Browse Items (16481 total)
Sort by:
-
COMPUTATION OF b-CHROMATIC TOPOLOGICAL INDICES OF SOME GRAPHS AND ITS DERIVED GRAPHS
The two fastest-growing subfields of graph theory are graph coloring and topological indices. Graph coloring is assigning the colors/values to the edges/vertices or both. A proper coloring of the graph G is assigning colors/values to the vertices/edges or both so that no two adjacent vertices/edges share the same color/value. Recently, studies involving Chromatic Topological indices that dealt with different graph coloring were studied. In such studies, the vertex degrees get replaced with the colors, and the computation is carried out based on the topological index of our choice. We focus on b-Chromatic Zagreb indices and b-Chromatic irregularity indices in this work. This paper discusses the b-Chromatic Zagreb indices and b-Chromatic irregularity indices of the gear graph, star graph, and its derived graphs such as the line and middle graph. 2023, RAMANUJAN SOCIETY OF MATHEMATICS AND MATHEMATICAL SCIENCES. All rights reserved. -
Compressive Sensing Based Compression Algorithm for the Audio Signal
Nyquist sampling is used in the conventional digital converter to convert the analog audio signal to digital audio data. Traditional approaches, such as Nyquist sampling, require high sampling rates, leading to large datasets. After sampling, the digital audio data is often compressed using algorithms like Moving Picture Experts Group Layer-3 Audio Coding (MP3), Advanced Audio Coding (AAC), or other codecs to re-duce the file size for storage or transmission. Recently, Compressive Sensing (CS) has been used instead of Nyquist Sampling. Instead of sampling at the Nyquist rate, Com-pressive Sensing samples the signal at a much lower rate. The recovery of the original signal from these fewer samples is possible through minimization techniques. Hence, in the proposed algorithm, we use Compressive Sensing for audio compression. The basis matrix for Compressive Sensing is generated by exploring different transform matrices. The proposed algorithm leverages the principles of Compressive Sensing to enhance audio compression by reducing the number of samples needed and using efficient recovery techniques, resulting in a high compression rate suitable for modern audio applications. 2025. -
Compression Based Modeling for Classification of Text Documents
Classification of text data one of the well known, interesting research topic in computer science and knowledge engineering. This research article, address the classification of text files issue using lzw text compression algorithms. LZW is a lossless compression technique which requires two pass on the input data. These two passes are treated separately as training stage and text stage for classification of text data. The proposed compression based classification technique is tested on publically available datasets. Results of the experiments shows the effectiveness of the proposed algorithm. 2019, Springer Nature Singapore Pte Ltd. -
Compressed unfired blocks made with iron ore tailings and slag
Growing demand for houses in urban India has increased the requirements for construction materials such as clay fired bricks and cement blocks. At the same time, conventional practice of brick manufacturing is not environment friendly due to high energy consumption and CO2 emissions during various stages of its production. Therefore, recent trend in research has been directed towards utilization of various industrial wastes and methods, which emerge as sustainable alternatives for environmental concerns arising in the construction industry. This study focused on utilizing mining waste, namely iron ore tailing (IOT) in development of stable blocks. It has reported various properties of compressed unfired blocks formed by IOT and ground granulated blast furnace slag (GGBS) in varying proportions and with a fixed amount of lime. The combination of GGBS and lime was found to be suitable in stabilizing IOT towards block production. Furthermore, a maximum compressive strength of 7.7 MPa was achieved for blocks after 28days of air curing. Also, the addition of GGBS has reduced the water absorption and apparent porosity of the IOT blocks, confirming the positive interaction between IOT, GGBS and lime. It also indicates the prospective of blended binders in improving the compactness of the blocks, which will have direct influence on the durability and service life of the blocks. Finally, the results show that most of the developed blocks satisfy the requirement of IS 1077 specification and can be used in various applications such as load and non-load bearing walls, framed structures, foundations and pedestrian walkways. 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Compressed Spatio Temporal Graph Neural Networks for Multivariate Time-Series Forecasting
