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Integration of 0.1 GHz to 40 GHz RF and microwave anechoic chamber and the intricacies
The aim of this paper is to highlight and elaborate the construction and establishment of a rectangular anechoic chamber (AC) of dimensions 7 m 4 m 3 m working from 0.1 GHz to 40 GHz. It is an informative checklist giving an insight on the reckoning of chamber dimensions and selection of appropriate absorbers as per the required specifications. It briefs the key features of validation of an anechoic chamber, namely, shielding effectiveness and reflectivity (quiet zone). It describes the intricacies of the integration of systems such as vector network analyzer (VNA), antenna mounting stands, three-axes motorized antenna rotation control circuitry, and customized software. The validation of the established chamber is accomplished for overall shielding effectiveness of ?80 dB and reflectivity of ?40 dB in one cubic meter area at the receiving antenna or the antenna under test (AUT) region far away from transmitter say, at 5.5 m separation. This paper covers the measurement results of three broadband horn antennas which can be used as reference antennas for characterization of other antennas in the chosen frequency range. The entire report will certainly be a guideline for any reader or aspirant who is interested in the development of a similar anechoic chamber and looking for complete intricacies. 2020, Electromagnetics Academy. All rights reserved. -
Integrating Traditional Healing Practices with Cognitive Therapy: Attitude, Preparedness and Perceived Effectiveness among Clients and Therapists
Mental health and well- being has become a serious concern in the Indian health setting. The mental health care has been rapidly increasing. The various approaches involved in mental health has been explored widely in the Indian mental health setting. This research study aims to explore the integrated approach which involves traditional healing practices and cognitive therapy. The aim of this research study is to understand the three main variables attitude, preparedness and perceived effectiveness in clients and therapists while integrating traditional healing practices with cognitive therapy. The traditional healing practices explored in this study are yoga, meditation and mindfulness. The attitude of the clients and therapists towards the integrated approach has been studied. The preparedness of the clients as well as the preparedness of the therapists toward the integrated approach is also the next set of objectives in the research study. The next two objectives have been to study the perceived effectiveness of this approach in clients and therapists. The research study is a qualitative study. The data for the research study has been collected using semi- structured interviews. The data has been analyzed using thematic content analysis. The sample for the study includes 5 therapists and 10 clients who have been involved in this therapeutic approach. The results of the study show that there are two types of attitude clients who have interviewed hold towards the integrated approach. The two types of attitude include positive attitude and apprehensive attitude. The attitude of the therapists towards the approach has been positive and the factors which have led to the positive attitude has been cultural factors, familial background and previous exposure. The apprehensive attitude in clients have been due to the forced participation and past negative experience. The positive attitude of the therapists has been due to prior training and prior positive results. The preparedness and perceived effectiveness observed in therapists and clients have also been studied at length in the research study. The preparedness observed in clients has been due to previous exposure and knowledge and in therapists it has been due to extensive practice and the perceived effectiveness seen in clients. The perceived effectiveness observed in clients have been at three levels. They are physiological well- being, psychological well- being and improved relationships in the family. The perceived effectiveness in therapists have been seen as increased emotional and physical well- being as well as increased competence in the profession. -
Integrating spiritual disposition intervention into behavioral medicine: A case report on systemic lupus erythematosus from India
Background: Systemic Lupus Erythematosus (SLE) is a chronic inflammatory systemic autoimmune disease. The disease manifests as the bodys immune cells start attacking healthy connective tissue, which affects the skin, kidneys, blood vessels, brain, and other vital organs. As with any other chronic illness, the disease has psychological implications. Purpose: Literature suggests patients with SLE experience anxiety, depression, anger, and stress along with physiological symptoms. There is a strong association between the occurrence of stress and the onset of the disease. These psychological symptoms can be ameliorated through spiritual activities such as meditation, mindfulness, journaling, and reading. Mehtod: This case report is based on the importance of spirituality in the healthcare system. The study focuses on the concept of a whole-person-centered approach to the medical care industry. Spirituality has been proven to have a positive effect on health and illness. Hence, a 10-week intervention with 30 sessions focusing on spiritual dispositions was provided to the patient for this study, along with regular pharmacological treatment. The present case report is of a 56-year-old woman from New Delhi, India, who was diagnosed with SLE 2years ago. Results: The results reveal the positive effect of the intervention, as it led to a significant decrease in stress levels and depressive symptoms; it also resulted in improved quality of life, an enhanced coping style, and bolstered health hardiness. There was an increase in the score of a spiritual personality. Conlcusion: Spiritual Disposition as an intervention was sucessfull in reducing psychological implications of the disease thus leading to overall positve growth in the patient. The Author(s) 2024. -
