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Efficient Reconstruction and Secure Transmission of Medical Images For Telemedicine Applications
No full textTelemedicine has become a crucial solution for delivering healthcare services remotely,
particularly in remote areas and during emergencies. It enhances communication between
patients and healthcare providers by enabling remote monitoring, medical imaging, and
data sharing. By integrating smart healthcare devices, telemedicine systems can transmit real-time patient data directly to physicians, supporting timely consultations and
interventions. Store-and-forward telemedicine services allow for the collection of medical data—including images, pathology reports, and patient health information—at one
location, where it is securely stored and later transmitted to healthcare providers at a
different location for review and consultation. This thesis presents a comprehensive approach for the reconstruction and secure transmission of low-dose computed tomography
(LDCT) images using store and forward telemedicine services.
In the first work we presented a comprehensive review based on computational medical image reconstruction techniques. This study aims to discuss some of the significant
contributions of data-driven techniques to solve the inverse problems in medical image
reconstruction (MIR). In this study, we have comprehensively studied various reconstruction techniques based on machine learning and deep learning. This work provides a
detailed survey of MIR, which includes the traditional reconstruction algorithm, machine
learning, and deep learning-based approaches such as GAN, autoencoder, RNN, U-net,
etc., to solve inverse problems, evaluation metrics, and openly available codes used in the
literature.
The second work introduces unsupervised image reconstruction techniques that combine
iterative reconstruction techniques, i.e., analytical and statistical methods with neural
networks. In the first part, the study integrates the Maximum Likelihood Expectation
Maximization (MLEM) algorithm with unsupervised deep convolutional neural network
(DCNN) priors. The second approach presents a novel unsupervised CT reconstruction
method that leverages an Attention-Enhanced Deep Image Prior (AE-DIP) in fusion with
the Simultaneous Algebraic Reconstruction Technique (SART).
The third approach introduces Loss-construct Unsupervised Network Adjustment (LUNA)
for low-dose CT reconstruction. It combines SART with weighted total variation (WTV)
regularization within a Deep CNN, optimized using the ADMM framework for balanced
and accurate results. Multiple loss functions—perceptual, SSIM, WL2, WTV, and sinogram loss—guide the network updates, addressing data limitations in deep learning. This
robust, unsupervised method effectively enhances low-dose CT image reconstruction.
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The fourth approach is a pixel-based blind self-embedding fragile watermarking technique tailored for e-healthcare applications, specifically designed for store-and-forward
telemedicine services. Authentication bits are generated through Chaotic Coordinate
Mapping, which involves a series of logical and cyclic operations within the spatial features of the image. The Linear Feedback Shift Register (LFSR) is employed to generate
both a random matrix and a cryptic key. Ensuring perceptual quality after the watermark
insertion is necessary for CT images, specifically for low-dose images.
Keywords: Store and forward telemedicine services, inverse problems, low CT image
reconstruction, Iterative image reconstruction methods, Deep image Prior, ADMM optimizations, loss functions, CT image authentication, Blind watermarking, self-embedding
fragile watermarking
Effect of Elicitors on Metabolite Production in Didymella sinensis, an Endophytic Fungus Isolated from C. sinensis
No full textCatechins are a type of polyphenolic compounds with strong antioxidant properties, primarily
found in the leaves of Camellia sinensis (tea plant) and widely recognised for their
therapeutic effects, such as anti-inflammatory, anticancer, anti-tumour, and antimicrobial
properties. Additionally, certain endophytic fungi isolated from tea have been identified as
capable of producing catechins. However, yield was found to be very low, which poses
challenges for practical applications. This study aims to boost catechin production in the
endophytic fungus Didymella sinensis (CSPL5b), isolated from C. sinensis, by using the
elicitation technique to enhance the biosynthesis of secondary metabolites.
This study explores how adding certain substances known as “elicitors” influences catechin
production in CSPL5b. The fungal cultures were treated with three different elicitors:
Salicylic acid (SA), tea leaf extract (TE), and catechin (CAT) at different concentrations.