Precise traffic flow forecasting is crucial for efficient transportation management and traffic congestion alleviation. Existing models typically fail to process the intricate spatial- temporal relationships in traffic data and thus incur compromised prediction performance. In this work, we introduce a Compressed Spatial-Temporal Enhanced Graph Neural Network (Comp-STEMGNN) to overcome these limitations. Our model combines 1D convolution-based temporal compression with graph neural networks to compress redundant time-series information without compromising vital patterns. Graph convolutional layers and temporal convolutional blocks extract the spatial and temporal relationships and facilitate efficient learning from enormous sensor networks. Experimental comparisons on benchmark traffic datasets show that Comp-STEMGNN outperforms existing approaches in forecasting accuracy while enjoying substantial computational complexity reduction. These findings identify its potential in real-time traffic forecasting and intelligent transportation systems. 2025 IEEE. -
Compressed Data Representation Methods for High-Speed Search
The current age of computing revolves around data; the ability to fetch and store large quantities of information has become imperative for systems such as embedded systems and even search engines. Methods of compressed data representation are vital, as they enable faster query execution while reducing the storage space needed. This paper has analyzed such methods. The authors have reviewed bitmap indexing, inverted index compression, succinct data structures, LZ-based schemes, and compressed tries based on the set criteria of practical usefulness, search performance, and space efficiency. Through qualitative metrics, the authors performed a comparative evaluation, which is then represented in a conceptual figure and through tables. Moreover, the paper analyzes potential use case scenarios in domains such as bioinformatics, log management, edge computing, and AI-powered search pipelines. Other issues that have been explored include a balance between compression and query latency, optimizing for heterogeneous hardware, encrypted data search, and searching through encrypted data. The findings illuminate previously unexplored areas of research, including learned indexing, adaptive compression, and searching with minimal energy expenditure. The Research Publication,. -
Comprehensive understanding of biomedical usages of metal and non metal doped carbon dots
In recent years, carbon dots have garnered significant attention, particularly within the biomedical realm, owing to their exceptional characteristics. The unique attributes of carbon dots can be further enhanced through the introduction of heteroatom via doping. Various techniques have been devised by researchers to facilitate the doping of carbon dots, with both metallic and non-metallic elements. Elements such as nitrogen (81%), sulfur (67%), and silicon (64.1%) have been successfully employed for doping carbon dots leading to heightened quantum yields. This review compiles the diverse methodologies and elements employed in doping of carbon dots, and their applications in the biomedical domain in recent times. This review discusses the uses of doped carbon dots, both metal and non-metal-doped variants, elucidating their manifold utilities in various biomedical sectors, notably bioimaging, wound healing, and cancer therapy. The discussion culminates by addressing present challenges and offering insights into future prospects of doped carbon dots. 2023 Elsevier Ltd -
Comprehensive transcriptomic and functional characterization of protoplast regeneration in Angelica gigas Nakai
Background: Protoplasts that are isolated from various plant sources, including leaf mesophyll tissue, callus, will continue to have the ability to take part in cell wall regeneration, division, and expression of totipotency. In model systems like Arabidopsis thaliana, it has been thoroughly established. Meanwhile, the fate of protoplasts isolated from both embryogenic (EC) and non-embryogenic callus (NEC) in other plants is unknown. Thus, we conducted transcriptome analyses of protoplasts produced from both EC and NEC in Angelica gigas in the present investigation. To achieve this, three stages of RNA sequencing were carried out: (1) EC, (2) freshly isolated protoplasts (Pt), and (3) cells undergoing cell division (CD) during A. gigas in vitro protoplast regeneration. Different gene expression programs were identified across stages through transcriptome profiling, which highlighted early stress responses, transcriptional changes, and the acquisition of stem cell identity following protoplast isolation. Results: A pre-existing stem cell-like condition was shown by the strong expression of WUSCHEL-RELATED HOMEOBOX5 (WOX5) and CUP-SHAPED COTYLEDON2 (CUC2) genes at the EC stage. Important genes linked to stress reactions and cellular transcriptional changes, as WOX13 and WOUND INDUCED DEDIFFERENTIATION1 (WIND1), were significantly elevated at the Pt stage. Additionally, during this phase, genes associated with the cell cycle, auxin and cytokinin signaling, and cell wall regeneration were also active, indicating a dynamic shift toward regaining stem cell identity. Key regulators of stem cell maintenance and proliferation, such as LATERAL ORGAN BOUNDARIES DOMAIN16 (LBD16) and ENHANCER OF SHOOT REGENERATION2 (ESR2), were then substantially expressed at the CD stage, encouraging the start of cell