters length in the liquid and a similar dependence for flash points. The conditions for effective extinguishing of alcohols and alkanes with dry foam glass have been determined. Different modes of extinguishing hydrocarbons with flash temperatures tfp<28 оС and tfp>28 оС are recommended, based on the primary layer of 6 cm of wet foam glass with a fraction of 1.0–1.5 cm, with the possibility of finalizing the extinguishing, if necessary, with an inorganic gel by spraying components with an application rate of 0.2 g/cm2.
The study of the cloging process of stormwater infiltration systems with various filter nozzles
Authors: Artemiev Serhii , Rybalova Оlha , Bryhada Olena , Ilinskyi Oleksii , Matsak Anton
Published: February 2025

The process of siltation on multilayer infiltration devices during filtration of stormwater runoff has been studied. Silting of devices determines their operational capacity, nevertheless the quantitative understanding of the silting process is quite limited, especially on devices with different filtering noozles. Therefore, a laboratory study of the effluent infiltration process has been conducted to better understand the physical processes of siltation. The silting process has been studied under conditions of a constant water level, with a concentration of suspended solids of 80 300 mg/dm3 using four filtering nozzles: basalt, sawdust, limestone and polyurethane foam. It has been discovered that the largest layer of silting is formed at the boundary between the filter and the soil due to the formation of a sludge plug, which "protects" the filter/soil boundary. The composition of the sludge plug of the upper layer filtering the volume of the column has been analyzed and it was determined that the physical siltation is mainly caused by migration of sediment particles with a diameter of less than 0.05–0.071 mm (the fraction of which is the main one in the formation of the sludge plug). The issue of distribution of suspended solids according to size throughout the volume of the filtering device has been studied. The main fractions that most adhesion and affect the process of silting devices have been established. Relationships between the rate of infiltration of stormwater runoff and the accumulation of suspended solids in the filter layer has been determined. The lowest rates of decrease in filtration rate have been observed when using limestone (40 %), polyurethane foam and basalt showed similar results (51 % and 55 %), the largest decrease in filtration rate was in sawdust – 74 %. The practical significance of the results of the study lies in understanding the processes of pollution (siltation) of surface runoff treatment devices, which in turn makes it possible to modernize cleaning systems (design, filter nozzles, etc.) and minimize the accumulation of certain fractions of suspended solids on the surface of the watershed.
Еnsuring the safety of passengers during the depressurization of the aircraft cabin in high-altitude flights
Authors: Rudakov Serhii , Myrgorod Oksana , Petukhova Olena , Pirohov Oleksandr , Shcholokov Eduard , Korniienko Ruslan
Published: February 2025

The work includes an improved complex of technical means of collective informing about the values of the maximum reserve time of consciousness preservation in emergency situations (ES) of high-altitude flights. Statistical data on the occurrence of emergency situations (ES) on passenger aircraft were studied, which indicate the need to develop means of ensuring the safety of passengers of civil aviation aircraft in the event of emergency situations.One such complex is a complex of technical means of collectively informing passengers about the values of the maximum reserve time of maintaining consciousness in emergency situations in high-altitude flights. The object of the study is the organization of the safety of aircraft passengers in the event of an emergency.The article addressed the problem of ensuring the safety of aircraft passengers by identifying and eliminating some discrepancies between the possibilities of informing passengers and the lack of a set of technical means that allow such information to be implemented.To eliminate such discrepancies, a mathematical approach to the synthesis of integral indicators of the danger of high-altitude flight emergencies was considered, which made it possible to substantiate the need for the development of technologies for monitoring the situation in the aircraft cabin for the timely recognition of potentially dangerous situations caused by a decrease in barometric pressure. The work solves the scientific task of the research, which includes the development of a set of scientifically based technical solutions for informing aircraft passengers in the event of a high-altitude flight emergency.The peculiarities and distinguishing features of the obtained results, thanks to which they allowed to solve the researched problem, was the development of the algorithm of riskometry of the safety of high-altitude flights based on the human factor, with the subsequent implementation in the complex of technical means of ensuring safety. In order to build a complex of technical means of notifying passengers in the emergency of high-altitude flights, passenger safety assessments are given, calculated in real time on the basis of primary indicators available for registration during the entire flight (including in the event of an emergency). The practical application of the obtained results can be used in the aviation field in the event of an emergency.
Behavior patterns of reinforced concrete structures of modular shelters in explosion conditions
Authors: Tolok Igor , Rybka Evgeniy , Pozdieiev Serhii , Kustov Maksim , Novhorodchenko Alina , Plisko Yuliia
Published: February 2025

