bluuebunny/crossref_metadata_2025 huggingface dataset:
A mathematical approach for modeling the blood flow containing nanoparticles by employing the Buongiorno’s model
Authors: Li Shuo , Ahmad Sohail , Ali Kashif , Hassan Ahmed M. , Hamali Waleed , Jamshed Wasim
Published: October 2023

A mathematical model has been suggested for the numerical study of blood flow in a vessel due to the pumping action of the heart. Blood is assumed to contain some impurities in the form of chemically reactive species (undergoing a first-order irreversible reaction) and, being a hybrid nanofluid, also contains the nano-sized solid particles, thus forming a homogeneous mixture which is subjected to a pressure gradient (of trigonometric nature) in the horizontal direction. Human vessel is subjected to a transverse magnetic field and is presumed to be filled with plaque which is considered as a porous medium, and is mathematically modeled by applying the Darcy–Forchheimer theory. The nonlinear nature of the governing equations steered toward the decision of using the numerical approach to obtain the solution of the governing system, which led to the discovery of a linear concentration variation across the vessel at higher values of the Reynolds number. Finally, a 38% rise in the heat transfer has been noted due to the presence of solid particles in the human blood.
Triboelectric nanogenerator based on a water droplet spring with a concave spherical surface for harvesting wave energy and detecting pressure
Authors: Wang Weiyuan , Tang Weimin , Wang Ping , Liu Zhenhui , Wang Zhenkun , Qiao Shuo
Published: October 2023

Triboelectric nanogenerator (TENG) has strong application potential in collecting nano energy and detecting micro motion. In this study, a TENG based on a water droplet spring with a concave spherical surface was proposed. The dispersive-aggregative triboelectric nanogenerator (DA-TENG) added the water droplet to the concave spherical surface which was covered with circular copper foil electrode and polytetrafluoroethylene. External loading/unloading caused water droplet dispersion/aggregation. Therefore, the solid and liquid electrodes could generate voltage by contacting and separating. Meanwhile, DA-TENG design parameters were optimized to find optimal output conditions, including the water droplet volume, the cross-sectional radius of the concave spherical surface, the force area of the elastic membrane, and the excitation frequency of the shaker. In addition, the voltage signal generated by volunteers pressing DA-TENG could show the keyboard usage habits of different people and thus serve as a basis for personnel identification, which suggested DA-TENG could be used as a self-powered pressure detector. Finally, DA-TENG was designed as a harvesting wave energy device. Under a 6 MΩ load, a unit of work could produce a peak current of 1.7 μA and an effective power of 8.82 μW; three units could produce a peak current of 5.3 μA.
Linguistic and cultural peculiarities of Turkish and Arabic speech etiquette in farewells and greetings
Authors: Dulayeva Elnara , Mamedova Fatima , Khalel Agnur
Published: October 2023

The peculiarities of speech etiquette in each language are determined by historical, cultural, social, cognitive, and religious factors. The study of greeting and farewell speech formulas in Turkish and Arabic is relevant for identifying key linguacultural meanings and concepts using conceptual modeling. The purpose is to analyze the linguistic and cultural conditioning of etiquette formulas in these languages. Linguacultural analysis of linguistic facts was used, along with elements of conceptual, communicative, comparative, and semantic analysis. The results show that the conceptual structure of etiquette formulas consists of functional-semantic fields like temporality, religiosity, marking conversation beginnings/endings. In Turkish, temporal concepts like “day” and “morning” are most frequent, while in Arabic religious concepts like “Allah” and “peace” prevail. Similarities include polite treatment of interlocutors, adherence to religious traditions, and hospitality. Differences lie in the degree of metaphoricality, imagery, and extended responses. The conclusions form ideas about the interrelations between core and peripheral linguacultural concepts, linguistic diversity, and invariance of etiquette formulas, their cognitive representation and role in shaping linguistic personality. The study contributes to understanding national mentality through the analysis of speech formulas.
Development of a Laboratory Test Apparatus for Simulating Core Drilling under High In Situ Stress
Authors: Rong Guan , Chen Zhiheng , Li Bowen , Liu Ruotao , Xu Lida
Published: October 2023

Rock cores drilled under high in situ stress environments are inevitably permanently damaged due to the stress relief, which significantly affects the evaluation of the physical and mechanical properties of deep rocks. Quantitatively correlating this sampling damage with in situ stress distribution is challenging because of the complexity of the geological environment and the diversity of rock materials. To address this challenge, a laboratory test apparatus has been developed that can apply specific pressure to shallow rock materials to simulate high in situ stress environments and drilling–coring to simulate the sampling process of deep rock masses. The results of verification tests demonstrate that the integrity of cores gradually deteriorated as the sampling confining pressure increased. Moreover, simultaneous increases in the density and size of microcracks were observed within the cores, where these microcracks propagate through grain boundaries, generate intragrain and transgranular microcracks, extend outwardly to form macroscopic cracks, and enhance porosity. These findings confirm the applicability of the apparatus for conducting quantitative sampling damage studies. In the future, further investigations using the apparatus will be conducted to explore the mechanical attenuation patterns of rock cores, thereby providing a reference to evaluate rock mechanics parameters for engineering practices.
Carbon Sequestration Capacity of Stabilized Soft Clays with Recycled Binders
Authors: Dejenie Bruk Belay , Raghuram Ammavajjala Sesha Sai , Korkiala-Tanttu Leena , Forsman Juha , Gustavsson Henry
Published: October 2023