division. The dynamic regulation of embryogenesis-related genes, including SOMACTIC EMBRYOGENESIS RECEPTOR-LIKE KINASE 2 (SERK2), LBD29, ESR2, LBD16, D-TYPE CYCLINS (CYCD3-2), and WOX1, during protoplast culture was validated by real-time quantitative polymerase chain reaction (RT-qPCR). Conclusions: WOX5 and CUC2 genes were found to be significantly expressed at the EC stage, suggesting a pre-existing stem cell-like state. Important genes linked to stress reactions and cellular transcriptional changes, as WOX13 and WIND1, were clearly elevated at the Pt stage. The activation of genes linked to cell wall renewal, auxin and cytokinin signaling, and the cell cycle during this phase also suggested a dynamic transition toward regaining stem cell identity. Additionally, the findings previously reported show that the EC-derived protoplasts successfully underwent cell division and contributed to the development of somatic embryos. Although the NEC-generated protoplasts did not divide upon culture, these results show that embryogenic cells maintain their embryogenic potential even after protoplast isolation and culture. The Author(s) 2026. -
Comprehensive study on using hydrogen-gasoline-ethanol blends as flexible fuels in an existing variable speed SI engine
The rising human population is causing the utilization of enormous amounts of fossil fuels to fulfill energy needs. Various renewable sources are used as fossil fuels however those resources are not powerful in supplanting customary non-renewable energy sources like gasoline in vehicles. The depletion of conventional fossil fuel utilized in a vehicle contributes to an increased portion of air contamination and is a danger to human well-being. Also, to maintain the supply demand, many active types of research have been carried out in mixing a higher percentage of ethanol over gasoline and further moving towards flex-fuel vehicles. But there arises a problem of knocking and higher CO, and HC emissions from the engine. To overcome the above problem, ethanol could be mixed in a higher percentage over gasoline with the help of hydrogen assistance and can completely avoid the problem of knocking and reducing CO and HC emissions. In this research, the combustion, emission, and performance characteristics of a variable-speed gasoline engine fuelled with ethanol-blended gasoline along with hydrogen assistance are taken for investigation at variable speeds like 1800, 1600, 1400, and 1200 rpm. Hydrogen is added to blended fuel (E30) which has better combustion, emission, and performance than other blended fuels. Hydrogen addition is done at 2, 3, and 4 ms respectively. The outcomes showed that the E30 + H2 at 3 ms has better combustion, emission, and performance, still, the emission of NOx is higher in comparison with all the other blends due to complete combustion. Thus, a two-stage analysis has been done, one is making a comparison among various blends of ethanol, and the second one is the comparison among the various energy shares of hydrogen. 2023 Hydrogen Energy Publications LLC -
Comprehensive Study on Sentiment Analysis: Types, Approaches, Recent Applications, Tools and APIs
Sentiment analysis can be considered a major application of machine learning, more particularly natural language processing (NLP). As there are varieties of applications, Sentiment analysis has gained a lot of attention and is one among the fastest growing research area in computer science. It is a type of data analysis which is observed from news reports, user reviews, feedbacks, social media updates etc. Responses are collected and analyzed by researchers. All sentiments can be classified into three categories-Positive, Negative and Neutral. The paper gives a detailed study of sentiment analysis. It explains the basics of sentiment analysis, its types, and different approaches of sentiment analysis. The recent tools and APIs along with various real world applications of sentiment analysis in various areas are also described briefly. 2020 IEEE. -
Comprehensive study of the relationship between multiverse and big data
Studies linking two broader spectra of topics have fascinated scholars in many aspects. Here we tried associating two such far-reaching aspects which have finite connectivity between them. Multiverse has been the talk of the hour which explains the theory of multiple universes which exist in parallel. This is a topic in physics concerned with many relative matters. On the other side, Big data is the subject in computing and information science describing the volume, velocity, and variability of the data hitting computer-connected systems. Big data can only be handled with newer architectures, algorithms, and methodologies as its features are contradicting regular computer systems and networks. It is well known that multiple processors are required to handle big data existing in parallel performing a single job given by the data analyst. So as we know, multiverse consist of hypothetical concepts of several parallel universe having everything like information, energy, and time. However, we see this situation to draw an association connecting parallel universes of the multiverse with parallel processors of big data by incorporating the concepts of working of parallel universe in the processing of Big Data. We provide a comprehensive observation on both the topics and take positive lenience on bringing a newer terminology in data science. History of multiverse along with big data structures are brought in with related parameters. This aspect is novel in its nature and we complement the literature carried out by the researchers and scholars appropriate analysis. We also showcase a model of the school of thought mentioned above in drawing conclusions. 2023 The Authors -