The results of mathematical modeling of the impact of the explosion and the resulting stress-strain state in reinforced concrete structures of a modular shelter are presented. The compliance of the shelters with the safety conditions required by the current standards of Ukraine is also established. For this purpose, the behavior of the enclosing structures of ground modular shelters under the effects of explosions and the action of penetrating ionizing radiation was investigated, which guarantees the safety of people inside the shelters and their protection from the effects of air strikes. The scientific study obtained results that allow investigating the mechanisms of destruction or loss of integrity of shelter structures and establishing the relationship between these aspects and ensuring the performance of its protective functions under the effects of an explosion during enemy shelling. The results of the study were obtained through the development of a new approach to calculations based on the use of the warhead of the corresponding projectile in TNT equivalent, the explosion distance and the position of the point where the explosion occurs. The corresponding calculations were used in the LS-DYNA software package, where the behavior of reinforced concrete shelter structures under load conditions was mathematically described, and mathematical relations of strength and plasticity theories were also used. And the pressure determined by these parameters can be used to study its impact on structures. The results of mathematical modeling of the behavior of protective shelters under explosion conditions were obtained, which allow us to investigate the mechanisms of destruction or loss of integrity of shelter structures and establish the relationship of these aspects with ensuring the performance of its protective functions under the influence of an explosion. The implementation of the research results is the presentation of technical proposals for modular shelters to protect the population from damage caused by combat operations.
Аcoustic monitoring of sources of emergency situations related to the device of firearms
Authors: Tiutiunyk Vadym , Levterov Alexander , Tiutiunyk Olga , Usachov Dmytro
Published: February 2025

The method of identifying the facts of the use of various types of firearms has been improved based on the use of the average characteristic of the acoustic spectrum of a shot, by determining the characteristic frequencies with maximum amplitude values, which consists in determining the characteristic frequencies under conditions of exceeding the threshold level of amplitudes of the harmonics of the received signal, determining the energy of such a spectrum, and subtracting the energy of the reference spectrum from the energies of the experimentally obtained spectra of shots. The use of the improved method for studying the characteristics of the acoustic spectra of shots from a Makarov pistol of 9 mm caliber, a traumatic pistol "Fort-14R" and an AK-74 assault rifle of 5.45 mm caliber made it possible to identify the type of firearms by the received acoustic signal with a probability of 0.95. Based on the research results, a functional diagram of the hardware implementation of the improved method for identifying the facts of using various types of firearms by the spectral properties of the received acoustic signal has been developed. The circuit implements a median filter, bandpass filters, a block of characteristic frequencies of shots, an encoding block, a decoder block and a block of logical elements "Conjunction". The identification process consists of analyzing an 18-bit code in 6 groups of 3 digits, at the output of the processing results there is a corresponding combination of signals that determines the belonging to a certain type of weapon and / or its presence in the database of known samples. Based on the hardware implementation circuit of the improved method for identifying the facts of the use of various types of firearms by the spectral properties of the received acoustic signal, the features of the development and operation of a geographic information system for acoustic monitoring of terrorist emergencies and automated identification of facts of use in an urban area are established.
Evaluation of Consumer Loyalty for Purchasing Tourism Tickets in Marketplace
Authors: Haykal Azzahrah Putri , Suhud Usep , Wibowo Setyo Ferry
Published: February 2025

The purpose of this study was to determine consumer loyalty in purchasing tourist tickets through the variables of system quality, information quality, social media marketing activities, customer satisfaction and perceived value. This study was conducted using quantitative methods and a total of 240 respondents. The results of the study were seven accepted hypotheses and three rejected hypotheses.

Keywords: system quality, information quality, social media marketing activities, customer satisfaction, perceived value, customer loyalty
Segmental Fracture in Younger Children Managed by Submuscular Plating: A Case Report
Authors: Indratama Dhifo , Akbar Taufik
Published: February 2025