This study estimates the CO2 sequestration capacity of Malmi clay stabilized with various recycled binders tested in laboratory conditions. Carbonation experiments were performed on stabilized samples using an autoclave and a carbonation chamber. Results revealed that the rate of carbonation differs significantly when carbonation is performed using a carbonation chamber or an autoclave. After 1 day in room temperature, the carbonated-stabilized samples were kept in the carbonation chamber for 13 days or in the autoclave for 5 days. Additionally, the reference samples were cured for 14 and 28 days to estimate the effect of CO2 sequestration capacity on curing time. Further, thermogravimetric analysis (TGA) was used to measure the CO2 intake. The findings indicated that the CO2 sequestration capacity of carbonated-stabilized soil for the recycled binders ranged from 2.8 % to 4.1 % of dry mass of the mixture. The CO2 intake was found to be 4.1 %, 3.5 %, 3.0 %, and 2.8 %/dry mass of the mixture for cement type I (CEMI), cement type III (CEMIII), GTC (gypsum + slaked lime + CEMIII), and biomass fly ash + CEMII (BFA + CEMII) stabilized clay, respectively. Ultimately, GTC binder was found to have the greatest potential to be carbon negative. The present study shows that it may be potential to create stabilization technique, which can be carbon negative especially by using recycled binder materials.
Photoredox-catalyzed reaction as a powerful tool for rapid natural product Gem-dimethylation modification: discovery of potent anti-cancer agents with improved druggability
Authors: Zhang Chao , Song Yugang , Sun Xiuyun , Liu Qianlong , Li Zhen , Yin Shenyi , Xi Jianzhong Jeff , Zhai Xin , Rao Yu
Published: October 2023

Tylophorine has diverse biological activities; however, the stability, solubility, and central nervous system toxicity have severely limited use of tylophorine. The gem-dimethyl group is an organic chemistry functional group that consists of two methyl groups bonded to the same carbon atom. This feature has gained significant attention in medicinal chemistry due to its unique properties and potential applications in drug design. We applied a new photoredox methodology to tylophorine modification, resulting in a series of gem-dimethyl tylophorine analogues. Among the analogues, compound 4b demonstrated promising activity against a wide range of tumor cell lines and exhibited significantly improved drug-like properties, including enhanced solubility and stability. Compound 4b showed an exceptional inhibitory effect (7.8 nM) against a C481S mutation-induced ibrutinib-resistant non-Hodgkin’s lymphoma cell line, as well as primary tumor cell lines obtained from patients. Importantly, compound 4b exhibited significantly reduced anti-proliferative activity against the normal cell line tested, indicating the potential for an enhanced therapeutic window for compound 4b. Based on these early-stage data, we believe that our study provides a solid foundation for the development of new therapeutic agents for potential drug-resistant cancer treatment in the near future.
Nuevos escenarios y retos en seguridad y defensa para las Fuerzas Armadas de Colombia
Authors: Fernández-Osorio Andrés Eduardo , Moreno-Peláez Jesús Eduardo , Bahamón-Jara Martha Lucía , Villalba-García Luisa Fernanda
Published: October 2023

Los cambiantes y complejos tiempos de un mundo cada vez más globalizado generan permanentemente nuevos escenarios y retos en la seguridad de los Estados que son generalmente asumidos por las Fuerzas Armadas. Sin embargo, la vertiginosa progresión del crimen transnacional exige una comprensión novedosa de las estrategias multidimensionales requeridas para su mitigación, así como una cuidadosa evaluación de su efectividad. Así las cosas, este artículo examina, para el caso colombiano, el avance hacia la consolidación de un país en paz y tranquilidad empleando las variables “limitación efectiva del conflicto armado”, “control efectivo del crimen”, y “búsqueda de justicia por mano propia” recopiladas por el Proyecto de Justicia Mundial. Se concluye que, aunque los datos muestran avances en algunos aspectos que fortalecen la gobernabilidad y el Estado social de derecho, solamente a través del empleo de la “Acción Unificada” Colombia podrá sortear las amenazas emergentes que impiden alcanzar los intereses nacionales y la reconciliación entre los ciudadanos.
Efficiency of the Implementation of Innovation and Investment Projects at Healthcare Institutions: Integral Analysis and Ways of Enhancement
Authors: STAHIV O. , BILETSKA I. , PEREPOLKINA O. , AVGUSTYN R. , MYKYTYN O.
Published: October 2023