Integrating rod-shaped nickel molybdate@polypyrrole matrix for sustainable adsorptive removal of organic dye: Kinetics, isotherm, and thermodynamics study
Water pollution presents a significant global challenge that impacts the environment. The release of industrial effluents significantly contributes to this. Adsorption studies offer a sustainable and cost-effective solution to efficiently remove organic pollutants from water. The current study comprises a polypyrrole/nickel molybdate composite for the effective adsorption of organic dyes, such as methylene blue, from aqueous solutions. The catalyst has been comprehensively characterized using various techniques, including XRD, FE-SEM, FT-IR, HR-TEM, XPS, BET, TGA, zeta potential, and DLS analysis. Adsorption studies demonstrate up to 97% removal efficiency in 60 min. This study also evaluates the impact of various parameters, such as temperature, pH, dye concentration, and quantity of the catalyst, on the adsorption efficiency. The R2 value of 0.99 that is obtained in the kinetics study suggests the suitability of the adsorption process toward pseudo-second-order kinetics. The adsorption isotherm study reveals that the adsorption follows Freundlich's adsorption isotherm. The maximum adsorption capacity of the study is found to be 17.76 mg/g. Investigations into thermodynamic study give a ?H value of ?19.21 J/mol K, indicating the exothermic behavior, and ?G of ?6.95 KJ/mol, suggesting the spontaneity of the composite during the adsorption process. These results demonstrate the potential of the developed material as an effective adsorbent for removing organic dyes from water sources. 2023 Wiley Periodicals LLC. -
Integrating mindfulness and addiction awareness in higher education: Strengthening resilience and promoting well-being
This chapter explored integrating mindfulness and addiction awareness within higher education. The journey uncovers these practices' profound potential in enhancing student resilience and well-being. The transformative impact of a mindful approach is underscored by examining their symbiotic relationship, individual benefits, and intersection with microlearning. From understanding addiction's prevalence among students to fostering a compassionate learning environment, the discussion navigates ethical considerations, cultural sensitivity, and challenges. A resounding call to action resonates, urging higher education institutions to embed these practices strategically, cultivating an environment prioritizing holistic student growth and development. The promise lies in a brighter future-a generation of self-aware, resilient individuals empowered to navigate challenges with poise, empathy, and well-being. 2024, IGI Global. -
Integrating machine learning techniques for Air Quality Index forecasting and insights from pollutant-meteorological dynamics in sustainable urban environments
Air pollution poses a significant environmental and health challenge in Delhi, India. This research focuses on predicting the Air Quality Index (AQI) for Delhi utilizing machine learning techniques. The research methodology encompasses comprehensive steps such as data collection, preprocessing, analysis, and modeling. Data comprising various pollutants and meteorological parameters were gathered from the Central Pollution Control Board (CPCB) spanning from January 1, 2016, to December 30, 2022. Missing values were imputed using the IterativeImputer method with RandomForestRegressor as the estimator. Data normalization and variance reduction were achieved through Box-Cox transformation. Spearman Rank Correlation analysis was employed to explore relationships between features and AQI. Initial evaluation of nine machine learning algorithms identified Random Forest and XGBoost as the top performers based on accuracy. These algorithms were further optimized using 5-fold cross-validation with RandomizedSearchCV. The results demonstrated the efficacy of both algorithms in AQI prediction. Notably, PM2.5 and CO concentrations emerged are most influential features, highlighting the potential for AQI improvement in Delhi through the reduction of these pollutants. This research distinguishes itself through a meticulous examination of the complex interconnections between pollutants and AQI, providing invaluable insights to inform targeted interventions and enduring policies geared towards improving air quality in Delhi. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Integrating dye-sensitized solar cells and supercapacitors: portable powerpacks for future energy applications