Introduction: Complex femur fractures in children are rare and occur due to high-energy trauma. Most of these fractures are managed surgically with the primary goal is the restoration of the anatomical alignment. In this report, we describe the management of complex femur fractures in pediatric patients.
Case Presentation: A 5-year-old boy who came to the emergency room at Andalas University Hospital with left thigh pain which occurred due to a high-energy traffic accident since 10 hours before admission. From primary survey, patient was in stable condition. From local examination there was discrepancy and angulation on the left thigh with local tenderness. Plain radiographic studies on the left femur showed a segmental diaphyseal fracture. Afterwards, patient underwent open reduction and internal fixation (ORIF) with submuscular plate fixation on the same day.
Result: After surgery, discrepancy was inapparent. On one month follow up, healing and rehabilitation was uneventful, with patient being active and no infection spotted. After three months of follow up, abundant callus formation was observed on the follow up x ray. Clinically, patient did not complain any pain, played actively, and range of motion almost returned to normal as shown by near-normal gait and ability to do various of movements.
Discussion: Although theoretically segmental fractures are best managed by Titanium Elastic Nailing System (TENS), multiple clinical setting and facilities considerations may sometimes varies the options available. Submuscular plate fixation is a good choice in settings where C-arm is unavailable and appropriate implants are scarce. This is beneficial in terms of attaining a good reduction and fixation especially for complex patterned fracture, although, one must point out the possible shortcomings such as more bleeding and much soft tissue stripping that may hinder healing process.
Conclusion: Complex femur fractures in children are uncommon and challenging to manage. Understanding principles of fracture fixation and choosing the best suitable implants for each case allows for excellent functional outcomes and early patients ambulation.

Keywords: comminuted, fracture, pediatric, plate fixation
UNMANNED AERIAL VEHICLE (UAV)-BASED COMPUTER VISION MODEL FOR REAL-TIME BIRDS DETECTION IN RICE FARM
Authors: Yakubu I. , Audu M. M. , Zayyanu Y.
Published: February 2025

Rice farming in Nigeria suffers significant losses due to bird damage, necessitating advanced mitigation strategies. This study investigates the integration of computer vision with unmanned aerial vehicles (UAVs) to provide real-time bird detection and deterrence in rice fields. Given the varied agricultural conditions in Nigeria—including different farm sizes, vegetation density, and lighting conditions—the proposed system was designed for adaptability and robustness. Utilizing a dataset of 1,113 bird images captured via UAVs and ground cameras, a YOLOv8 model was trained with rigorous preprocessing and augmentation techniques. The model achieved a precision of 85%, recall of 70%, and mAP@50 of 80%, demonstrating strong detection capabilities. However, performance decreased in densely occluded environments, with mAP@50:95 stabilizing at 39%. Real-time testing confirmed the system's practical applicability and reliability under diverse environmental conditions. This solution represents a cost-effective, scalable approach to protecting rice fields, offering a significant leap forward in precision agriculture.
Study on the Optimization of Precise Positioning Biopsy and Subsequent Treatment Strategy of Cervical Lesions under Hysteroscopy
Authors: Jiating Li
Published: February 2025

Cervical lesions remain a significant public health challenge due to their potential progression to cervical cancer, necessitating effective diagnostic and therapeutic approaches. This study focuses on the optimization of precise positioning biopsy and subsequent treatment strategies for cervical lesions under hysteroscopy, a minimally invasive diagnostic procedure. By leveraging advanced imaging modalities, such as narrow-band imaging (NBI) and artificial intelligence (AI)-assisted diagnostics, hysteroscopy offers unparalleled accuracy in detecting and sampling suspicious lesions. Comparative analyses reveal its superiority over traditional methods, including colposcopy, in enhancing diagnostic sensitivity and specificity.
Subsequent treatment strategies tailored to biopsy results emphasize minimally invasive techniques, fertility-preserving options, and emerging molecular therapies. High-grade lesions are addressed through targeted excisional or ablative procedures, while advanced cases benefit from multidisciplinary interventions, including immunotherapy and chemoradiation. The integration of AI in diagnostic workflows and the development of portable hysteroscopic systems represent promising avenues for improving accessibility and efficiency.
This study synthesizes existing advancements, identifies persistent gaps, and proposes innovative solutions to refine the diagnostic and therapeutic landscape of cervical lesion management. By addressing barriers such as procedural costs, training limitations, and variability in diagnostic accuracy, this research aims to contribute to the equitable and effective treatment of cervical lesions, ultimately reducing the global burden of cervical cancer.
Innovative Vesicular Drug Delivery System of Ibuprofen with Unsaturated Fatty Acids: Formulation and Evaluation
Authors: Rukari T.G. , Gavali P.A. , Patil V.J. , Gaonakr S.S. , Rathod K.S. , Patil Y.M. , Dhongade Y.R. , Jagtap V.A.
Published: February 2025

