Numerical Modelling of an Unsaturated Capillary Barrier Cover System Using HYDRUS-2D for Percolation Control |Chapter 7 | Current Concepts in Engineering Research and Technology Vol. 1

 

Inclined multi-layered barriers can be used to protect underlying waste storage facilities. The intended barriers can confine infiltration through the implementation of the capillary barrier effect. In this study, the effect of rainfall, evaporation, and transpiration on the hydraulic properties of inclined covers was assessed by performing simulations using HYDRUS-2D numerical models. The material layers included clay loam soil as a seepage control layer, sandy soil as a moisture retention layer, and gravel as a capillary break layer. The numerical analysis simulated 20 years of climatological data (2000-2019) from Windsor, Canada, representing humid conditions with variable precipitation and evapotranspiration patterns.

 

Key quantitative results indicate that 21.09% of cumulative net rainfall was converted to lateral drainage along the sloped interfaces, while 78.91% of infiltrated water eventually exited through the bottom boundary as vertical percolation. The mean flux across the bottom boundary was 206.70 cm/day (2.39×10⁻⁶ m/s), demonstrating minimal deep percolation under the prevailing climatic conditions. Lateral diversion occurred at the interface between the seepage control layer and moisture retention layer due to the significant slope (10%) and contrasting hydraulic properties of adjacent layers. At reduced degrees of saturation, water movement between layers was restricted by low hydraulic conductivity, with the negative pressure head in the seepage control layer having minimal effect on water content in underlying layers.

 

This modelling approach, which uniquely combines an inclined multi-layer configuration with long-term transient climatic forcing, demonstrates that properly designed capillary barrier covers can effectively minimise leachate generation in waste containment systems. The findings provide quantitative design guidance for landfill covers in humid regions, showing that 10% slopes with layered clay loam, sand, and gravel materials achieve the capillary barrier effect under variable climatological conditions. The performance of this protective earthen cover can be guaranteed under the current climatological conditions, offering engineers a validated numerical framework for optimising waste containment cover designs.

 

Author(s) Details

Mohammad Ali Hagh Shenas
Department of Civil Engineering, Razi University, Kermanshah, Iran.

 

Hassan Sharafi
Department of Civil Engineering, Razi University, Kermanshah, Iran.

 

Please see the book here :- https://doi.org/10.9734/bpi/ccert/v1/7166

Sieving and Separation Automation with AI in the Food Processing Industry: Challenges of Implementing Advanced Solutions| Chapter 6 | Current Concepts in Engineering Research and Technology Vol. 1

 

The food processing industry is presently experiencing a data revolution, and sieving and separation processes are no exception. Sieving, also known as screening, is a method of separating particles based on size. It's a common process in food processing to refine and separate products like flour, sugar, cocoa powder, and spices. It can also be used for grading products into different sizes, like tea or coffee beans. While traditionally reliant on mechanical adjustments and operator experience, sieving and separation operations are now being transformed by the power of artificial intelligence (AI). AI-driven sieving and separation systems are emerging as key innovations that enhance efficiency, safety, and sustainability. This article explores how these advancements are driving a new era of intelligent processing in the food processing sector. It further studies the concept of sieving and separation automation from the angle of artificial intelligence [AI] and tries to study the hierarchical interrelationships amongst the various challenges faced by food processing companies in implementing advanced sieving solutions with the help of the VAXO technique embedded in ISM methodology.

 

 

Author(s) Details

Kshitij Mohan Sharma
Multi Tech Engineering, New Delhi, India.

 

Remica Aggarwal

Multi Tech Engineering, New Delhi, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/ccert/v1/6612

Hybrid Watermarking Framework Using Discrete Wavelet Transform and Visual Cryptographic Scheme| Chapter 5 | Current Concepts in Engineering Research and Technology Vol. 1

 

The rapid growth of the internet and easy access to multimedia data have increased concerns about unauthorised use and redistribution of digital content. Digital watermarking is a widely used technique for copyright protection and authentication of digital multimedia. Several watermarking techniques have been proposed in the literature, limited research has been conducted on the effective integration of multi-level DWT with visual hiding schemes to achieve both high robustness and perceptual quality simultaneously. This chapter presents a robust copyright protection scheme based on the discrete wavelet transform (DWT) and visual hiding scheme (VHS). Unlike the traditional schemes, in this proposed scheme, the original image was modified by embedding the watermark into the original image. The visual hidden scheme was used to construct a watermarked image. In embedding, 3 level DWT was applied on the cover image and then the embedding of the watermark was performed using the VHS technique after resizing the watermark image. In order to express the robustness and perceptibility of the presented watermark scheme, experimental results show the performance of the proposed scheme based on parameters, peak signal-to-noise ratio and resistance against various signal processing operations and attacks. The proposed scheme shows higher perceptible performance of the watermarked image without an attack environment produces 51.8 dB PSNR and a minimum of 47.7dB for test images. Under an attack environment, the performance degrade not significantly but in under tolerable range of 30 dB to       42 dB. In future work, the fractional transforms can be more suitably used to increase system robustness in the same direction.