Comprehensive study of the physicochemical properties of three-component deep eutectic solvents and their implications for microbial and anticancerous activity
Sustainable chemistry centers on substituting perilous solvents and materials with eco-conscious alternatives. Deep eutectic solvents (DES) hold substantial potential in this arena. This inquiry includes the formulation of three-component eutectic solvents and an exhaustive scrutiny of their physical and chemical attributes. These encompass solubility, boiling point, pH, density, viscosity, surface tension, refractive index, contact angle, conductivity, Fourier-transform infrared spectroscopy, polarized optical microscopy, thermogravimetric analysis, and differential scanning calorimetry. Furthermore, a biological exploration featured two bacterial strains and two fungal strains. The entire spectrum of ten three-component DES was administered to these microorganisms to discern plausible impacts. In addition, the biomedical promise of these DES was unveiled through anticancer assays employing MCF-7 and HeLa cell lines. The outcomes were favorable, underscoring robust anticancer potency, thereby hinting at future oncological utility. These interdisciplinary endeavors envelop the progression of sustainable solvent innovation, meticulous physicochemical scrutiny, microbial analysis, and anticancer appraisal. This study propels inventive resolutions with ecological and biomedical reverberations by amalgamating these distinct yet interconnected facets. 2024 Indian Chemical Society -
Comprehensive Study of Silver Nanoparticle Functionalization of Kalzhat Bentonite for Medical Application
The characterization and biomedical modification of bentonite clays from the Kalzhat deposit (Kzh), which is situated in Kazakhstans Zhetysu region, are the main objectives of this work. In order to improve the raw materials structural qualities, the montmorillonite fraction was enriched, and coarse impurities were eliminated using the Salo method. The presence of meso- and micropores that guarantee high dispersity and specific surface area, as well as the prevalence of montmorillonite and kaolinite, was all confirmed by physicochemical analysis. Particle size measurements indicated finely dispersed structures with a propensity to aggregate, whereas thermal analysis demonstrated resilience under heating. After effective functionalization with silver nanoparticles, a porous hybrid system with improved surface reactivity was produced. These enhancements demonstrate the modified bentonites usefulness as a multifunctional carrier for the immobilization and controlled release of pharmaceuticals, with potential uses in drug delivery systems, antimicrobial coatings, and wound-healing materials. The material has potential use in sorption and environmental protection technologies in addition to its biomedical application. Overall, Kzhs structural and functional performance is greatly improved by the combination of purification and functionalization with silver nanoparticles, highlighting its promise as a useful element in the development of next-generation polymercomposite systems. 2025 by the authors. -
Comprehensive strategies of Lignocellulolytic enzyme production from microbes and their applications in various commercial-scale faculties
Activities of anthropological organisms leads to the production of massive lignocellulosic waste every year and these lignocellulolytic enzymes plays crucial role in developing eco-friendly, sustainable and economical methods for decomposing and pre-treating the biomass to produce biofuels, organic acids, feeds and enzymes. Lignocellulolytic enzymes sustainably hydrolyse the biomass and can be utilized in wide range of applications such as personal care, pharmaceutical, biofuel release, sewage treatment, food and beverage industries. Every year a significant ton of biomass waste is released and insight on these crucial enzymes could establish in all the industries. However, due to the increased demand for compost materials, biomass degradation has resulted in composting processes. Several methods for improving compost amount and quality have been explored, including increasing decomposer inoculums, stimulating microbial activity, and establishing a decomposable environment. All of these prerequisites are met by biotechnological applications. Biotechnological procedures are used to improve the activity of enzymes on biomass. It leads to an adequate supply of compost and base materials for enterprises. In terms of effectiveness and stability during the breakdown process, lignocellulolytic enzymes derived from genetically modified species outperformed naturally derived lignocellulolytic enzymes. It has the potential to increase the quality and output of byproducts. This review discussed the development of lignocellulolytic enzyme families and their widespread applications in a variety of industries such as olive oil extraction, carotenoid extraction, waste management, pollution control, second-generation bio-ethanol production, textile and dyeing, pharmaceuticals, pulp and paper, animal feed, food processing industries, detergent, and agricultural industries. 2022 Visagaa Publishing House. -
