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Conductivity/Electrochemical Study of Polyvinyl pyrrolidone-Poly(vinyl alcohol)/I3? Thin Film Electrolyte for Integrated Dye-Sensitized Solar Cells and Supercapacitors
Abstract: The current era focuses not only on producing solar energy but also preserving it for future use. Dye-sensitized solar cells (DSSC) and supercapacitors (SC) are such energy-based devices. DSSCs capture the solar energy and SCs store this captured energy. A natural anthocyanin dye extracted from Garcinia indica (kokum fruit) was used in the DSSCs. SnO2, one of the promising electrode materials for DSSC, was synthesized via a microwave technique. Blend polymer electrolytes (BPE) were prepared through a solution casting technique. A polyvinyl pyrrolidone (PVP) and polyvinyl alcohol (PVA) blend with varying concentrations of potassium iodide, along with iodine dopant, was prepared as a BPE electrolyte composition. The best of the PVA-PVP/KI composition was chosen using Nyquist plots of electrochemical impedance spectroscopy (EIS). Varying the temperature, the dielectric and conductivity study of the chosen composition was studied in detail. A fast/single-step synthesis technique, namely a laser-engraved approach, was used for few-layer graphene synthesis. This graphene serves as a common platform for the DSSC-SC integrated device: as a counter electrode in DSSC and graphene-graphene symmetric electrode in SC. A DSSC-SC integrated device was fabricated and characterized using various analytical and microscopy techniques. The integrated device showed a 0.42 fill factor and 0.56% efficiency. The discharge time for integrated DSSC-SC cells was found to be increased threefold. Graphical Abstract: [Figure not available: see fulltext.] 2020, The Author(s). -
CONFIDENTIAL TRAINING AND INFERENCE USING SECURE MULTI-PARTY COMPUTATION ON VERTICALLY PARTITIONED DATASET
Digitalization across all spheres of life has given rise to issues like data ownership and privacy. Privacy-Preserving Machine Learning (PPML), an active area of research, aims to preserve privacy for machine learning (ML) stakeholders like data owners, ML model owners, and inference users. The Paper, CoTraIn-VPD, proposes private ML inference and training of models for vertically partitioned datasets with Secure Multi-Party Computation (SPMC) and Differential Privacy (DP) techniques. The proposed approach addresses complications linked with the privacy of various ML stakeholders dealing with vertically portioned datasets. This technique is implemented in Python using open-source libraries such as SyMPC (SMPC functions), PyDP (DP aggregations), and CrypTen (secure and private training). The paper uses information privacy measures, including mutual information and KL-Divergence, across different privacy budgets to empirically demonstrate privacy preservation with high ML accuracy and minimal performance cost. 2023 SCPE. -
Configuration of Streamlines of a Rotating Fluid Flows with Variable Viscosity
Volume 2, issue 8, ISSN 23938374 -
Conflict and Coexistence of Human Rights: An Exploratory Study with Reference to Intellectual Property Rights
Human rights and Intellectual Property Rights (IPRs) have developed independently. Human rights are inalienable rights associated with human dignity while IPRs are the rights with the goal of promoting innovations and the interests of select communities to further economic and technological growth. The economic and personal interests of the individual have received prime attention under the international intellectual property law. Economic growth is given priority over human rights in the international criteria for IPRs in global trade. Whereas, it has a significant impact on the implementation of human rights for both individuals and communities, including the rights to adequate food, health, environment, and education. IPRs are gravely at odds with human rights, even though a connection between the two rights can be found in General Comment No. 17 on Article 15(1)(c) of the International Covenant on Economic, Social, and Cultural Rights (ICESCR) and Article 27 of the Universal Declaration of Human Rights (UDHR). According to the UDHR, intellectual property is a human right in and of itself, but its enforcement often infringes other human rights. In light of the above perspective, the authors explore the interrelationship between IPRs and human rights and also analyze the evolving IPRs, in different fields of its application, causing adversarial impacts on several other human rights. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Confrontations faced by women in higher education institutions and strategies to overcome the anomalies in the mid-career