Inflammation is a complex physiological response involved in numerous pathological conditions, requiring effective treatment. Non-steroidal anti-inflammatory drugs (NSAIDs) have long been utilized to alleviate inflammation associated symptoms. Conventional topical formulations of NSAID suffer from limitations such as poor skin penetration, low drug retention, and inadequate therapeutic efficacy. To overcome this limitations, novel vesicular drug delivery systems, particularly transferosomes, have emerged as promising alternatives. Transferosomes, a specialized type of deformable liposomes, offers unique advantage for targeted drug delivery through the skin. They can deform and squeeze through narrow intercellular spaces, enhancing drug permeation into underlying tissues. This facilitates deepest penetration of NSAIDs into inflamed regions, maximizing therapeutic effects while minimizing systemic exposure and adverse effects. Transferosomes, formed via thin film hydration method with oleic acid, cholesterol, surfactant, and organic solvent. They have a particle size of 297nm and a mean zeta potential of -24.2mV. Entrapment efficiency is 83% and demonstrates effective drug retention. The optimized batch is chosen on particle size and entrapment efficiency, and these incorporated into carbopol 934 gel and evaluated for appearance, grittiness, texture pH, spreadability, extrudability, drug content and in-vitro drug release. This comprehension evaluation ensures formulation efficiency. Overall, the development and evaluation of novel vesicular drug delivery systems, particularly transferosomes, represent significant advancement in drug delivery technology. By utilizing their unique properties, these systems hold promise for improving therapeutic efficacy and enabling sustain release in the treatment of inflammatory conditions.
Method Development and Validation for Simultaneous Estimation of Bempedoic Acid and Ezetimibe in Pharmaceutical Dosage Form by
RP- HPLC
Authors: Vanga Supriya , Aneesa Aneesa , C. Parthiban , M. Sudhakar
Published: February 2025

A straightforward, accurate, and precise method has been successfully developed for the simultaneous estimation of Bempedoic acid and Ezetimibe in both bulk and tablet dosage forms. This achievement marks a significant advancement in pharmaceutical analysis. The method employed a chromatographic approach using a standard BDS C18 column measuring 150 x 4.6 mm with a particle size of 5μ. The mobile phase, comprising awell-balanced blend of 0.01N Ammonium acetate Buffer and Methanol in a 55:45 ratio, was efficiently pumped through the column at a constant flow rate of 1 ml/min. The critical buffer used in this methodology was 0.01N Ammonium acetate buffer, maintaining a stable temperature at 30°C. The optimized wavelength of 230 nm was selected for analysis. The retention times for Bempedoic acid and Ezetimibe were precisely determined as 2.219 minutes and 2.794 minutes, respectively, demonstrating the method's reproducibility with %RSD values of 0.3 and 0.4. Impressive recoveries of 100.25% for Bempedoic acid and 99.72% for Ezetimibe were achieved. Furthermore, the method exhibited impressive sensitivity with LOQ and LOD values of 0.07, 0.24, and 0.01, 0.04, respectively, derived from the regression equations. This method's exceptional efficiency not only reduced retention times but also minimized overall run time, offering a practical, cost-effective solution suitable for routine quality control testing within the pharmaceutical industry. Its simplicity and accuracy make it a valuable addition to pharmaceutical analysistechniques
A Review on the Resistance of Probiotic Microorganisms to Antibiotics
Authors: Ram Aranyak , Bhattacharjee Dibyojyoti , Alam Sk Mahbub , Jana Snehasis , Pal Rohan
Published: February 2025

Live microorganisms that give the host health benefits when taken in pre-determined doses are known as Probiotics. Probiotics are gaining popularity worldwide and are widely used in food and medicine. Consumption of probiotics is increasing with further in-depth research on the relationship between intestinal flora and host health. Most people pay more attention to the function of probiotics but ignore their potential risks, such as infection and antibiotic resistance transfer to pathogenic microbes. Some probiotic strains harbour genes for resistance that could potentially be shared with harmful bacteria in the gut, contributing to the overall problem of antimicrobial resistance. This horizontal gene transfer is one mechanism by which antibiotic resistance (AMR) could arise due to probiotics. This horizontal gene transfer is successfully carried out by, Conjugation, Transformation, Transduction processes. Probiotics, live bacteria offering gut health benefits, are generally safe. However, some potential risks exist. Certain probiotic strains may carry genes for antibiotic resistance on plasmids, transferable DNA. This raises the concern of creating multi-drug resistant pathogens. Additionally, some individuals with weakened immune systems or underlying health conditions may experience side effects like bloating or gas. To mitigate these risks, choosing probiotics with well-researched strains and documented safety profiles is crucial. Consulting a healthcare professional before starting probiotics, especially if immunocompromised or with chronic conditions, is also recommended. In this document we attempted to list few of the antibiotic resistance (AMR) which propagate through probiotics.
Nanotechnology at the Molecular Level: Nanoemulsion Demystified
Authors: Chaudhari Gopa , Mulla Taufik
Published: February 2025