After 10 and 15days, metabolites were extracted using ethyl acetate to obtain crude extracts.
The extracts were then tested for different phytochemical analyses using TLC, and their total
phenolic content (TPC) and total flavonoid content (TFC) were measured. Additionally, the
DPPH method was used to assess antioxidant ability. Further, quantitative analysis was also
done using High Performance Liquid Chromatography (HPLC).
Among the elicitors, salicylic acid and catechins significantly enhanced catechin production
and bioactivity. This research demonstrates that using elicitation is an effective method for
boosting catechin production in D. sinensis. Using fungi as a source of catechins offers a
sustainable and reliable alternative to tea plants, making it a cost-effective, eco-friendly, and
consistent method for obtaining valuable secondary metabolites
Beyond the numbers : Why the insistence on a 15:1 studentteacher ratio could be counterproductive
No full textEffect of Dark Pattern on Tourism Industry
No full textDark Patterns are design tricks that manipulate users into making choices they might not
genuinely want, by exploiting cognitive biases. Despite their impact, research on these deceptive
tactics in the tourism industry remains limited. This study examines how dark patterns influence
consumer purchase intentions (PI) and fear of missing out (FOMO) on online travel booking
platforms. To do so two experiments are performed. Experiment one tested social proof (activity
message, positive testimonial, negative testimonial) across three categories of tourism (package,
hotel, flight) using a mixed factorial design. Its results showed that positive testimonials
increased purchase intentions, while activity messages heightened FOMO in participants.
Experiment two, tested scarcity appeals (countdown timer, limited supply) across the same
categories using mixed factorial design. Its results revealed that limited supply scarcity does
increase purchase intention more in comparison with countdown timer, but neither scarcity
appeal significantly affected FOMO. Experiment three, tested high anchor and low anchor
across the same categories u ko sing mixed factorial design. Its low anchor condition produced
slightly higher scores compared to the high anchor condition but neither anchor significantly
affected FOMO. Findings indicate while positive testimonials and limited supply scarcity and
low anchor effectively boost consumers' purchase intentions, their impact on FOMO varies,
suggesting room for more targeted and ethical marketing strategies
Body Dissatisfaction and Self-Esteem as Determinants of Behavioral Tendencies in Romantic Relationships
No full textAccording to a 2019 report by the Mental Health Foundation, 31% of adolescents and 35% of adults report dissatisfaction with their body image which highlights a pervasive concern regarding self-perception. This issue is less about physical appearance and more about the disparity between how individuals perceive themselves and how they aspire to appear. Carl Rogers (1995) posited that the incongruence between one’s real and ideal selves can result in psychological distress and adverse outcomes. Negative self- perceptions not only impact individual well-being but also have detrimental effects on interpersonal interactions and relationships. Research by Murray et al. (1999) further underscores that self-doubt can exacerbate insecurities within romantic relationships, which may contribute to the manifestation of symptoms associated with relationship- centered obsessive-compulsive disorder (ROCD).
A primary developmental task of early adulthood is the establishment of intimacy with a romantic partner. Erikson (1968) emphasized that a well-defined sense of self is critical for forming successful and meaningful intimate relationships. Failure to pursue a positive self-concept during adolescence may lead to challenges such as loneliness and emotional isolation, which, in turn, can manifest as apprehension and difficulty in establishing romantic relationships and close friendships (Erikson, 1968).
While the roles of self-esteem and body dissatisfaction in relationship dynamics have been extensively studied over the years, their association with relationship-centered obsessive-compulsive disorder (ROCD) remains underexplored.
Prior research underscores that individuals experiencing heightened body dissatisfaction and diminished self-esteem are more likely to encounter adverse relational outcomes, including increased romantic jealousy, relational conflicts, and diminished satisfaction within partnerships. These dynamics are further compounded by compensatory behaviors, such as over-investment in romantic relationships and strategic gift-giving, aimed at securing relational stability and addressing self-perceived inadequacies.