Introduction. Improving the quality of medical services and raising the effectiveness of the operation of the subjects of the medical system of Ukraine requires intensifying innovation, which needs significant investments. So, the application of qualitative methods for analyzing the efficiency of such projects is of great importance.Problem Statement. Scholarly research and methodological framework and practical recommendations deal with the identification of problem areas and aspects of the implementation of innovation and investment projects at healthcare institutions in Ukraine.Purpose. The purpose is to comprehensively analyze and to identify the problematic aspects of the implementation of innovation and investment projects by healthcare institutions and to determine the measures to address them as well as to increase the effectiveness of the innovation.
Material and Methods. In the course of the study, the method of economic and mathematical modeling has been used to perform a composite analysis (using the weighted average method) of the effectiveness of the implementation of innovation and investment projects by the example of healthcare institutions.Results. It has been established that the efficiency of the implementation of innovation and investment projects at healthcare institutions of Ukraine is satisfactory, but such components as the financial and economic sustainability of the project and the quality of intellectual and personnel support, especially the structure of investments and their profitability, staff turnover and the level of professional qualification of medical personnel remain problematic. Financial and economic stability and investment andmarketing development remain the most problematic components of the efficiency.Conclusions. One of the key signs of the efficiency of investment and innovation projects in medicine is their systematic manner that involves a combination of measures to activate and develop investment and innovation in the organizational and institutional (1), the economic (2), the product and service (3), the social and psychological (4) components.
Test conditions of texture profile analysis for frozen dough
Authors: Dou Xinlai , Lv Mingshou , Ren Xuyang , He Yinyuan , Liu Linlin , Zhang Guang , Sun Ying , Zhang Na , Chen Fenglian , Yang Chun hua
Published: October 2023

Wheat flour is very important for making frozen dough. This paper firstly conducted an analysis of the basic properties of six varieties of wheat flour from different places and found that the variety BDHhgwf is most suitable to make frozen dough. Texture profile analysis (TPA) has been implemented in the dough-based food industry, and the properties of frozen dough were firstly investigated in this study. The results showed during TPA determination process of frozen dough, the variation of test parameters have an influence on the final result to some extent. The use of TPA in assessing the properties of frozen dough is presented. The recommended test conditions are: pre-test speed 3.0 mm/s, test speed (TS) 1.0 mm/s, posttest speed 1.0 mm/s, and compression ratio (CR) 50%. In a word, in this test method, the variation coefficient of dough was smaller and the dough was destroyed less by the texture analyzer and can truly reflect the texture of frozen dough.
Obraz Matki Bożej Róży Duchownej w kościele parafialnym w Jadownikach. Przyczynek do badań
Authors: Tadeusiak Witold
Published: October 2023

Od XV wieku w Jadownikach koło Brzeska znajduje się obraz Matki Bożej z Dzieciątkiem, nawiązujący stylem do Hodegetrii Krakowskich. Prawdopodobnie został namalowany przez Mistrza Zwiastowania z Jodłownika. Obraz ten przynajmniej między XVII a XIX wiekiem był otaczany lokalną czcią parafian, którzy wierzyli, że jest on wizerunkiem „niosącym łaski”. Niestety, w XX wieku pamięć o jego czci całkowicie zanikała, a po rozebraniu drewnianego kościoła parafialnego, w którym był przechowywany w głównym ołtarzu, został przeniesiony w 1910 roku do oddzielnej bocznej kaplicy w nowo wybudowanej świątyni. Po konserwacji wizerunku w latach 60. i zdjęciu XIX-wiecznych przemalunków, został przez wielu parafian uznany za fałszywy. Z czasem zaginęły również srebrne korony i pozostałe wota, świadczące o lokalnym kulcie. Kaplica zaś stała się miejscem przechowania po prostu kolejnego obrazu ze starego kościoła. Dzięki sięgnięciu do dawnych wizytacji biskupich i kapitulnych z czasów, kiedy Jadowniki były częścią diecezji krakowskiej, oraz naukom związanym z historią średniowiecza, dawno zapomniana historia odżywa, wzmagając lokalny kult Matki Bożej Róży Duchownej z Jadownik i odkrywając przed wiernymi historię ich własnej parafii.
The effects of deficit irrigation on water use efficiency, yield and quality of drip-irrigated tomatoes grown under field conditions in Zimbabwe
Authors: Godfrey Muroyiwa  , Emmanuel Mashonjowa  , Teddious Mhizha  , Maud Muchuweti
Published: October 2023