A revolutionary drug delivery method called nanoemulsion allows for regulated or prolonged drug release. The application of nano and sub-micron particles in the fields of food, cosmetics, and pharmaceuticals is increasingly gaining popularity. Submicron-sized emulsions known as nanoemulsions are being studied as medication carriers to improve the delivery of pharmaceutical drugs. When the appropriate cosurfactant and surfactant are utilized to combine two immiscible liquids into a single phase, these systems are thermodynamically stable and isotropic. Specifically, this interest has been increasing alongside advancements in stabilization and emulsification methods. The two main categories of nanoemulsion preparation techniques are high-energy and low-energy spontaneous emulsification methods. Since nanoscale emulsions have unique qualities including great stability, a beautiful look, high performance, and sensory benefit, their popularity has increased significantly in recent years. In fact, one of the most widely used formulation technologies in the cosmeceutical and pharmaceutical industries is nanoemulsions. In addition to their tiny droplet size, nanoemulsions' exceptional kinetic stability and thermodynamic properties have accelerated their development as a drug delivery technology for cosmetic products and dermatological treatments including bioactive ingredients. The formulation and preparation technique greatly influence the nanoemulsions' quality. Their primary focus is on distributing high-quality products to consumers while also exploring the possibility of mass production. However, formulators do have some restrictions, particularly with regard to the dispersion of active substances.
A Comprehensive Review of IoT Security: Challenges, Authentication Mechanisms
Authors: Palak Patel
Published: February 2025

The integration of IoT, blockchain, cloud computing, and encryption is transforming healthcare systems by addressing key challenges in security, privacy, and data management. This study examines innovative authentication frameworks for securing electronic health records (EHRs) and healthcare management systems, emphasizing the role of blockchain in enhancing data integrity, decentralization, and secure data sharing. Blockchain prevents single points of failure and ensures patient privacy through encryption and pseudonymization. Authentication mechanisms like multi-factor authentication (MFA), smart cards, and biometrics are crucial for mitigating threats such as replay attacks, man-in-the-middle attacks, and unauthorized access. For IoT-enabled healthcare, securing communication between devices and servers is essential. Techniques like Elliptic Curve Cryptography (ECC), fuzzy extractors, and Physically Unclonable Functions (PUFs) provide efficient, secure communication while minimizing computational burden. The study proposes an advanced security model that integrates lightweight encryption to address challenges in scalability, heterogeneity, and cyber threats. It also includes dynamic key-based authentication and context-aware authentication using RSSI to enhance security. This model ensures robust security for IoT-enabled healthcare systems, addressing emerging risks and ensuring the resilience of healthcare infrastructures. The research aims to optimize resource utilization, mitigate sophisticated cyber threats, and provide cost-effective scalability for secure, efficient health data management.
Improving Recognition Accuracy in Multimodal Biometric Systems: A Study on Facial Traits and Fusion Strategies
Authors: Dipti Yadav
Published: February 2025

Multimodal biometric systems are gaining prominence for their ability to enhance recognition accuracy and system security by integrating multiple biometric modalities. This study focuses on improving recognition accuracy through the effective utilization of facial traits and fusion strategies in multimodal systems. Facial traits, including features such as eyes, nose, lips, and chin, offer unique identification markers, but their performance can be hindered by factors like aging, lighting conditions, and variations in pose. To address these challenges, the integration of facial traits with other biometric modalities, such as fingerprints, iris scans, or behavioural biometrics, is proposed. The study explores various fusion strategies—feature-level, score-level, and decision-level—to combine information from multiple modalities effectively. Advanced machine learning techniques, including Support Vector Machines (SVMs) and Neural Networks, are employed to optimize feature extraction and fusion processes. Adaptive learning methods are integrated to ensure the system evolves with dynamic user data, enhancing its robustness and adaptability to real-world conditions. The research identifies key challenges in multimodal biometric systems, such as data security, computational complexity, and ethical concerns, and proposes solutions to mitigate these issues. Experiments conducted on diverse datasets demonstrate significant improvements in recognition accuracy and reduced error rates when employing multimodal biometric fusion. This study also evaluates user perceptions and ethical considerations surrounding multimodal systems, emphasizing the importance of privacy, transparency, and compliance with data protection regulations. By leveraging the complementary strengths of facial traits and other biometric modalities, the proposed system achieves enhanced accuracy and reliability, making it suitable for applications in secure authentication, identity verification, and access control. The findings contribute to advancing biometric technologies, paving the way for robust and user-friendly multimodal systems in a variety of real-world scenarios
Managing Economic Efficiency in Dairy Production: Strategies for Innovation Development in the Context of Digitalization and Environmental Sustainability
Authors: Kristina Krichfalushii-Stepanov
Published: February 2025