 

 

Author(s) Details

Deepak Sharma
Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology, Guna, (M.P.), India.

 

Bali Ram Gupta
Department of Mathematics, Jaypee University of Engineering and Technology, Guna, (M.P.), India.

 

Shefali Sharma
Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology, Guna, (M.P.), India.

 

Please see the book here :- https://doi.org/10.9734/bpi/ccert/v1/6977

Predicting Student Performance Using Deep Learning and Indian Knowledge Systems | Chapter 8 | New Horizons of Science, Technology and Culture Vol. 8

 

Background: Existing data-driven approaches have demonstrated promising predictive capabilities; however, many remain narrowly focused on technical optimisation. By treating behavioural data as context-free signals, these systems often overlook the cultural, social, and ethical dimensions that influence learning.

 

Aim: The aim of this chapter is to develop a culturally grounded and ethically responsible framework for predicting student academic performance by integrating mobile phone behavioural analytics with principles drawn from the Indian Knowledge System (IKS).

 

Objectives: The study seeks to (i) model student learning behaviour using temporally rich mobile usage data, (ii) enhance prediction accuracy and interpretability through deep learning architectures, (iii) operationalise IKS-inspired constructs to provide cultural and ethical context, and (iv) support fair, human-centred educational interventions.

 

Methods: An integrative multi-input deep learning framework is proposed that combines Temporal Convolutional Networks (TCN) for sequential behaviour modelling, attention mechanisms for feature prioritisation, and static psychometric and demographic feature fusion. Mobile phone data capturing usage patterns, activity rhythms, and engagement indicators are processed alongside IKS-informed contextual features. Model performance is evaluated against classical machine learning baselines using predictive and fairness-aware metrics, with interpretability analyses supporting transparent decision-making.

 

Results: Experimental validation on representative datasets demonstrates that the proposed framework consistently outperforms traditional machine learning models in terms of prediction accuracy and stability. Attention-based explanations reveal that IKS-inspired features contribute meaningfully to performance gains while reducing subgroup disparities. The results indicate improved fairness, enhanced interpretability for educators, and greater alignment with student well-being and learning rhythms.

 

Conclusion: The results indicate that embedding contextual and value-oriented dimensions improves not only predictive accuracy but also interpretability and fairness, making the system more aligned with real educational environments. The inclusion of explainability mechanisms further strengthens trust and transparency, which are critical for adoption in academic settings. Overall, this work contributes a meaningful step toward educational AI systems that support holistic learning, respect learner identity, and encourage responsible decision-making in data-driven education.

 

Novelty: The key novelty of this work lies in embedding indigenous knowledge principles directly into the design and interpretation of deep learning models for educational analytics. By bridging behavioural data, advanced neural architectures, and culturally rooted context, the framework advances a human-centric paradigm for academic performance prediction that emphasises ethical responsibility, cultural resonance, and holistic educational outcomes.

 

 

Author(s) Details

S. Vimala
Department of Computer Science, St. Joseph’s College (Autonomous), Tiruchirappalli -2, Affiliated to Bharathidasan University, Tamil Nadu, India.

 

G. Arockia Sahaya Sheela
Department of Computer Science, St. Joseph’s College (Autonomous), Tiruchirappalli -2, Affiliated to Bharathidasan University, Tamil Nadu, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/nhstc/v8/7176

Biomass-Derived Activated Carbon for CO₂ Mitigation in Compression Ignition Engine Exhaust Systems | Chapter 7 | New Horizons of Science, Technology and Culture Vol. 8

 

Rapid industrialisation has intensified environmental pollution and global warming, with the automotive sector being a major contributor to greenhouse gas emissions. This study investigates an effective post-combustion CO₂ reduction approach for compression ignition (CI) engines using a modified exhaust adsorption system containing waste biomass–derived adsorbents. Activated carbon and biochar produced from coconut shell, rice husk, and eucalyptus wood through carbonisation and activation processes were evaluated for their CO₂ adsorption performance. Integration of a single adsorption chamber into the exhaust system achieved up to a 48% reduction in CO₂ emissions compared to baseline operation, while the addition of a second chamber provided a further 16% reduction. Experiments were conducted on a single-cylinder, four-stroke diesel engine, where baseline CO₂ emissions increased with engine load, reaching a maximum of 13.5%. After installing biochar and activated carbon filters, CO₂ emissions decreased significantly, with biochar showing superior performance at higher loads. The optimal configuration using blended diesel with activated carbon distributed across dual compartments reduced CO₂ emissions from 6.2% to 0.4% at maximum load. Concurrent reductions in CO, HC, and NOₓ emissions confirmed the effectiveness of the proposed adsorption system.

 

 

Author(s) Details

G. Balaji
Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India.

 

D. Premnath
Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India.

 

V. Rajasekar
Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India.

 

S. Natarajan
Department of Mechanical Engineering, Sri Venkateswara College of Engineering, Pennalur Village, Sriperumbudur Tk, Tamil Nadu, 602117, India.