Water availability in the root zone directly affects the yield and quality of tomatoes yet in most cases in sub-Saharan Africa water is either expensive or scarce. It is therefore important to establish and utilise suitable irrigation strategies in order to produce the crop in a sustainable way. In this study the effect of conventional and deficit irrigation treatments on yield, fruit quality and water use efficiency (WUE) were determined. Four trials were conducted at the University of Zimbabwe Farm from 2014-2017 with four treatments per trial: T1 = 100%, T2 = 80%, T3 = 60%, and T4 = 50% of crop water requirements (ETc). Treatments had equal number of plants per trial with an in-row plant spacing of 0.3 m and 0.5 m between adjacent rows. ETc was determined daily for each treatment and the corresponding volume applied through one drip emitter per plant. Fruits from each treatment were gathered while ripening and the total yield obtained.  WUE was calculated by dividing the total fresh yield by total irrigation water applied. Maximum yield was obtained where 100% ETc was applied, with no significant difference between yield of plants at 80% and 60% ETc, except in 2016. Yield decreased with 50% ETc in 2014, 2015, and 2017 with no significant difference in yield between 60% and 50% ETc treatments in 2016. The 2015 season recorded the highest yield when compared to other trials showing that we can save 40% of water resulting in high WUE with minimum loss in yield. Deficit irrigation reduced fruit water but increased fruit soluble solids (°brix), vitamin C and fruit acid concentrations. Firmness was best when 60% ETc was applied. These results show that deficit irrigation is feasible for crop water management options for the production of high-quality field-grown tomatoes without major yield reductions.
A baseline study on the prevalence of microplastics in South African drinking water: from source to distribution
Authors: Annelie Swanepoel  , Hein du Preez  , Henk Bouwman
Published: October 2023

Due to the worldwide increasing prevalence of microplastics in the aquatic environment, this study aimed to perform a screening of the source and drinking water of South Africa’s largest bulk drinking water supplier to determine the extent to which microplastics occur in the water. Source water samples, samples immediately after treatment, and samples in the distribution network (Johannesburg, Mabopane, Garankua and Pelindaba) were analysed. Microplastics concentrations in the source water ranged from 0.24 to 1.47 particles/L, immediately after treatment from 0.56 to 0.9 particles/L, and in the distribution network from 0.26 to 0.88 particles/L. Most of the microplastics found in the water were classified as ‘fragments’ and a few as ‘fibres’. The control sample (indicating contamination during sample preparation and analysis) showed 0.34 particles/L, which was higher than some of the samples taken, indicating very low microplastics concentrations in these samples. Little evidence was found that the drinking water treatment processes reduced the number of microplastics from the source to the final treated water. No evidence could be found that the pipes in the distribution network contribute to microplastics in the tap water. The most frequently found polymer in the samples was rubber. Based on mass, however, as a function of particle size and polymer density, ethylene-vinyl-acetate (a polymer commonly used as foam in sporting equipment and flip-flops) comprised 54% of the microplastics and polyethylene (standard and chlorinated) 25%.
Cape Town residents’ willingness to pay for a secure and ‘green’ water supply
Authors: JK Turpie  , GK Letley
Published: October 2023

The City of Cape Town experienced a serious drought between 2016 and 2018 which led to severe water shortages and concerns for the environment. This study took advantage of a period of unprecedented levels of awareness about water security in order to investigate households’ willingness to pay (WTP) for reliable water supply and their WTP to avoid environmental damages in securing this supply. Increasing the supply of water from dams and groundwater will ultimately impact on aquatic ecosystems, but alternatives are more expensive. We surveyed 248 households from 105 suburbs and used contingent valuation methods to investigate WTP for both secure and less damaging or ‘greener’ ways of supplying water. Depending on income level, households were willing to pay 63–127% more for their normal levels of consumption in order to have security of supply, and a further 35–68% more to ensure its environmental sustainability.  Based on the relationship between WTP for 7 income categories, the overall WTP for secure water supply under non-drought conditions amounted to some 2.8 billion ZAR/year, which is about 90% higher than pre-drought revenues.  Aggregate WTP for securing this supply using options that ensured the protection of the region’s rivers and estuaries was 3.3 billion ZAR. These results have an important bearing on water investment and pricing decisions over the longer term.
Endogenous irrigation in arid Zimbabwe: farmer perceptions of livelihood benefits and barriers to scaling
Authors: Moline Chauruka  , Annelieke Duker  , Pooja Prasad  , Pieter Van der Zaag
Published: October 2023

In Zimbabwe, farmer-led irrigation is far more widespread than planners and policy makers realise. Along the Shashani sand river, in the arid to semi-arid lands of south-western Zimbabwe, diverse farmer-initiated irrigation ventures exist. This qualitative case study focuses on bucket irrigation, in which very small vegetable fields of up to 450 m2 are fenced by tree branches, and irrigated with water from scoop holes in sandy river beds. Farmers initiate and operate their fields with no external assistance. This study presents the benefits of bucket irrigation as an often-overlooked form of farmer-led irrigation development. Through this qualitative and strongly observational study, 26 bucket irrigation farmers and 4 non-irrigators were interviewed using semi-structured interviews where farmers’ perceptions and experiences were captured. We investigate what drives and sustains bucket irrigation, its significance to rural livelihoods under harsh economic and climatic conditions, and the barriers towards scaling this type of farmer-led irrigation development. The results show that drivers for bucket irrigation stem from economic hardship and are gendered. Women are motivated to irrigate mainly by the need to produce vegetables for household consumption, whereas men pursue irrigation due to a lack of employment. Bucket irrigators experience enhanced food security, and have more secure income, contributing to improved wellbeing. Furthermore, despite the desire to scale, the farm size is mainly constrained by fencing and energy for transporting water, which is a result of a persistent lack of financial capital to invest in irrigation technologies. We conclude that bucket irrigation acts as an important livelihood strategy, and that it significantly enhances farmers’ resilience to economic and climatic shocks.  Bucket irrigation should not be overlooked in policies that advocate scaling of irrigation. Bucket irrigators have the potential to expand and benefit significantly if supported with innovative financial mechanisms that enable investments in the required technology and knowledge.
Occurrence of multidrug-resistant Escherichia coli and antibiotic resistance genes in a wastewater treatment plant and its associated river water in Harare, Zimbabwe
Authors: Hilary Takawira  , Joshua Mbanga
Published: October 2023