The primary aim of this study is to identify effective strategies for innovation development that can bolster dairy production efficiency in the context of modern challenges. Key tasks include examining the current state of digitalization within the dairy industry, assessing the implications of environmental sustainability demands, and evaluating innovative approaches that align with these goals. This article investigates the management of economic efficiency in the dairy sector, focusing on how digital technologies can be seamlessly integrated to promote sustainable practices while maximizing productivity. The study employs a comprehensive analysis of digital tools, such as precision agriculture, automated milking systems, and data analytics, alongside an assessment of sustainable practices, including waste management and resource conservation. Research results highlight that embracing digital tools dramatically improves operational efficiency. Additionally, sustainable practices are found to enhance product quality while promoting environmental stewardship.The findings affirm that integrating digital technologies and sustainability strategies can yield substantial benefits for dairy producers. The article concludes by recommending actionable pathways for stakeholders in the dairy chain to support the transition toward a more efficient and sustainable future. The study ultimately contributes to the discourse on dairy management practices, underscoring the importance of innovation and sustainability in ensuring the sector's resilience and competitiveness in a rapidly changing economic landscape.
Modeling Seismic Signals of an Earthquake through Symbolic Dynamical System: The Case of Surigao Region, Philippines
Authors: Teotima Evangelista Gorres
Published: February 2025

Earthquakes pose threats globally, most especially in developing hotspots such as the Philippines, given that it falls under the Pacific Ring of Fire. One of the most seismically active regions within the country is the Surigao region located in northeast Mindanao, where two large earthquakes hit in December 2023 with 7.4 and 6.8 magnitudes. The outcome of this study underscores the need for accurate earthquake forecasting models in such high-risk regions. Conventional methods for seismic signal modeling usually lose the complexity and nonlinear of seismic datasets. This paper uses symbolic regression with genetic programming as a means to come up with a more accurate and explainable model in estimating earthquake magnitudes in the Surigao area. A technique in machine learning, symbolic regression generates mathematical expressions which best fit empirical data, and it doesn't require a predefined model configuration. The developed model identifies critical parameters relevant to seismic phenomena and accurately estimates the magnitudes of earthquakes within the considered region. The model, such as the magnitude of 3.0, as happening in September 2024. The results obtained in this study contribute to the accuracy of forecasting for earthquakes by providing SR as an efficient tool for studying seismic records. These findings have the potential to further improve this effort in disaster preparedness and risk reduction that saves lives and reduces economic losses in earthquake-prone areas. Collaboration is encouraged with a continued comprehensive revision toward research for further exploration of broader applications in seismic hazard analysis.
Extreme Learning Techniques for Enhanced Sentiment Analysis
Authors: Akkireddi Vara Prasad
Published: February 2025

Extreme learning approaches are used to perform sentiment analysis on restaurant evaluations. Sluggish training and overfitting are two problems that traditional supervised learning techniques frequently face. In order to prevent overfitting and speed up training, extreme learning makes use of single hidden layer neural networks with randomly assigned weights. The goal is to create a quick and accurate model for identifying sentiment in meal reviews and to assess the differences between supervised learning techniques and models based on extreme learning. In order to map the scores to attitudes, the study uses a dataset of food reviews, where scores larger than three are interpreted as favourable and scores below that as negative. Training and testing sets are created from the dataset following preparation, which includes handling missing values and choosing pertinent columns. For modeling purposes, text data is transformed into Term Frequency-Inverse Document Frequency (TF-IDF) characteristics. The network is given randomly initialized weights and biases in both single layer and multi layer perceptron implemented. During model training, the loss function is computed, weights and biases are adjusted by backpropagation, and predictions are computed using forward propagation technique. By using a threshold of 0.5, the model's accuracy is assessed. Accuracy scores are used as a statistic for reporting training and testing accuracy. The model further validates the effectiveness for sentiment analysis in the context of food reviews by showing quicker training times and less sensitivity to overfitting. The work presents extreme learning approaches as a competitive substitute for supervised learning, which advances sentiment analysis tools. Comparing the model based on extreme learning to traditional supervised learning methods, experimental results show that the latter achieves competitive accuracy in sentiment analysis. Faster training times and less sensitivity to overfitting are further features. As a strong substitute for supervised learning techniques, this study highlights the effectiveness of extreme learning approaches for sentiment analysis in meal evaluations. Extreme learning improves the efficacy and precision of sentiment analysis models, especially in areas such as restaurant evaluations, furthering the practical uses of sentiment analysis tools.
The Effect of Atrium Roof Forms on the Day Light Performance of Atrium and Adjoining Spaces: An Analytical Study
Authors: Sarvesh Anand, Manoj Kumar
Published: February 2025