Integrating energy storage and harvesting devices have been major challenges and significant needs of the time for upcoming energy applications. Photosupercapacitors are combined solar cell-supercapacitor devices which can provide next-generation portable powerpacks. Owing to advantages like economic and environmental friendliness, dye-sensitized solar cells (DSSCs) offer vast potential for being integrated with energy accumulation devices like supercapacitors. Over the past few years, various types of harvesting cum storage power devices combining DSSCs and supercapacitors have been reported. Over time the devices have improved in both performance and stability providing a broad outlook to possible future advancements including commercialization. We still have many challenges that are yet to be resolved in order to take these powerpacks to the next level of applications in portable and wearable electronics and communication devices. In this context, a detailed analysis and comparison of already reported photo-powered integrated supercapacitors based on DSSCs would give further insights into future advancements. In this review, we have discussed the development of photosupercapacitors, their fabrication strategies, and different materials used as counter electrodes, electrolytes, and dye sensitizers. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Integrating deep learning in an IoT model to build smart applications for sustainable cities
These days, many CS experts focus their efforts on IoT. IoT is an emerging & cutting-edge technology that enables many items, including vehicles and home appliances, to connect and cooperate via mechanisms like machine to machine communication, big data, and AI. It has found use in a wide range of settings, from smart homes and cities, to healthcare and agriculture, to factory automation. Smart cities are becoming smarter, cars are getting more features, and health and fitness devices are getting more sophisticated thanks to the internet of things. Many problems that are directly relevant to the IoT's development have yet to be resolved. The exponential development of IoT has given birth to new problems, including concerns about personal data and security. There is need of a comprehensive approach that tackles the scalability, security, efficiency, and privacy concerns raised by the widespread deployment of IoT. 2023, IGI Global. -
Integrating AI Tools into HRM to Promote Green HRM Practices
The image of Human Resource Management (HRM) is undergoing a drastic transformation. The conventional methods are evolving due to the emergence of technology, especially with the integration of Artificial Intelligence (AI) and data analytics into the HR processes. With the rapidly changing concept of the overall growth of an organization, AI is becoming a vital stimulant for sustainable growth. AI-powered tools promote data-driven decision-making for talent acquisition, performance management, workforce training and development, optimization of energy consumption and waste reduction. Green HRM aligns these efforts by integrating sustainability considerations into talent management strategies, nurturing employees eco-engagement, and promoting environmentally responsible practices within the workforce. This research paper aims to explore the synergies between AI tools and Green HRM practices, investigating how the integration of AI technologies into HR processes can contribute to the promotion of environmental sustainability. By examining real-world case studies, this study aims to investigate the potential of AI-powered solutions in shaping the future of HRM through the lens of sustainability. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Integrating AI and Cybersecurity: Advancing Autonomous Vehicle Security and Response Mechanisms
The rapid evolution of autonomous and connected vehicles has led to their integration with numerous technologies and software, rendering them vulnerable targets for cybersecurity attacks. While efforts have traditionally focused on preventing these attacks, the escalating risk underscores the importance of also vindicating their wallop. Nevertheless, this procedure is often onerous & facade scalability confronted, particularly due to connectivity issues in automobiles. This research advises a vehicle-based vibrant imposition response scheme, enabling swift responses to a variety of incidents and reducing reliance on external security centers. The classification encompasses an inclusive range of probable retorts, a procedure for evaluating retorts, & innumerable assortment approaches. Implemented on an embedded platform, the solution was evaluated using two distinct cyberattack use cases, highlighting its adaptability, responsiveness, volume for dynamic arrangement constraint alterations & nominal memory trail. Concurrently, this paper presents an innovative (AVSF) that synergistically integrates (AI) and cybersecurity techniques to fortify AV resilience against evolving threats. Additionally, the framework incorporates advanced cybersecurity measures such as encryption, authentication, and intrusion detection to mitigate vulnerabilities and safeguard critical AV systems. The fusion of AI and cybersecurity not only enhances AV security posture but also enables intelligent cyber threat monitoring and response capabilities. Extensive simulations and experimental evaluations demonstrate the efficacy of the AVSF in real-time scenarios, contributing to the development of robust security solutions for autonomous vehicle deployment and advancing safer transportation systems in the era of AI-driven mobility. 2024 IEEE. -
Integrated synchronous buck converter emulation and method of design thereof /
Patent Number: 201941035816, Applicant: Jayanta Biswas.
The present invention is related to the Buck converter output ripple voltage analysis field, more particularly, the present invention is related to integrated synchronous buck converter emulation and method of design thereof. A DC-DC synchronous buck converter is emulated on FPGA based on geometric model of average inductor current. -
Integrated Synchronous buck converter emulation and method of design thereof /
Patent Number: 201941035816, Applicant: Jayanta Biswas.