This study is among the first to investigate how specific relationship behaviors may contribute to the development of symptoms associated with relationship-centered obsessive-compulsive disorder (ROCD). While much of the existing literature emphasizes the treatment of ROCD (Doron et al., 2017) and its symptomatology (Doron, 2016), limited attention has been given to its developmental origins and the personality factors that may predispose individuals to the condition. Given the substantial associations between certain relational behaviors and relationship quality, it becomes important to explore the factors that are linked with the presence of ROCD symptoms, including potential antecedents and mediating variables. Such insights are essential for reducing both the likelihood and severity of its negative effects on relationships.
The research gathered data from a substantial non-clinical sample of 400 individuals between the age of 18-30 (Mean = 23.97, SD = 3.73) who were or had been involved in a heterosexual romantic relationship.
The outcomes validated the hypotheses derived from the conceptual framework. The central discoveries of the research were as follows: (1) Body dissatisfaction has a direct impact on relationship obsessive compulsive disorder (ROCD) symptoms (2) Self-esteem plays a mediating function between body-dissatisfaction and relationship obsessive compulsive disorder (ROCD) symptoms.
The study's findings indicated that the practical motive behind gift-giving served as a mediator in the relationship between self-esteem and ROCD symptoms. In contrast, the obligatory motive for gift-giving did not show a significant link to ROCD symptoms but was notably associated with self-esteem. Additionally, the research demonstrated that romantic jealousy played a mediating role in the connection between self-esteem and ROCD symptoms.
These nuanced findings of the impact of body dissatisfaction and self-esteem on relationship dissatisfaction may shed light on the exploration of self-esteem and worth. This understanding may help individuals comprehend the connection between distress and perceived shortcomings in their romantic relationships
Design Verification Using Formal Techniques
No full textThe increasing complexity of chips has made traditional verification methods more difficult and
expensive. To tackle the challenge of accurately implementing intricate designs, current research is
exploring the integration of formal techniques with adjustments to design methodologies. It has
been suggested that formalizing abstract models early in the design phase can help detect design
errors and reduce the cost of fixing bugs. Recognizing that different verification issues require
unique strategies is crucial for effectively applying formal verification in the initial stages of
design. Each perspective offers a distinct way of reasoning to answer the question, "Why is the
design correct?" By employing various models and tools for each perspective, a set of viewpoints
can capture the design intuition. This approach allows the models to be sufficiently small for quick
construction, validation, and modification. Identifying corner case issues early in the design
process results in lower redesign costs compared to discovering bugs later on. Additionally, this
thesis includes efforts to cut the number of test cases in half, thereby saving simulation time. The
conclusion and future directions of the work are discussed at the end of the thesis
Bacterioboat, a Novel Drug Delivery System Development and Application.
No full textPh.D.In spite of having many advantages, administration of a drug through the oral route only allows less than 10% absorption of the drug, which has low solubility or low cell membrane permeability, or both, through the gastrointestinal (GI) tract, especially the small intestine1 . Therefore, it has many disadvantageous consequences, including substantial financial loss due to the requirement of at least ten times more drugs than the body originally required 2–5 . Moreover, oral drug administration usually requires multiple doses due to the faster metabolism of drug molecules in the GI tract. In addition to that, excessive use of drugs shows undesired toxicity in various parts of the digestive tract6,7. Henceforth, reduction of drug use is necessary without compromising the effectiveness of the drugs. This thesis introduces a novel drug delivery approach integrating nanotechnology with microbial vectors, offering a new paradigm for targeted and sustained drug release. We report the development and deployment of Bacterioboat, which consists of surfaceencapsulated mesoporous nanoparticles on metabolically active Lactobacillus reuteri, as a drug carrier suitable for oral administration8 . The porous chitosan nanoparticle layer serves as a protective barrier, shielding the bacteria from any potential adverse effects of the loaded drug while preserving the integrity of the delivery system during its passage through the gastrointestinal (GI) tract. Importantly, the bacteria remain alive and metabolically active throughout the process, retaining their capacity for biofilm formation, which is crucial for effective colonisation and sustained drug release. The BB system's versatility extends beyond drug delivery. It can attach dietary supplements, such as vitamins and proteins, as well as other beneficial compounds or enzymes, to the microbes. This allows for a sustained release and enhanced bioavailability of these compounds, providing added health benefits without any negative side effects. Furthermore, the BB system can be easily formulated into various oral dosage forms, including tablets, capsules, or oral suspensions. This adaptability ensures that the system can be consumed conveniently and effectively for therapeutic purposes or to deliver desired health benefits
Estimating Psychophysiological Changes Using Heart Rate Variability Analysis
No full textPh.D. ThesisThe autonomic nervous system (ANS) plays a crucial role in
maintaining physiological balance, responding dynamically to
external modulators categorized as stressors and relaxers. Heart Rate
Variability (HRV) serves as a key biomarker for assessing these
influences, enabling objective analysis of stress and relaxation states.