Wastewater treatment plants (WWTPs) have been identified as point sources of antibiotic-resistant bacteria (ARB) and antibiotic-resistance genes (ARG). Due to variations in antibiotic use and prescribing patterns in different countries, it is imperative to establish the presence of ARB and ARGs in water environments on a country-by-country basis. This study investigated the occurrence of 11 antibiotic-resistance genes (QNRB, DFR14, CTX-M, KPC, Sul1, QNRA, Sul2, ERMB,  ERMA, SHV, NDM), and antibiotic-resistant Escherichia coli in a WWTP and its associated river water in Harare, Zimbabwe. 24 water samples were collected across 3 sites: upstream and downstream of the WWTP; final effluent of the WWTP. The samples were collected weekly for 8 weeks. Pure cultures of the E. coli isolates were obtained by membrane filtration (0.45 µm) and repeated streaking on Tryptone Bile X-glucuronide followed by biochemical tests (indole test; citrate test; motility, indole, and ornithine). Antibiotic resistance profiling was done for 12 antibiotics using the disc diffusion method. Total genomic DNA was extracted from the 21 water samples and the occurrence of 11 antibiotic-resistant genes investigated using conventional PCR. 86 E. coli isolates were obtained from the sampled sites: 28 from the upstream site, 26 from the WWTP effluent, and 32 from the downstream site. The results from chi-squared analysis showed a significant association (p < 0.05) between the sampling site and the percentage of antibiotic-resistant E. coli for all 12 antibiotics investigated. The percentage of E. coli isolates resistant to the tested antibiotics varied from 29% (ertapenem) to 80.2% (ciprofloxacin). 81 (94.2%) E. coli isolates were resistant to antibiotics from ≥3 classes.  Eight (8/11, 72.7%) ARGs were detected in the WWTP effluent and river water samples. Results indicate that the investigated WWTP and associated river water are reservoirs of ARGs and antibiotic-resistant E. coli, which is a public health concern.
Сила ненасилия: Сцепка этики и политики
Authors: Батлер Джудит
Published: October 2023

В своей новой книге Джудит Батлер доказывает, что этика ненасилия должна связываться с широкой политической борьбой за социальное равенство. Один из современных вызовов, с которыми сталкивается политика ненасилия, сводится к существованию расхождения во мнениях о том, что считать насилием и ненасилием. Батлер утверждает, что ненасилие часто ошибочно принимают за пассивную практику или за сосуществование с властью, но на самом деле ненасилие — этическая позиция, находящаяся в самой гуще политического поля. Если рассматривать ненасилие как этическую проблему в рамках социальной и политической философии, то потребуется осуществить критику индивидуализма, а также понять психосоциальный аспект насилия. Агрессивная форма ненасилия принимает то, что враждебность — составная часть нашего психического устройства, но она также ценит амбивалентность как способ предотвращения перерастания агрессии в насилие. Книга адресована философам, социологам, политологам, культурологам и тому кругу читателей, кому интересно знать, что сегодня происходит в современной социальной и политической философии.
Friction stir-welding of AZ31B Mg and 6061-T6 Al alloys optimization using Box-Behnken design (BBD) and Artificial Neural network (ANN)
Authors:   Dept. of Mechanical Eng., College of Eng. and Technology, Wollega University, Nekemte, Ethiopia, Efa Dame Alemayehu , Gutema Endalkachew Mosisa ,   Dept. of Mechanical Eng., College of Eng. and Technology, Wollega University, Nekemte, Ethiopia, Lemu Hirpa G. ,   Dept. of Mechanical and Structural Eng. and Materials Science, Faculty of Science and Technology, University of Stavanger, N-4036 Stavanger, Norway, Gopal Mahesh ,   Dept. of Mechanical Eng., College of Eng. and Technology, Wollega University, Nekemte, Ethiopia
Published: October 2023

The primary goal of the study is to optimize the welding parameters using Friction Stir Welding (FSW) to join AZ31B Mg and AA 6061 alloys considering input parameters such as rotational speed, welding speed, shoulder-to-pin diameter ratio and plunge force and output parameters as peak temperature. The simulation experiment is carried out using COMSOL Multiphysics® 6.0 Software. The simulation experiment is designed using the Box-Behnken design (BBD) of Response Surface Methodology (RSM) and mathematical models were developed. The Analysis of Variance (ANOVA) is used to assess the features of the performance effectiveness of the parameters. Both direct and indirect interaction effects are investigated; the results indicate that the rotational speed is the most influential parameter when compared to other factors; as rotational speed increases consequently; there is an increase in temperature. Finally, the Artificial Neural Network was trained and tested in MATLAB software to optimize the parameters. The validation was performed to predict the minimal predicted temperature value. The confirmatory tests reveal that the predicted results are extremely close to the experimental values from the simulation.
CEP-DTHP : A Complex Event Processing using the Dual-Tier Hybrid Paradigm Over the Stream Mining Process
Authors: Panpaliya Mayur , Ranjan Nihar , Algude Arun
Published: October 2023