The present invention is related to the Buck converter output ripple voltage analysis field, more particularly, the present invention is related to integrated synchronous buck converter emulation and method of design thereof. A DC-DC synchronous buck converter is emulated on FPGA based on geometric model of average inductor current. The integrated synchronous buck converter achieves precise regulation of the output voltage to fulfill the requirements of DVS applications. -
Integrated skills for parenting the adolescents (ISPA): An intervention to strengthen parent- adolescent relationship /
Review of Neuropsiquiatrica, Vol.76, Issue 4, pp.413-422, ISSN No: 1609-7394. -
Integrated photonic devices for cancer detection
[No abstract available] -
Integrated IoT-Based Secure and Efficient Key Management Framework Using Hashgraphs for Autonomous Vehicles to Ensure Road Safety
Autonomous vehicles offer various advantages to both vehicle owners and automobile companies. However, despite the advantages, there are various risks associated with these vehicles. These vehicles interact with each other by forming a vehicular network, also known as VANET, in a centralized manner. This centralized network is vulnerable to cyber-attacks which can cause data loss, resulting in road accidents. Thus, to prevent the vehicular network from being attacked and to prevent the privacy of the data, key management is used. However, key management alone over a centralized network is not effective in ensuring data integrity in a vehicular network. To resolve this issue, various studies have introduced a blockchain-based approach and enabled key management over a decentralized network. This technique is also found effective in ensuring the privacy of all the stakeholders involved in a vehicular network. Furthermore, a blockchain-based key management system can also help in storing a large amount of data over a distributed network, which can encourage a faster exchange of information between vehicles in a network. However, there are certain limitations of blockchain technology that may affect the efficient working of autonomous vehicles. Most of the existing blockchain-based systems are implemented over Ethereum or Bitcoin. The transaction-processing capability of these blockchains is in the range of 5 to 20 transactions per second, whereas hashgraphs are capable of processing thousands of transactions per second as the data are processed exponentially. Furthermore, a hashgraph prevents the user from altering the order of the transactions being processed, and they do not need high computational powers to operate, which may help in reducing the overall cost of the system. Due to the advantages offered by a hashgraph, an advanced key management framework based on a hashgraph for secure communication between the vehicles is suggested in this paper. The framework is developed using the concept of Leaving of Vehicles based on a Logical Key Hierarchy (LKH) and Batch Rekeying. The system is tested and compared with other closely related systems on the basis of the transaction compilation time and change in traffic rates. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
Integrated intelligent framework for e-learning
E-learning is the primary method of learning for most learners after regular academics studies. Knowledge delivery through e-learning technologies increased exponentially over the years because of the advancement in internet and e-learning technologies. Knowledge delivery to some people would never have been possible without the e-learning technologies. Most of the working professionals do focused studies for carrier advancement, promotion, or for improving domain knowledge. These learners can find many E-learning is the primary method of learning for most learners after regular academics studies. Knowledge delivery through e-learning technologies increased exponentially over the years because of the advancement in internet and e-learning technologies. Knowledge delivery to some people would never have been possible without the e-learning technologies. Most of the working professionals do focused studies for carrier advancement, promotion, or for improving domain knowledge. These learners can find many free e-learning web sites from the internet easily in the domain of interest. However, it is quite difficult to find the best e-learning content suitable for their learning based on their domain knowledge level. Users spent most of the time figuring out the right content from a plethora of available content and end up learning nothing. A framework using machine learning algorithms with Random Forest Classifier is proposed to address the issue, which classifies the e-learning content based on its difficulty levels and provides the learner the best content suitable based on the knowledge level. The framework is trained with the data set collected from multiple popular e-learning web sites. The model is tested with real-time e-learning web site links and found that the e-contents in the web sites are recommended to the user based on its difficult levels as beginner level, intermediate level, and advanced level. -
Integrated intelligent framework for e-learning
E-learning is the primary method of learning for most learners after regular academics studies. Knowledge delivery through e-learning technologies increased exponentially over the years because of the advancement in internet and e-learning technologies. Knowledge delivery to some people would never
have been possible without the e-learning technologies. Most of the working professionals do focused studies for carrier advancement, promotion, or for improving domain knowledge. These learners can find many free e-learning web sites from the internet easily in the domain of interest. However, it is quite
difficult to find the best e-learning content suitable for their learning based on their domain knowledge level. Users spent most of the time figuring out the right content from a plethora of available content and end up learning nothing. A framework using machine learning algorithms with Random Forest Classifier
is proposed to address the issue, which classifies the e-learning content based on its difficulty levels and provides the learner the best content suitable based on the knowledge level. The framework is trained with the data set collected from
multiple popular e-learning web sites. The model is tested with real-time elearning web site links and found that the e-contents in the web sites are recommended to the user based on its difficult levels as beginner level, intermediate level, and advanced level.
