June 2025 Volume 11 Issue 2

ENGINEERING & TECHNOLOGY JOURNAL

Investigating the influence of attentional paradigm on the impact of underline frequency components on occipital region through a hybrid machine learning model

Aashish Sharma, Dr. Raghavendra Prasad

  • Pages: 1-11
    • <p>The study of attention has garnered considerable interest in cognitive psychology and neuroscience. The capacity for attention allows one to process perceptually important information while blocking irrelevant information from interfering with an ongoing task. The proposed computational model effectively explores the correlation of the role of occipital region while processing the attentional stimulus. The computational model was supported by the decision from ERP results which indicated the predominant presence of C100, P200, P300 and N400 components. Understanding the neurological underpinnings behind abstract cognition requires extensive research on attentional and occipital brain activity. When examining brain activity using electroencephalography (EEG), the occipital cortex, which is predominantly in charge of visual processing, also participates in attentional tasks in the context of abstract cognition. However, the attentional paradigm and its relationship to the occipital brain provide significant insights into cognitive processes, their ecological validity, reductionism, and emphasis on visual processing are drawbacks. The research suggests novel techniques and strategies for analysing EEG signals to improve the precision and dependability of attention assessment to solve these limitations. These suggested methods and modes present prospective directions for additional study and advancement in the area.</p>

COMPARATIVE ANALYSIS OF THE COMPRESSIVE STRENGTH OF CONCRETE UNDER DIFFERENT CURING METHODS

Yogendra Kaul , Satish Parihar

  • Pages: 1-7
    • <p>Concrete is the most prevalent material in building, exhibiting many features and potential production techniques. Concrete is distinguished by its strong compressive strength and durability, traits that may have been directly affected by the preservation technique in ancient times. The aim of this study is to illustrate the significance During the concrete curing process, together with an examination of the impact of the selected curing technique about the compression resistance. Forty-eight concrete test specimens were produced in accordance with the specification. criteria. Subsequently, the samples were partitioned into eight groups, each undergoing distinct Types of curing: immersion curing, bi-daily; outdoor curing; complete immersion curing. various waters, use of a commercial curing agent; with polyethylene film coating and in the absence of treatment. Conducting compression tests at 7 and 28 days. Among the findings acquired, The batch subjected to the curing procedure with polyethylene covering exhibited superior effective resistance to compression, succeeded by immersion methods inside water.</p>

Optimizing High-Strength Concrete Performance with Self-Healing Technologies

Sunil Kumar Verma , Mr. Satish Parihar

  • Pages: 1-7
    • <p>This study focuses on optimizing high-strength concrete (HSC) by incorporating five mineral admixtures&mdash;quartz dust, fly ash, metakaolin, ultra-fine sludge, and rice husk ash&mdash;along with a third-generation superplasticizer to reduce water demand and enhance compaction density. Despite HSC&rsquo;s promising properties, its adoption is limited due to crack formation, which compromises durability. To address this, the research explores self-healing concrete using calcite-precipitating bacteria to automatically repair cracks, improving sustainability and longevity. Additionally, eco-friendly materials are integrated to reduce the environmental impact of cement production. The research is conducted in four phases, including material analysis, blend optimization, bacterial development, and mix design validation</p>

A SYSTEMATIC REVIEW ON EARLY DIAGNOSIS AND INTERVENTION STRATEGIES OF ALZHEMERS DISEASE FROM BIOMARKERS TO THERAPEUTIC APPROACHES

Saumya Singh , Hari Om Sharan , C.S Raghuvanshi

  • Pages: 1-9
    • <p>Alzheimer's disease (AD) is predicted to become much more common as the world's population ages, posing a serious threat to global health. Effective intervention and treatment depend on early discovery, yet the diagnostic techniques used today are often invasive, expensive, and time-consuming. This study examines a range of procedures and biomarkers for the early identification of AD, from cutting-edge noninvasive and minimally invasive techniques like EEG, ocular imaging technologies, and blood/saliva/urine biomarkers, to traditional methods like brain imaging and CSF analysis. We talk about how crucial it is to find biomarkers for AD that can identify the disease in its preclinical or early clinical phases so that appropriate action may be taken before irreversible cognitive loss happens. Potential methods for early diagnosis are discussed, including speech testing, subjective memory complaints assessment, late-onset depression evaluation, and episodic memory tests. In addition, we look at standard biomarkers such as CSF tau levels and amyloid &beta;, as well as brain imaging techniques like PET and SPECT scans. The emerging non-invasive and minimally invasive biomarkers that show promise in predicting the presence of AD are discussed in this review, along with ocular imaging methods like OCT and OCTA and blood, saliva, and urine biomarkers that measure electrical activity. Although these biomarkers may be more accessible and user-friendly, standardization and validation across a range of populations are still crucial. We talk about the latest developments in AI and machine learning methods for merging and evaluating multi-modal data, which provide insights into customized forecasting and long-term tracking of AD development. In conclusion, we provide an overview of the major research projects and approaches included in the review, emphasizing their contributions to the area of early Alzheimer's disease detection.</p>
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