Daylight is a key component of a sustainable environmental approach to the building design. An atrium is a major source which allows the maximum daylight to come inside the deep plan building which reduces the demand of artificial light hence leads to an energy efficient building design. However, direct sunlight is problematic because of a source of glare which increases the thermal heat gain inside the building. The key atrium components are the roof fenestration system, the geometry of the atrium well, the reflectance of the well's surfaces and the daylight levels achieved in spaces adjacent to the well. This paper describes the various atrium roof forms and its performance by simulating different types of atrium roof 3D model. Day lighting analysis was done using Climate Studio tool with Rhinoceros 3D 7.0. Built on Energy Plus and a novel RADIANCE-based path tracing technology.
Comparative Review of AWS and Azure Confidential Computing Systems
Authors: Nikhil Sagar Miriyala
Published: February 2025

Confidential computing is an emerging field that focuses on ensuring the privacy and security of data during computation, addressing the increasing concerns with respect to data breaches and unauthorized access to sensitive information in cloud environments. The paper provides a comparative review of two prominent cloud platforms offering confidential computing solutions, namely, AWS Nitro Enclaves and Azure Confidential VMs with Intel SGX Enclaves. We analyse both platforms across multiple dimensions, such as their core components, attestation processes, communication mechanisms, and performance limitations. Additionally, we will evaluate practical factors such as regional availability, types of instances, and resource allocations. By analysing the unique features, advantages, and trade-offs of each platform, the paper aims to provide a clear understanding of why confidential computing is important in the context of increasing data privacy requirements and regulatory frameworks, such as GDPR and how these technologies enable secure and isolated execution of sensitive workloads on the cloud.
Cognitive Framework to Identify Women Empowerment using Swarm Enhanced Neural Networks
Authors: Sreedevi N
Published: February 2025

Women are contributing equally with males to the development of a healthy family, society, and nation. One indication of women's empowerment is socioeconomic level. This study is an innovative one concentrated on the classification and comparison of Socio-Economic Status (SES). Women along the evolution of a cognitive model. Many factors affect the socioeconomic level of women; consequently, an artificial neural network (ANN) model using Fire Work Optimization (FWO) is used to detect, forecast, and classify this status. Operating for optimization, FWO uses swarm intelligence. Training ANN for classification goals using FWO. The results of the experiment prove that FWO-ANN performed more efficiently giving 99.34 percent accuracy in classification. Other swarm optimization methods, such as Particle Optimization (PSO) and Cat Swarm Optimization (CSO), were not as accurate or efficient as the current model.
Sustainable Development Using SPSS an Emerging Software Tool: A Quantitative Analysis
Authors: Noorjahan Sherfudeen
Published: February 2025

Incorporating economic, social, and environmental considerations into policymaking and corporate practices is essential for achieving sustainable development, which is multidimensional. This study looks into how statistical software tool like SPSS can be used to test and model the processes of long-term growth in a number of different areas. The study looks at big datasets from a lot of different industries and regions to find out how they measure important sustainability indicators like carbon emissions, resource efficiency, and socioeconomic equity. This is done by using complex quantitative methods to look at the data. Integrating classic and modern statistical software is made novel in this study; which makes easier to simulate complicated sustainability patterns and gives policymakers and companies information they can put into practice. Using data mining, AI-enhanced features, and machine learning algorithms in these tools, the research finds links between sustainability factors and the success of different sustainability initiatives that were not known before. Even though these software tools have a lot of potential, the study points out some limitations like the data quality, complexity to judge the long-term benefits of sustainability and to make sure that different measurement frameworks used in different regions and industries. The findings demonstrate that businesses may enhance their long-term profitability and environmental impact by incorporating sustainable development objectives into their operations. Additionally, the research highlights the importance of using data to inform decision-making in the creation of sustainable policies. Using SPSS has several benefits, such as improving predictive capacities, processing massive information accurately, and providing a thorough study of sustainable development initiatives. This study adds to theoretical and practical knowledge by providing a data-driven strategy for achieving global sustainability objectives.
Sustainable Supply Chain Management: Assessing Environmental Impact Using Data Analytics
Authors: Noorjahan Sherfudeen
Published: February 2025