 

C. Karthikeyan
Department of Energy Science, Alagappa University, Karaikudi- 630003, Tamil Nadu, India.

 

Kapilan Natesan
Department of Mechanical Engineering, Nitte Meenakshi Institute of Technology, Yelahanka, Bangalore-560064, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/nhstc/v8/7167

Hypersensitivity Pneumonitis: A Rural India Story | Chapter 9 | An Overview of Disease and Health Research Vol. 10

 

Dry nasal snuff, commonly known as “Chhikni” in India, is a smokeless tobacco preparation composed of finely powdered tobacco that is inhaled into the nasal cavity. Although traditionally perceived as less harmful than smoking, long-term inhalational exposure may lead to significant pulmonary complications. Hypersensitivity pneumonitis (HP) is an immune-mediated interstitial lung disease caused by repeated inhalation of sensitising antigens in susceptible individuals. The report presents the case of a 67-year-old woman with a 30-year history of chronic dry snuff inhalation (4–5 times daily) who presented with acute hypoxic respiratory failure. Clinical examination revealed diffuse crackles and wheezes with severe hypoxemia. Laboratory investigations showed leukocytosis, while inflammatory markers and autoimmune serologies were unremarkable. High-resolution computed tomography (HRCT) of the chest demonstrated bilateral mosaic attenuation with patchy ground-glass opacities suggestive of inflammatory pneumonitis. Infectious and autoimmune etiologies were excluded. Based on significant chronic inhalational exposure and radiologic findings, a diagnosis of chronic hypersensitivity pneumonitis was made.

 

The patient was treated with high-dose intravenous methylprednisolone followed by oral corticosteroids, resulting in significant clinical and radiological improvement. She was discharged on minimal home oxygen therapy with strict avoidance of further snuff exposure.

 

This case highlights dry nasal snuff as a potential but underrecognized cause of chronic hypersensitivity pneumonitis and emphasises the importance of detailed exposure history in patients presenting with unexplained interstitial lung disease.

 

 

Author(s) Details

Hairya Ajaykumar Lakhani
SBKS Medical Institute and Research Centre, Vadodara, India.

 

Miloni Mineshbhai Nada
Surat Municipal Institute of Medical Education and Research (SMIMER), Affiliated to the Veer Narmad South Gujarat University, Surat, India.

 

Aarjuv Majmundar
SBKS Medical Institute and Research Centre, Vadodara, India.

 

Sucheta Lakhani
SBKS Medical Institute and Research Centre, Vadodara, India.

 

Jitendra D Lakhani
SBKS Medical Institute and Research Centre, Vadodara, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/aodhr/v10/7174

 

Infantile Malignant Osteopetrosis Presenting with Bone-Within-Bone Appearance and Suspected Haematological Malignancy: A Case Report | Chapter 8 | An Overview of Disease and Health Research Vol. 10

 

Background: The radiological sign “bone within a bone” is observed in a variety of conditions, including osteopetrosis. Osteopetrosis, first described by Albers-Schonberg in 1904, is a rare genetic disorder characterised by increased bone density. “Osteopetrosis of infantile origin” is one of its rare and aggressive subtypes, which is inherited as an autosomal recessive trait and often leads to death due to recurrent infections and multi-system involvement.

 

Aim: The study aims to focus on a case of malignant form of osteopetrosis with its varied and severe clinical course, prognosis, urgent need for treatment and its likely association with haematological malignancy like lymphoma.

 

Case Presentation: A 2-year-old male child presented with fever, loose stools and gum bleeding for 2 days with regression of milestones. Examination revealed severe malnutrition with significantly enlarged lymph nodes and hepatosplenomegaly. Laboratory investigations showed pancytopenia with atypical cells, deranged renal function, and transaminitis. The pathognomic finding of “bone within a bone” was seen on X-ray. CT scan imaging showed moderate dilatation of the ventricles with thickening of the posterior fossa imitating a mass lesion. The child was provisionally diagnosed with hypothyroidism, osteopetrosis, and possible haematological malignancy. The child succumbed to death due to severe sepsis despite the treatment.

 

Discussion: Increased bone density in osteopetrosis causes encroachment of marrow space, leading to all other consequences. Children diagnosed in early infancy often succumb to death due to severe sepsis. Management of osteopetrosis is usually symptomatic, requiring a multidisciplinary approach. Hematopoietic stem cell transplantation (HSCT) is considered potentially curative in selected autosomal recessive forms with intrinsic osteoclast defects and remains the definitive treatment under research.

 

Conclusion: Malignant infantile osteopetrosis is a rare but fatal condition, and its resemblance to other disease conditions often masks the diagnosis. Creating awareness about osteopetrosis, along with genetic counselling and antenatal diagnosis, plays an important role in managing it. Although rare, its co-existence with lymphoma should always be ruled out.

 

 

Author(s) Details

Monica Jassal
Maharishi Markandeshwar College of Medical Sciences and Research, Sadopur, Ambala, India.

 

Vyas Kumar Rathaur
All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/aodhr/v10/7144