Comprehensive spectro-temporal studies of GX 17+2 using AstroSat observations
We performed a comprehensive spectro-temporal study of the Z-type neutron star low-mass X-ray binary GX 17+2 using long term data from the AstroSat/Soft X-ray Telescope (SXT) and Large Area X-ray Proportional Counter (LAXPC). The hardnessintensity diagrams (HIDs) of the source revealed a positive correlation between the hardness and intensity, characteristic of soft spectral state. Additionally, the LAXPC-20 HID showed the presence of secular shifts in both hardness and intensity. Time-averaged spectral modelling in the 0.7 ? 30.0 keV energy range indicated that the spectra could be well fitted with the model combination: constant edge edge tbabs thcomp bbodyrad. This analysis yielded a blackbody radius (Rbb) of ?59 km, photon index (?) of ?2.84 and electron temperature (kTe) of ?4.84 keV. Time-averaged temporal analysis revealed normal branch oscillations (NBOs) at ? 7 Hz in Observations 1 and 3, flaring branch oscillation (FBO) at ?15 Hz in Observation 2, and horizontal branch oscillation (HBO) at ?36 Hz in Observation 5. Flux resolved spectro-temporal analysis indicated that the source remained in the soft spectral state throughout all observations. A positive correlation was observed between kTbb, Fbb and Fbol, whereas an anti-correlation was noted between kTe and Fbol. The constant frequency of NBOs with an increase in Fbol suggests that their origin lies in a region strongly influenced by the corona, as explained by the radiation-hydrodynamic model. The origin of FBOs may be attributed to the damped radiation-hydrodynamic mode of radial flow, while the origin of HBOs is supported by the beat-frequency model. 2024 Elsevier B.V. -
Comprehensive spectro-temporal studies of GX 17+2 using AstroSat observations
We performed a comprehensive spectro-temporal study of the Z-type neutron star low-mass X-ray binary GX 17+2 using long term data from the AstroSat/Soft X-ray Telescope (SXT) and Large Area X-ray Proportional Counter (LAXPC). The hardnessintensity diagrams (HIDs) of the source revealed a positive correlation between the hardness and intensity, characteristic of soft spectral state. Additionally, the LAXPC-20 HID showed the presence of secular shifts in both hardness and intensity. Time-averaged spectral modelling in the 0.7 ? 30.0 keV energy range indicated that the spectra could be well fitted with the model combination: constant edge edge tbabs thcomp bbodyrad. This analysis yielded a blackbody radius (Rbb) of ?59 km, photon index (?) of ?2.84 and electron temperature (kTe) of ?4.84 keV. Time-averaged temporal analysis revealed normal branch oscillations (NBOs) at ? 7 Hz in Observations 1 and 3, flaring branch oscillation (FBO) at ?15 Hz in Observation 2, and horizontal branch oscillation (HBO) at ?36 Hz in Observation 5. Flux resolved spectro-temporal analysis indicated that the source remained in the soft spectral state throughout all observations. A positive correlation was observed between kTbb, Fbb and Fbol, whereas an anti-correlation was noted between kTe and Fbol. The constant frequency of NBOs with an increase in Fbol suggests that their origin lies in a region strongly influenced by the corona, as explained by the radiation-hydrodynamic model. The origin of FBOs may be attributed to the damped radiation-hydrodynamic mode of radial flow, while the origin of HBOs is supported by the beat-frequency model. 2024 Elsevier B.V. -
Comprehensive Review on Video Watermarking Security Threats, Challenges and its Applications
Data is a crucial resource for every business, and it must be protected both during storage and transmission. One efficient way of securing data and transferring it is through digital watermarking, where data is hidden inside a medium like text, audio, or video. Video watermarking is visible or invisible embedded data on a video in a logo, text, or video copyright disclaimer. In this proposed paper, the goal is to analyze the characteristics of video watermarking algorithms and the different metrics used for them. It deals with the extent to which the different requirements can be fulfilled, taking into consideration the conflicts between them and the practical challenges of video watermarking in terms of attacks like geometric attacks and non-geometric attacks. It also focuses on the process of watermarking a video. Recent advances in data security indicate that employing a video watermarking technology to transmit private data will be an effective method of transmitting sensitive data. The Electrochemical Society -