Women do succeed in higher positions in the higher education system but only to a certain point, and many women are really motivated by the traditional academic values such as passion to the discipline, pursuit of knowledge, good working environment, and flexibility. Women in higher education .spend the majority of their life at the mid-career stage. Some of them feel wedged, undervalued, and find no motivation to go forward in their mid-career. Hence, the mid-career stage is very much important with women academicians, and they feel there is little support or mentoring. Hence, the mid-career period is increasingly difficult to navigate. Women encounter enormous obstacles in their academic career, including unequal task distribution and balancing caring responsibilities to name a few. The aim of this chapter is to discuss in detail the challenges and obstacles faced by women in their mid-career in higher education and a few strategies to overcome the encounters. 2022, IGI Global. All rights reserved. -
Confronting an undefined crime
For the BJP-led NDA, maintaining traditional family values is crucial, and these values are deeply intertwined with belief systems where marriage is viewed as a sacred institution. -
Congestion Avoidance in Vehicular Ad Hoc Network MAC Layer Using Harmony SearchModified Laying Chicken Algorithm (HS-MLCA)
To address congestion in the MAC layer and enhance overall performance, the HS-MLCA is proposed. This algorithm incorporates the principles of both Harmony Search and Laying Chicken Algorithm to optimize resource allocation and congestion control. At the MAC layer, HS-MLCA offers several advantages over traditional congestion control schemes. Firstly, it leverages the Harmony Search algorithm, which is known for its ability to exploit the best outcomes in search processes. By exploring the solution space and exploiting promising regions, HS-MLCA optimizes resource allocation in the MAC layer. The integration of the Laying Chicken Algorithm (LCA) further enhances performance by improving convergence speed and solution accuracy. This hybrid approach leverages the strengths of both Harmony Search (HS) and LCA, resulting in more efficient and effective resource management. The Laying Chicken Algorithm simulates the behavior of laying hens in terms of resource allocation and competition. This approach contributes to provide the solution in quality and convergence speed, as the algorithm adapts to the dynamic nature of the MAC layer and the varying traffic conditions in VANETs. By combining the strengths of Harmony Search and Laying Chicken Algorithm, HS-MLCA offers improved performance in terms of congestion control in the MAC layer. It optimizes resource allocation, minimizes collisions and packet loss, reduces delay, and enhances overall network efficiency. These improvements ultimately lead to better quality of service, increased network capacity, and enhanced user experience in VANETs. It is worth noting that the specific performance improvements and benefits of HS-MLCA may vary depending on the implementation details, network conditions, and the specific VANET scenario. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Congestion management approaches in deregulated power system an illustrative approach
In deregulated power system with competitive electricity market environment, the provision of strategic bidding option to the market participants and its consequences are open up new challenging tasks to the system operator. The market economic efficiency is mainly dependent on transmission system support. The inability of transmission system support to drive market cleared schedule is known as congestion and which is not desirable. The remedial actions to relieve congestion in the transmission system known as congestion relief approaches and are differ in various markets around the world. The objective of this paper is to illustrate some of the technical and non-technical approaches using simple case studies. 2016 SERSC. -
Connect among employee engagement and three key of organisational commitment level - An empirical exploration AMID techs
The main objective of this paper is to gravely examine the link between employee engagement level and affective, continuance and normative commitment level in information technology (IT) organisations in Bangalore city. In primary data, responses are collected through well framed questionnaires and direct interaction with the employees to selected sample of 550 respondents of 10 Information Technology organisations in Bangalore city. The result revealed that employee engagement level explained 32% of the variation in total commitment. Since the P value is less than 0.01, it can be inferred that the linkage between employee engagement level and total commitment is statistically significant. The study identified a strong, positive correlation between employee's engagement level and affective commitment (d = 0.347, p =0.000) and employee's engagement level and normative commitment (d =.265, p =0.000), which were statistically significant. The study also revealed a positive correlation between employee engagement level and continuance commitment, which was not statistically significant (d =.072, p =0.096). The current study adds to the research pointing at employee's engagement level as a promising underlying mechanism to improve employee's organisational commitment level. IAEME Publication. -