This research presents a multi-domain approach to HRV analysis,
integrating standard time-domain and frequency-domain features
with advanced techniques such as Fuzzy Recurrence Plot (FRP) and
Empirical Mode Decomposition-based FRP (IMF_FRP_GLCM).
First, the study investigates the impact of city driving stressors and
slow-paced breathing relaxers on ANS activity, revealing that
RMSSD consistently exhibits opposite trends under these conditions,
making it a robust indicator of stress and relaxation states.
Furthermore, to deepen the understanding of the autonomic
responses, the study converts HRV time series into image-based
representations—particularly through fuzzy recurrence plots. This
transformation adds a powerful visual dimension that preserves
temporal and nonlinear dynamics, making subtle physiological
changes associated with relaxation more apparent. By visualizing
these patterns, clinicians and individuals can more intuitively
observe and track autonomic responses to slow-paced breathing,
thereby enhancing interpretation, communication, and adherence in
relaxation-focused interventions.
Building upon this, the study explores time-series-to-image
conversion techniques to enhance HRV classification, leveraging
FRP for improved feature extraction and machine learning
performance. HRV time series collected from 60 participants during
spontaneous and slow paced breathing were analyzed across different
segment lengths. Results demonstrate that standard HRV features
provide optimal classification performance for 5-minute segments,
while IMF_FRP features maintain high accuracy even for ultra-short
segments, aligning with real-time monitoring requirements in
wearable health devices. Feature selection methods such as Fisher
Discriminant Ratio (FDR) and greedy search improved classification
efficiency, with Support Vector Machine (SVM) achieving an
accuracy of 96.6% and specificity of 100% for 5-minute segments.
The findings underscore the significance of FRP-based analysis in
detecting physiological states and provide a foundation for
integrating HRV-based stress and relaxation detection into smart
wearable technology. By bridging traditional HRV analysis with
novel machine learning techniques, this research advances the
objective and data-driven methods for stress monitoring and
personalized health interventions
Forgiveness and Interpersonal Problem Solving : Mediating Role of Personality
No full textThe present research sought to explore the mediating role of personality in the relationship between
forgiveness and interpersonal problem-solving. This cross-sectional, correlational study involved
a sample of 100 students aged 18 to 30 from four universities in Punjab. The data was collected
by using standardized instruments such as Bolton Forgiveness Scale, the Big Five Inventory, and
the Short Form of the Social Problem Solving Inventory. Correlational analysis and regression
indicated a positive association between forgiveness and adaptive problem-solving styles
(including positive problem orientation and rational problem solving) as well as with personality
traits like agreeableness, extraversion and openness. Mediation analysis using Hayes’ PROCESS
macro revealed that agreeableness and openness partially mediated the relationship between
forgiveness and interpersonal problem solving (constructive problem solving). Neuroticism was
associated with maladaptive strategies such as impulsive carelessness and negative problem
orientation. The results suggest that forgiveness serves as an important emotional resource that
facilitates improved interpersonal functioning and conflict resolution through the influence of
personality traits.
Keywords: Forgiveness, Interpersonal Problem Solving, Personality, Big Five Model