CEP is a widely used technique for the reliability and recognition of arbitrarily complex patterns in enormous data streams with great performance in real time. Real-time detection of crucial events and rapid response to them are the key goals of sophisticated event processing.  The performance of event processing systems can be improved by parallelizing CEP evaluation procedures. Utilizing CEP in parallel while deploying a multi-core or distributed environment is one of the most popular and widely recognized tackles to accomplish the goal. This paper demonstrates the ability to use an unusual parallelization strategy to effectively process complicated events over streams of data. This method depends on a dual-tier hybrid paradigm that combines several parallelism levels. Thread-level or task-level parallelism (TLP) and Data-level parallelism (DLP) were combined in this research. Many threads or instruction sequences from a comparable application can run concurrently under the TLP paradigm. In the DLP paradigm, instruc-tions from a single stream operate on several data streams at the same time. In our suggested model, there are four major stages: data mining, pre-processing, load shedding, and optimization. The first phase is online data mining, following which the data is materialized into a publicly available solution that combines a CEP engine with a library. Next, data pre-processing encompasses the efficient adaptation of the content or format of raw data from many, perhaps diverse sources. Finally, parallelization approaches have been created to reduce CEP processing time. By providing this two-type parallelism, our proposed solution combines the benefits of DLP and TLP while addressing their constraints. The JAVA tool will be used to assess the suggested technique. The performance of the suggested technique is compared to that of other current ways for determining the efficacy and efficiency of the proposed algorithm.
Enhancing Data Security in Healthcare IoT: An Innovative Blockchain-based Solution
Authors: Patel Ochchhav , Patel Hiren
Published: October 2023

The Internet of Things (IoT) has revolutionized the healthcare industry by enabling the seamless integration of medical devices, sensors, and data-driven applications. However, the large influx of sensitive healthcare data and the proliferation of linked devices have caused grave worries about data security and privacy. Traditional centralized security systems are unable to handle the changing threats and problems in the IoT healthcare setting. This study suggests a novel strategy for boosting data security in the healthcare industry that makes use of blockchain technology. The main goal of this research is to develop and deploy a trustworthy framework that safeguards private healthcare information in IoT networks. Blockchain, as a distributed and decentralized ledger, offers inherent security features such as immutability, transparency, and cryptographic mechanisms. In this research, it is suggested that healthcare data be gathered via the IoT and stored in the Interplanetary File System (IPFS) using Ethereum-based blockchain technology for data security. The suggested method creates a reliable environment for managing healthcare data by exploiting the special features of blockchain. The json and jpeg files are utilized five times on a distributed database housed on IPFS and a centralized database hosted on Firebase, and the upload and download times are recorded. For IoT-based healthcare systems, we have also investigated the cost and length of time required to implement smart contracts on blockchain platforms like Rinkeby, Binance, and Matic. This research suggests implementing the Blockchain platform in an IoT-based healthcare system to provide data confidentiality, integrity, and accessibility.
Classification of Atrial Fibrillation using Random Forest Algorithm
Authors: G. C. Suguna , Shirahatti Sunita , Bangari Sowmya R. , S. T. Veerabhadrappa
Published: October 2023

The electrocardiogram is indicates the electrical activity of the heart and it can be used to detect cardiac arrhythmias. In the present work, we exhibited a methodology to classify Atrial Fibrillation (AF), Normal rhythm, and Other abnormal ECG rhythms using a machine learning algorithm by analyzing single-lead ECG signals of short duration. First, the events of ECG signals will be detected, after that morphological features and HRV features are extracted. Finally, these features are applied to the Random Forest classifier to perform classification. The Physionet challenge 2017 dataset with more than 8500 ECG recordings is used to train our model. The proposed methodology yields an F1 score of 0.86, 0.97, and 0.83 respectively in classifying AF, normal, other rhythms, and an accuracy of 0.91 after performing a 5-fold cross-validation.
Review of the State of the Art of Transfer Learning for Plant Leaf Diseases Detection
Authors: Koli Sakshi , Rastogi Ritesh , Gehlot Anita , Singh Rajesh , Joshi Kapil , Priya Priya
Published: October 2023