Connected k-forcing sets of graphs and splitting graphs
The notion of k-forcing number of a graph was introduced by Amos et al. For a given graph G and a given subset I of the vertices of the graph G, the vertices in I are known as initially colored black vertices and the vertices in V (G) ? I are known as not initially colored black vertices or white vertices. The set I is a k-forcing set of a graph G if all vertices in G eventually colored black after applying the following color changing rule: If a black colored vertex is adjacent to at most k-white vertices, then the white vertices change to be colored black. The cardinality of a smallest k-forcing set is known as the k-forcing number Zk (G) of the graph G. If the sub graph induced by the vertices in I are connected, then I is called the connected k-forcing set. The minimum cardinality of such a set is called the connected k-forcing number of G and is denoted by Zck (G). This manuscript is intended to study the connected k-forcing number of graphs and the splitting graphs. 2020 the author(s). -
Connectivity between India and Sri Lanka: A model for South Asia
India-Sri Lanka bilateral ties pervade in almost all areas despite various ups and downs. In the age of globalization, connectivity is crucial in maintaining and enhancing relations. Realizing this, India and Sri Lanka have invested in connectivity in four broad areas: physical, cultural, information and communication technology (ICT), and economic. Physical connectivity presently exists through air and sea; given the proximity, land connectivity would benefit the common man on both sides. Cultural connections go back centuries and have received an institutional framework of late. ICT linkage is emerging but highly promising in terms of public-private involvement. With components of trade and investments, economic connectivity faces tough competition from extra-regional powers like China. On the way forward, challenges abound and require patience and maturity in policy making and its implementation in both countries. 2020 Elsevier Inc. All rights reserved. -
Consecutive Radio Labelling of Graphs
Radio labelling or radio colouring is an assignment of positive integers to the vertices of a graph such that the difference between labels of any two vertices must be at least one more than the difference between the diameter of the graph and the distance between the vertices themselves. A graph G admits consecutive radio labelling when the radio number of the graph equals the order of the graph. In this paper, we study certain graphs admitting consecutive radio labelling and identify certain properties of such graphs. Moreover, we characterize the graphs with diameter two admitting consecutive radio labelling and examine certain properties of the labelling under some graph operations. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Conservation of Endangered Cordyceps sinensis Through Artificial Cultivation Strategies of C. militaris, an Alternate
Cordyceps, an entomopathogenic fungus belonging to the Ascomycota phylum, is a familiar remedial mushroom that is extensively used in the traditional medicinal system, especially in South Asian nations. The significance of this genus members in a range of therapeutic and biotechnological applications has long been acknowledged. The exceedingly valuable fungus Ophiocordyceps sinensis (Cordyceps sinensis) is found in the alpine meadows of Bhutan, Nepal, Tibet, and India, where it is severely harvested. Driven by market demand and ecological concerns, the study highlights challenges in natural C. sinensis collection and emphasizes the shift towards sustainable artificial cultivation methods. This in-depth review navigates Cordyceps cultivation strategies, focusing on C. sinensis and the viable alternative, C. militaris. The escalating demand for Cordyceps fruiting bodies and bioactive compounds prompts a shift toward sustainable artificial cultivation. While solid-state fermentation on brown rice remains a traditional method, liquid culture, especially submerged and surface/static techniques, emerges as a key industrial approach, offering shorter cultivation periods and enhanced cordycepin production. The review accentuates the adaptability and scalability of liquid culture, providing valuable insights for large-scale Cordyceps production. The future prospects of Cordyceps cultivation require a holistic approach, combining scientific understanding, technological innovation, and sustainable practices to meet the demand for bioactive metabolites while ensuring the conservation of natural Cordyceps populations. Graphical Abstract: (Figure presented.). The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Consolidation of Cloud Computing in Smart and Sustainable Environment