Comprehensive Review on CdTe Crystals: Growth, Properties, and Photovoltaic Application
Abstract: Despite the deep interest of materials scientists in cadmium telluride (CdTe) crystal growth, there is no single source to which the researchers can turn towards for comprehensive knowledge of CdTe compound semiconductor synthesis protocols, physical properties and performance. Considering this, the present review work focuses to bridge this shortcoming. The direct band gap (Eg) CdTe crystals have been in limelight in photovoltaic application (PV) since the optoelectronic properties such as Eg (1.49 eV), absorption coefficient (~105 cm1), p-type conductivity, carrier concentration (6 1016 cm3) and mobility (1040 cm2/(V s)) at the room temperature are reported that optimum for solar cells. Additionally, Cd-based compounds such as CdTe and CdZnTe have also been widely studied in the field of ? and ?-ray radiation detector, because of their extraordinary advantages like large atomic number, low weight, high mechanical hardness, flexibility, and the availability of the constituent materials. CdTe has demerits like toxicity and high melting temperature, which will complicate the growth of stoichiometric cadmium telluride crystals at high temperatures. In this regard, the review work focused the periodic evolution of the growth protocols until now. The different synthesis methods, characterization, and recent progress in the field of crystalline CdTe were discussed briefly. Important optical and electrical characteristics are presented in the tables and remaining issues have discussed, this could be looked into for further research. The applications of CdTe crystals for photovoltaic fields are also discussed in this review paper. Pleiades Publishing, Ltd. 2023. ISSN 0031-918X, Physics of Metals and Metallography, 2023, Vol. 124, No. 14, pp. 17951812. Pleiades Publishing, Ltd., 2023. ISSN 0031-918X, Physics of Metals and Metallography, 2023. Pleiades Publishing, Ltd., 2023. -
Comprehensive Phytochemical, Anti-Oxidant and GC-MS Analysis of Strobilanthes jomyi P. Biju, Josekutty, Rekha & J.R.I.Wood
Background and Objective: Plant-based medication is one of the most established practices in the Indian medical field. Earlier, raw parts of plants were directly used to treat many health conditions. Later, the most valuable part was identified, separated the chemical compounds and treated various diseases. The plant Strobilanthes jomyi belongs to the family Acanthaceae, commonly called Elathumpadi. The study aimed to evaluate the physicochemical, mineral composition, phytochemical, anti-oxidant and GC-MS analysis of leaves stem and root of S. jomyi. Materials and Methods: Different vegetative parts of S. jomyi were extracted with the Soxhlet extraction method by using methanol as solvent. Physicochemical, phytochemical, mineral composition, anti-oxidant and GC-MS analyses were evaluated by different standard protocols. Results: The phytochemical analysis revealed that leaves contained more phenolic (87.40.44 mg gG1 of GAE), flavonoid (66.230.53 mg gG1 equivalent of QE), carbohydrate (44.71.28 mg gG1 of fresh weight), protein (17.70.76 mg gG1 of fresh weight), proline (46.80.15 mg gG1 of fresh weight) and chlorophyll (46.80.15 mg gG1 of fresh weight) content than the root and stem of methanolic extract. The non-enzymatic anti-oxidant assays of the methanolic extract showed the presence of higher anti-oxidant activities in leaves, followed by root and stem. The GC-MS study of the root, stem and leaves revealed medicinally important bioactive compounds like 2,4-di-tert-butyl phenol, phytol, squalene, phenol, neophytadiene and lupeol. Conclusion: Strobilanthes jomyi can be used as an alternative source of the ayurvedic system of medicine based on its phytochemical and antioxidant activity. 2023. -
Comprehensive Maintenance of Data Quality with Software Design and Analysis
Software development activities rely heavily on the maintenance of data quality to ensure that decisions are performed efficiently without glitches. The paper will be oriented toward an in-depth approach to ensuring data accuracy through the structured design of quality-assured software. Cross-functional collaboration, problem resolution, and data validation are some of the techniques that shed light upon the essence of having multiple quality checkpoints at every stage of the software development lifecycle. The methodology is illustrated by use case and sequence diagrams that explain the interaction between system components within data validation workflows. It introduces a case study within a startup environment, which could be applied practically to solve data inconsistencies and improve operational processes on a general level. Some of the solutions developed through this novel approach to overcoming common data management challenges would include error detection automation and real-time feedback mechanisms. This paper discusses the important activity of QA in relation to data integrity. From there, the said paper continues to discuss how that concept may be applied in real life. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.