Plant leaf diseases can have a significantly negative influence on the quantity and quality of agricultural cultivation, as well as the safety of food production. Plant leaf diseases could potentially entirely prevent the harvest of grains in some situations. Therefore, it is extremely important from a pragmatic standpoint to look for quick, automatic, cheap, and accurate ways to detect plant leaf diseases. One of the well-known plant leaf disease detection approaches is deep learning. Deep learning has several drawbacks as a result of the huge amount of data required to train the network. When a dataset has inadequate photographs, performance falls. An approach called "Transfer Learning" is an extensively used method for addressing the shortcomings of a small dataset, the length of the training process, and improving the performance of the model. In this study, we investigated transfer learning for deep CNNs to improve the learning capability to recognize leaf disease. This survey focuses on categorizing and analyzing the recent developments in transfer learning for Deep CNN situations to enhance learning performance by reducing the need for extensive training data collecting.
Survey and Review on Various Topology and Geographical based Routing Protocol Parameters to Ensure the QOS Parameters of VANET
Authors: Ahamed V. M. Niaz , K. Sivaraman
Published: October 2023

Vehicular Ad Hoc Network (VANET) is a type of wireless network that allows communication between vehicles and infrastructure. One of the critical considerations in VANET is Quality of Service (QoS) parameters, which determine the network's performance. The effective management of QoS parameters is essential for VANET's reliable and efficient operation. In this research paper, we aim to explore topology-based and geographical-based routing protocol parameters to ensure QoS parameters in VANET. The former uses the network topology to make routing decisions, while the latter uses the location information of vehicles.  We will first provide an overview of VANET and QoS parameters. Then, we will delve into the key parameters of topology-based and geographical-based routing protocols and how they affect QoS. We will also survey and review the existing routing protocols and parameter values used in these protocols. The findings of this research paper will provide insights into the effective management of QoS parameters in VANET and contribute to the development of more efficient routing protocols.
Sentiment Analysis and Classification on Amazon Products using Improved Support Vector Machine for Multiclass Classification
Authors: Geethanjali D. , Suresh P.
Published: October 2023

There is a huge increase in number of peoples who have been accessing many social networking sites especially user post or reviews for a specific product, company, brand, individual, forums and movies etc. These reviews are helpful in judging customer perception on certain thing. The development of algorithms that could automate the categorization of distinct comments based on feedback from consumers became an analyst project, and this automated classification process is known as sentiment analysis. This research main goal is to analyze Amazon product reviews using an approach to Machine Learning (ML) built around TF-IDF and then employ the Support Vector Machine (SVM) algorithm to categorize the sentiment scores and sentences. SVM can handle binomial classification but the customer reviews is mostly classified into positive, negative and neutral and in some applications, it is fine grained into star ratings such 1-5 or sometimes 1-10. Also, in some applications features or attributes are high in number in which some are irrelevant. Hence, this work applies feature subset algorithm and improves the existing SVM to handle multiclass classification. The Sentiment analysis, Rapidminer tool is considered for classification and the results are visualized, assessed with suitable classification metrics.
Implementation of Intelligent Smart Heart Health Monitoring System using IOT
Authors: Sudhakar M. Venkata , Kandula Srinivasa Rao , Teju V. , Sowmya K. V. , Aruna Vipparla , Sharief Abdul Hussain , Seelam Koteswararao
Published: October 2023

There are a lot of severe diseases that are associated with humans, but one of them is cardiac arrest, which, in general terms, we call a heart attack. The already existing heart rate monitoring systems are not mobile, are expensive, and take a little longer to give out the results. So, in this work, we will go for a system called Heart Rate Monitoring system using an ECG sensor and a Raspberry Pi, which actually represents the acquisition and interpretation of a human heart’s data collected with the help of sensors, anywhere and everywhere on the earth, through IOT. We generally consider heart rate while noting the status of the heart, but the oxygen level and body temperature also play a major role in determining the exact heart status. So, the hardware required to implement this heart rate monitoring model consists of different health sensors and a Raspberry Pi configured in a way to communicate with the guardian and the respective doctors over the Internet through an available smart mobile phone. In this work, the sensors configured with the hardware collect the required information about the patient’s health, which includes parameters such as the patient’s heart rate, body temperature, and SPo2 levels. Then, using the collected information from the sensors, the patient’s heart activity is actively observed. Thus, the patient himself or herself can easily identify his or her heart condition with the help of collected data anywhere on the earth through the internet. An alert indicating that their heart status is not good is displayed to the caretakers on the mobile, which shows a message called "abnormal condition to the patient" given the condition that the collected sensors’ values are beyond the threshold information through the GSM module, and also the GPS location of the patient will be sent to the caretakers as well as to the doctors.
Custom Deep Learning Model for the Diagnosis of Cervical Carcinoma
Authors: Kamaraj Abinaya , Bangar Sivakumar
Published: October 2023

Cancer is the second most common cause of death in the majority of the world due to late diagnosis. Most cancer cases are typically discovered at an advanced stage, which lowers the likelihood of recovery because proper therapy cannot be given at that time. In particular, for incurable cancers, which may result in a reduced life expectancy due to the rapid progression of the disease, the sooner cancer is identified, the more effective the therapy may be. Early detection also lessens the financial effects of cancer because treatment in the early stages is much cheaper than treatment in later stages.The method suggested is an end-to-end deep learning method in which the input photos are sent directly to the deep model, which makes the decision. The proposed Ensemble of deep learning modelIV3-DCNN to detect cancer in pap-test images. The model's precision, FScore, Specificity, Sensitivity, and accuracy of 99.4%, 99.23, 95.48, 97.9, and 99.2%. Last but not least, the suggested strategy would be very beneficial and successful, especially in low-income nations where referral mechanisms for patients with suspected cancer are frequently lacking, resulting in delayed and fragmented care.
A Critical Evaluation of Business Improvement through Machine Learning: Challenges, Opportunities, and Best Practices
Authors: Gadekar Bhagyashree , Hiwarkar Tryambak
Published: October 2023

