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Integrated Automated Attendance System with RFID, Wi-Fi, and Visual Recognition Technology for Enhanced Classroom Security and Precise Monitoring
The integrated automated smart attendance system utilizes RFID, Wi-Fi, and visual recognition technologies to elevate classroom security and ensure precise monitoring of attendance records. It consolidates cutting-edge components such as RFID tags, ESP8266 Wi-Fi modules, ESP-32 CAM modules, solenoid locks, servo motors, and PIR sensors to devise a strong remedy. RFID technology enables accurate attendance tracking by assigning tags to students and faculty members. The Wi-Fi and visual recognition components enhance the system's functionalities, facilitating wireless connectivity, instantaneous data transfer, and validation of identities. Solenoid locks and servo motors ensure controlled access, responding to validated attendance records. PIR sensors detect motion, contrasting between genuine presence and proximity. The paper's methodology delineates the necessary hardware and software requirements, procedures for system initialization, testing phases, establishment of server connectivity, implementation of access control mechanisms, and formulation of end-of-session protocols. It highlights the successful integration and validation of hardware components, backend connectivity, identity confirmation, attendance recording, data encryption, and session termination procedures. The research aims to modernize attendance tracking in educational settings, improving efficiency, accuracy, and security while appreciating the need for further adaptation to suit diverse educational environments for broader adoption and sustained advancement. 2024 IEEE. -
Integrated biorefinery development for pomegranate peel: Prospects for the production of fuel, chemicals and bioactive molecules
Current experimental evidence has revealed that pomegranate peel is a significant source of essential bio compounds, and many of them can be transformed into valorized products. Pomegranate peel can also be used as feedstock to produce fuels and biochemicals. We herein review this pomegranate peel conversion technology and the prospective valorized product that can be synthesized from this frequently disposed fruit waste. The review also discusses its usage as a carbon substrate to synthesize bioactive compounds like phenolics, flavonoids and its use in enzyme biosynthesis. Based on reported experimental evidence, it is apparent that pomegranate peel has a large number of applications, and therefore, the development of an integrated biorefinery concept to use pomegranate peel will aid in effectively utilizing its significant advantages. The biorefinery method displays a promising approach for efficiently using pomegranate peel; nevertheless, further studies should be needed in this area. 2022 Elsevier Ltd -
Integrated Effect of Flow Field Misalignment and Gas Diffusion Layer Compression/Intrusion on High Temperature - Polymer Electrolyte Membrane Fuel Cell Performance
Misalignment in the flow field plates of High-Temperature Polymer Electrolyte Membrane Fuel Cell (HT-PEMFC) due to manufacturing tolerances, assembly process, or unavoidable vibration during the cell operation is contemplated its performance and durability. This study investigates the effect of flow field plate misalignment and its concomitant impact with varying the clamping pressures on HT-PEMFC operation. The study considers six degrees of cathode flow field misalignment, varying from 0% to 100% with respect to the anode flow field. Clamping pressures ranging from 1 to 2 MPa are applied to the various cases of misalignment to study their effect on GDL deformation and intrusion into the channels. The structural analysis shows that as the misalignment increases from 0 to 100%, the GDL compression increases from 26.72% to 37.75% for 1 MPa, 40.07% to 56.63% for 1.5 MPa, and 53.43% to 75.51% for 2 MPa, owing to the increase in compression approximately by 41% from their base cases and it is also crucial to note that GDL compression exaggerates at higher clamping pressures. The misalignment results in the sagging of Membrane Electrode Assembly (MEA), and the amplitude of wave nature is proportional to the degree of misalignment and clamping pressure, indicating the misalignment is the sole factor for structural changes. As a result, considerable variance in current distribution and average value is observed, i.e., at operating voltage 0.5 V, the current density drops from 4472.7 to 4264.4, 4420.7 to 4211.8, and 4374.1 to 4161.3 A m?2 from cases 1 to 6 for clamping pressures 1, 1.5, and 2 MPa, respectively, resulting in a 4.7% loss in performance. According to the observations, a misalignment of 60% is tolerable, with minimal performance loss and negligible non-uniformity in cell distributions. 2022 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. -
Integrated fuzzy AHP and TOPSIS as innovative student selection methodology at institutions of higher learning
BACKGROUND: The selection of students at academic institutions has been a challenging affair given multiple criteria that need to be considered by the institution. Additionally, multiple evaluators and decision makers are involved in the student selection process, rendering it inconsistent. The complexity and subjectiveness in such decisions making requires new and innovative approach in order to be more systematic and transparent. OBJECTIVE: This paper presents an innovative methodology for student selection for admission into an Institute of Higher Learning (IHL) using Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Drawing on the success of using these methods in other fields, this study applies the technique and principles on student selection process. METHOD: Fuzzy Analytical Hierarchy Process (FAHP) is used in determining the weights of the criteria by the decision makers which avoids the vagueness and inconsistencies in decision making process and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method ranks finds out the best alternative solution for student selection by calculating the relative closeness from the positive ideal solution. RESULTS AND CONCLUSION: This research finds using the hybrid method is effective in student selection for IHL and makes the process efficient and bias-free. This method can be applied to various fields and uses where multi-criteria decision making is involved. 2023 - IOS Press. All rights reserved. -
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. -
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 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 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 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 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 photonic devices for cancer detection
[No abstract available] -
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 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 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. -
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. -
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 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 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 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 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.