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Integrated hybrid membrane system for enhanced water treatment and desalination for environmental preservation
Technology advancements in desalination, water treatment, and energy efficiency are crucial to preserving our planet. It is critical to find solutions for the future that save natural resources and lessen environmental damage because the freshwater shortage is getting worse, and energy demand is increasing. They face various obstacles, even though their breakthroughs are extremely important. Lot of energy can be utilized for the traditional desalination techniques, as it negatively impacts the environment. Then, the process of the existing Water Treatment (WT) are expensive and ineffective. An Integrated Hybrid Membrane System for Enhanced WT (IHMS-EWT) is a unique technique for WT and desalination was suggested in this study. The integration of many membrane procedures like nanofiltration, reverse and forward osmosis, and membrane distillation, and these will helps in facilitating the best WT and desalination methods. Due to the incorporating Renewable Energy (RE), the IHMS-EWT also demonstrates the (SWMS) Sustainable Water Management System, as it enhances the EE and thereby reducing the environmental impact. The great potential in the wide range of applications was offered by the IHMS-EWT technique. Providing the decentralized WT solutions in the remote areas, this unique approach has the ability to reduce the fresh water scarcity in the coastal areas based on the demands of the municipal, industrial and agricultural demands. The environmental sustainability throughout the lenghthy operations was ensured by the support of IHMS-EWT. It also helps in providing resilience in the crisis situations. The cost-effective evaluations, operating parameter optimization, and performance prediction of the method was enabled by employing the computational modelling. Through simulatimg different contexts, the effective configurations and operational techniques are focussed on the study for enhancing the IHMS-EWT technology.The model shift in the SWM, the IHMS-EWT technique addresses the main problems and brings one step for more secure environment. Comparing to other existing methods, Improving the water purification by 98.2 %, 94.2 % efficiency rate, the EC prediction rate of 96.2 %, the cost-effectiveness rate by 82.4 % and the performance rate by 96.7 % by the suggested IHMS-EWT model and it was demonstrated by the outcomes of the experiment. 2024 The Authors -
Integrated Home-Based Palliative Care in Motor Neuron Disease: A Case Report from Low- Middle Income Country
In many international care guidelines, multidisciplinary palliative care forms a key to optimum management in Motor Neuron Disease (MND). We describe the home-based palliative care interventions for a client with MND and his family from a Low and Middle-income country context. This report also discusses the advantages and challenges of the same with suggestions for sustaining the quality of care for neuro palliative conditions. 2021 Taylor & Francis Group, LLC. -
Integrated Health Care Delivery and Telemedicine: Existing Legal Impediments in India
The technological innovation in the healthcare sector has contributed to the growth of telemedicine in India. Health services fall under State responsibility as per the Indian Constitution by virtue of Schedule 7although policy and planning framework are under the scope of Central government. Telemedicine cannot not work as an autonomous service, rather, ought to be subjected to different regulations having complex ethical, medico-legal manifestations. As far as India is concerned, Ministry of Health and Family Welfare of India (MoHFW) is the body responsible for initiating the policy of digitization of healthcare. However the point ishow far digital health services going appropriately in India. Based on NDHBs comprehensive architectural framework of Federated National Health Information System in January 2020 and as the pandemic strategy Medical Council of India and the NITI Aayog released new guidelines on telemedicine with respect to registered medical practitioners, this research needed to be checked. Thus, the examination was done in these aspects. Guidelines were revisited to see how the hospitals in Delhi and NOIDA function based on the records submitted in medical consultation given to patients using telemedicine. It is felt that telemedicine being a nebulous concept in India, it needs to be analyzed in the light of prospective opportunities it would offer. There is a need for collaborative approaches on digital health, revision in the prevailing legal and ethical frameworks, the clinical practices corresponding to standing medical guidelines. Also, it is found that there exist no uniform telemedicine practices balancing the privacy norms, medico-legal responsibility and regulatory standards. To arrive at conclusion, the best practices prevailed in other countries are examined and adopted. It is felt that the policies existing in telemedicine need to be bifurcated as digital consultation, digital photography, remote patient monitoring (RPM) separately. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.