This paper presents a critical evaluation of the impact of machine learning (ML) on business improvement, focusing on the challenges, opportunities, and best practices associated with its implementation. The study examines the hurdles faced by businesses while integrating ML, such as data quality, talent acquisition, algorithm bias, interpretability, and privacy concerns. On the other hand, it highlights the advantages of ML, including data-driven decision-making, enhanced customer experience, process optimization, cost reduction, and the potential for new revenue streams. Furthermore, the paper offers best practices to guide businesses in successfully adopting ML solutions, covering data management, talent development, model evaluation, ethics, and regulatory compliance. Through real-world case studies, the study illustrates successful ML applications in different industries. It also addresses the ethical and social implications of ML adoption and discusses emerging trends for future directions. Ultimately, this evaluation provides valuable insights to enable informed decisions and sustainable growth for businesses leveraging machine learning.
Machine Learning Techniques to Evaluate the Approximation of Utilization Power in Circuits
Authors: M. P. Varghese , Muthumanickam T.
Published: October 2023

The need for products that are more streamlined, more useful, and have longer battery lives is rising in today's culture. More components are being integrated onto smaller, more complex chips in order to do this. The outcome is higher total power consumption as a result of increased power dissipation brought on by dynamic and static currents in integrated circuits (ICs). For effective power planning and the precise application of power pads and strips by floor plan engineers, estimating power dissipation at an early stage is essential. With more information about the design attributes, power estimation accuracy increases. For a variety of applications, including function approximation, regularization, noisy interpolation, classification, and density estimation, they offer a coherent framework. RBFNN training is also quicker than training multi-layer perceptron networks. RBFNN learning typically comprises of a linear supervised phase for computing weights, followed by an unsupervised phase for determining the centers and widths of the Gaussian basis functions. This study investigates several learning techniques for estimating the synaptic weights, widths, and centers of RBFNNs. In this study, RBF networks—a traditional family of supervised learning algorithms—are examined.  Using centers found using k-means clustering and the square norm of the network coefficients, respectively, two popular regularization techniques are examined. It is demonstrated that each of these RBF techniques are capable of being rewritten as data-dependent kernels. Due to their adaptability and quicker training time when compared to multi-layer perceptron networks, RBFNNs present a compelling option to conventional neural network models. Along with experimental data, the research offers a theoretical analysis of these techniques, indicating competitive performance and a few advantages over traditional kernel techniques in terms of adaptability (ability to take into account unlabeled data) and computing complexity. The research also discusses current achievements in using soft k-means features for image identification and other tasks.
Mind Control Robotic Arm: Augmentative and Alternative Communication in the Classroom Environment
Authors: Murthy G. N. Keshava , H. Rekha , Mirajkar Riddhi Rajendra , F. Sammy , Deshmukh Yogesh Suresh , Mutkule Prasad Raghunath
Published: October 2023

In recent years, technological advancements have greatly benefited the field of prosthetics. A large number of disabled people depend on prosthetics because they are an important technology. In order to provide augmentative and alternative methods of communication to these disabled people with various neuromuscular disorders, we must make sure they are provided with appropriate equipment to express themselves. Different types of arms are evaluated under robotic technology in terms of resistance, usability, flexibility, cost, and potential (such as robotic, surgical, bionic, prosthetic, and static arms). The main problems with these techniques are their high cost, the difficulty of installing and maintaining them, and the possibility of requiring surgery may arise. As a result, this paper is going to provide a description of the idea for combining an EEG controlled smart prosthetic arm with a smart robotic hand. An electrode headset is used to capture the signals from the robotic hand in order to control the device. Creating a robot arm that can help disabled people lead a more independent life is the main objective of this paper.
Online Campus Recruitment System-A Machine Learning Model
Authors: Dubey Mithilesh Kumar , Narang Barkha
Published: October 2023

As the job market for college students heats up, firms are paying more attention to campus recruiting as the major way of employing college graduates. This research looks at the indicators and reasons for possible hazards for companies when recruiting on college campuses. Several measures are advised in the interim, which may assist organizations to decrease the hazards connected with campus recruiting and boost its success rate. Training and placement cell operations are expedited, and students are put in the most coordinated scenario feasible, all owing to the campus recruiting system. This promotes the aggregation of student knowledge to boost the selection rate and simplifies the process of automatically creating management data. The major purpose of online training and placement is to automate the placement cell. CV validation, advertising job vacancies to a student community, maintaining contact with companies to invite students to internships and other events, monitoring the selection process, and engaging with a broad variety of users.