Cloud computing has revolutionized IoT device data collection, administration, and analysis by offering a scalable and sustainable solution for managing vast amounts of data. The paper highlights cloud computing's benefits in data processing, device management, cost efficiency and scalability. However, challenges related to security, data ownership, and vendor lock-in require attention. A novel sustainable cloud-IoT model is presented by integrating smart computing with cloud infrastructure. It is observed that the model records promising performance. The mean response delay is 1.9 seconds and the 89.5% is the generated mean computational storage accuracy rate. In conclusion, the cloud computing empowered sustainable model can be used in organizations to gain insights from IoT data and make informed decisions, shaping future research in this rapidly evolving field. 2023 IEEE. -
Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA): A developmental cohort study protocol
Background: Low and middle-income countries like India with a large youth population experience a different environment from that of high-income countries. The Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA), based in India, aims to examine environmental influences on genomic variations, neurodevelopmental trajectories and vulnerability to psychopathology, with a focus on externalizing disorders. Methods: cVEDA is a longitudinal cohort study, with planned missingness design for yearly follow-up. Participants have been recruited from multi-site tertiary care mental health settings, local communities, schools and colleges. 10,000 individuals between 6 and 23 years of age, of all genders, representing five geographically, ethnically, and socio-culturally distinct regions in India, and exposures to variations in early life adversity (psychosocial, nutritional, toxic exposures, slum-habitats, socio-political conflicts, urban/rural living, mental illness in the family) have been assessed using age-appropriate instruments to capture socio-demographic information, temperament, environmental exposures, parenting, psychiatric morbidity, and neuropsychological functioning. Blood/saliva and urine samples have been collected for genetic, epigenetic and toxicological (heavy metals, volatile organic compounds) studies. Structural (T1, T2, DTI) and functional (resting state fMRI) MRI brain scans have been performed on approximately 15% of the individuals. All data and biological samples are maintained in a databank and biobank, respectively. Discussion: The cVEDA has established the largest neurodevelopmental database in India, comparable to global datasets, with detailed environmental characterization. This should permit identification of environmental and genetic vulnerabilities to psychopathology within a developmental framework. Neuroimaging and neuropsychological data from this study are already yielding insights on brain growth and maturation patterns. 2019 The Author(s). -
Constraining the physical parameters of XTE J1701-462 through NuSTAR observations
The spectral properties of the transient neutron star low-mass X-ray binary XTE J1701-462 were studied using the data obtained from FPMA/B detectors onboard NuSTAR during its second known outburst (2022 September). The physical parameters of the system were derived from the analysis of the data in the 3.0-30.0 keV energy range. The patterns displayed on the hardness-intensity diagram of the three observations closely resembled the banana branch/normal branch, a vertex of horizontal and normal branch of the Z-track and a transition from normal branch to flaring branch. Spectral analysis of the source revealed the presence of Fe K emission complex. The source spectra were fitted with a multitemperature blackbody () component in conjunction with the reflection model (). The values of temperature (kTin) and radius (Rin) of the inner accretion disc obtained from the spectral fitting with the model combination - + showed the source to be in its soft spectral state during the observations. The inclination angle (?) of the source was estimated to be between 19 and 33 and the inner disc radius (Rin) was found to be 17.4 km. Assuming the case of magnetic truncation of accretion disc, the upper limits for the magnetic dipole moment (?) and the magnetic field strength (B) at the poles of the neutron star in the system were found to be 5.78 1026 G cm3 and 8.23 108 G, respectively, for kA = 1. 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. -
Constraint Governed Association Rule Mining for Identification of Strong SNPs to Classify Autism Data