Organizations have begun to use data-driven decision-making techniques in response to the rising significance of sustainability in supply chain management. To evaluate and improve the environmental impact of supply chains, this study examines the use of data analytics, in particular the use of sophisticated regression models. This study looks at how various supply chain processes including transportation, procurement, and production affect the environment and examines the sustainability measures. This study uses novel regression methods, termed as multivariate adaptive regression splines (MARS) as well as generalized additive models (GAMs), to show the non-linear relationship among the environmental factors and supply chain choices. The results show that these models help with sustainability performance predictions and that they can aid businesses in making eco-friendly supply chain choices. By combining sustainability objectives with data analytics to enhance supply chain environmental performance, this study contributes to the expanding body of knowledge.
Exploring the Impact of Environmental Policies on Economic Growth: An Empirical Analysis Using SPSS
Authors: Noorjahan Sherfudeen, R. Aruna
Published: February 2025

Various locations and businesses have seen varied results when trying to determine the link between environmental policy and economic success which has raged on for decades. By using statistical analysis via the Statistical Package for Social Sciences, this research tries to evaluate how environmental rules and policies affect economic development. Specifically, this study looks at energy consumption, employment rates, carbon emissions, and gross domestic product (GDP) in a number of different economies during the last 20 years. This study offers a fresh way to look at the effects of green policies by using a larger and more varied dataset. It does this by getting around the problems that earlier studies had with using different methods, having small sample sizes, and differences between countries. This also uses sophisticated SPSS regression methods to fix prior issues with model specification and multicollinearity, which makes the results more reliable. Policymakers who want to balance sustainable development (SD) with economic growth can use the results of this study. It adds to the ongoing discussion by showing how environmental restrictions affect economic performance. The results show that different policy actions have different effects, both beneficial and bad, and they highlight the necessity for complex approaches to environmental management.
An Energy Efficient Wireless Sensor Network for Optimal Routing using Hybridized Bio-Inspired Technique: An Integration of Modified Harmony Search and Competitive Swarm Optimization Algorithm
Authors: Ali Bostani
Published: February 2025

Due to their spatial distribution and energy constraints, the efficiency of Wireless Sensor Networks (WSNs) relies heavily on effective energy management. Optimizing energy consumption can significantly enhance network longevity and performance. While clustering techniques, such as Low Energy Adaptive Clustering Hierarchy (LEACH), help reduce energy usage, they suffer from inefficient local searches and poor exploration-exploitation balance.To address these limitations, this study proposes a hybrid bio-inspired optimization technique—Modified Harmony Search Algorithm (MHSA) combined with Competitive Swarm Optimization (CSO)—for optimal cluster head (CH) selection. The MHSA enhances global search efficiency, while CSO dynamically adapts to network changes, leading to improved convergence rates and balanced energy distribution.Performance evaluation, based on key metrics such as the proportion of alive nodes, residual energy, and throughput, demonstrates that the MHSA-CSO hybrid significantly outperforms existing WSN approaches. The proposed method achieves latency reductions by more than three orders of magnitude and energy efficiency improvements exceeding two orders of magnitude, effectively extending the operational lifetime of WSNs. This approach offers a robust, energy-efficient routing solution for WSNs, contributing to more sustainable and resilient network designs.
Review of Delay Factors in Construction Projects of Riyadh; A Case Study to Enhance Project Performance with Sustainability
Authors: Muhammad Wajidullah Khan
Published: February 2025

The construction project delays can be defined as an extension of time beyond the contractual time agreed during the tender stage, in past decade almost 70% of mega construction projects experienced time overruns. The construction professionals have specified that they have been facing average time delay of 10 to 30% from the original duration of the project. In modern building projects delays during MEP (Mechanical, Electrical and Plumbing) system installation phase are exceeding due to complexity and mechanized application of services in building projects. This study investigates the key challenges affecting the timely completion of construction projects and causing delays. As a case study chosen two mega ongoing construction projects in Riyadh, Saudi Arabia to investigate delays and their impact on project performance and sustainable development in construction. The challenges were discovered from the literature and investigated to analyze their significance towards project performance improvement and sustainable construction development. Data collection was administered through structured questionnaire survey performed among 291 construction professionals according to the sample size to find the objectives using 5-point Likert-scale. The impacts were grouped into main Kep Performance Indicator (KPI’s) of project i.e. quality, cost and time. The outcome reported various critical challenges contributed to project delays; poor communication, non-compliance with specifications, design approvals and monthly payments related factors being the most important challenge in the construction industry. The top strategies such as smooth coordination, approved design before execution, mock-ups, prototypes and timely payments of claims could significantly control project delays and enhance performance with sustainability. Finally, the study findings will contribute to the body of knowledge to mitigate delays and will help the construction professionals to enhance performance with sustainability for upcoming construction projects in Saudi Arabia.