Autism is a heterogeneous neuro developmental disorder found among all age groups. Nowadays more patients are detected with autism but very less awareness is prevailing in the society related to it. This paved a way for many researchers to carry out serious study on autism and its characteristics. Studying behavior and characteristics of Autistic patients is very important for diagnosing the level of autism. Classifying the association of different characteristic in autistic patients at gene level using machine learning techniques can give an important insight to the doctors and the care takers of the patients. Research is being carried out to identify the genes responsible for autism. The changes in gene sequence may lead to different characteristics in different people. Thus genotypic research is found to reveal well defined insight about various characteristics in autistic patients and their associations with genes. Single Nucleotide Polymorphism (SNP) being high in features indicate human genome variability and is associated with identification of traits for many human diseases including autism. The main aim of the proposed work is to identify SNP sequences which are responsible for carrying the autistic traits. This paper explore the application of Constraint Governed Association Rule Mining (CGARM) technique on SNP data for dimensionality reduction and thereby selecting the strong predominant SNP features which are relevant enough to accomplish classification with high accuracy. The research work incorporates the application of CGARM and is carried out in two stages. In the first stage CGARM was used to choose significant SNP features resulting in dimensionality reduction. In the second stage classification was carried out by subjecting the selected features to Artificial Neural Network (ANN) algorithm. The main advantage of the proposed work is its ability to reduce the dimensions without compromising the quality i.e. using CGARM strong SNPs were selected by applying various constraints like Syntactical constraints, Semantical constraints and Dimensionality Constraints resulting in higher accuracy. The CGARM technique is applied on Autism data collected from National Center for Biotechnology Information (NCBI) repository. The data is divided into a set of 118 features, out of 118 features CGARM contributed in identifying 22 predominant SNPs. Further by applying forward selection method top 17 features were selected and were given as input to ANN. The 10 fold cross validation resulted in 76.9% accuracy which was found to be 50% more than that of original features. The proposed work contributed in reducing the dimension by 85% and provided 76.9% accuracy with the help of only 15% features. 2020 IEEE. -
Constraints on the Labour Market Trajectory of Youth and Growth of NEET in India
This paper explores the trends, composition, and determinants of the rising Not in Employment, Education and Training (NEET) population in India. Based on the national level employment-unemployment surveys and macro level panel data, and using instrumental variable (IV) Probit and system generalized method of moments (GMM) regression models, it is explored that a set of supply and demand side factors determining the growth of NEET population in India. At the micro level, the individuals level of general education, technical and vocational training, gender, occupation and gender of head of the family, religion, standard of living of the family, earnings of the spouse, and a set of complex socio-cultural factors determine the NEET status of educated and trained youth. On the other hand, the macro level factors, including the growth of mechanization in agriculture, stagnant real wages, sluggish non-farm sector output growth, infrastructural backwardness, and the existing social-cultural setup in which educated youth live together create a negative macro level environment that compels them to remain out of the workforce for a longer period even after completion of their education/training. Based on these results, it is argued that policies aiming at the development of infrastructure along with the promotion of industry and modern service sectors should be given the top priority for checking the upsurge in the NEET population in India. 2023 XLRI Jamshedpur, School of Business Management & Human Resources. -
Construct modelling, statistical analysis and empirical validation using PLS-SEM: a step-by-step guide of the analysis procedure
Partial least square-structured equation modelling (PLS-SEM) is a widely accepted tool for statistical analysis in social science research. The complex architecture of PLS-SEM sometimes makes it difficult for users to understand the taxonomy, nomenclature, or process of statistical analysis. This research study proposes summarising the procedure adopted in PLS-SEM for data analysis. Measurement evaluation and structural model was the subject of discussion, with a focus on the statistical techniques employed. Furthermore, the threshold values corresponding to statistical tools under measurement and structural model were also provided. The inference of these threshold values were also discussed with an eye on improving researchers awareness and understanding. The discussion about the methodology adopted in statistical analysis with the help of PLS-SEM is also reported. Finally, the limitations of the research work were presented, and further study directions were streamlined. 2024 Inderscience Enterprises Ltd.