Usefulness of the Four Score Coma Scale in Children Admitted at an Intensive Care Unit of a Referral Centre

INTRODUCTION: Consciousness is the state of awareness of both one’s own self and his environment. A child who has a normal state of consciousness can be awakened and also aware of what is happening in and around her or himself. Altered level of consciousness is the impairment of the ability to maintain awareness of self and environment, and respond to environmental stimuli. Understanding of normal level of consciousness is necessary for the evaluation of abnormalities in a child’s behaviour. ALOC usually begins with reduced awareness of one’s self, followed by reduction in awareness of the environment, and finally by inability to aroused. The opposite of consciousness is coma, a state in which a person is unresponsive to all stimuli, including pain. Although consciousness and coma represents the extremes of mental status, there are many abnormal states of consciousness along that spectrum that may, at times, blunt imperceptibility into one another. Confusion occurs when there is a loss of clear thinking, usually manifested by impairment of cognitive abilities and decision making. Disorientation often accompanies confusion. In general, disorientation to time occurs first, followed by disorientation to place, and then by deficiency in short term memory. Loss of recognition of one’s self is a latter finding. In delirium, there is a succession of confused and unconnected ideas. Delirious children often have extreme mental and motor excitement, so they become disoriented, fearful, irritable, offensive, or agitated. AIM OF THE STUDY: To determine whether the FOUR (Full outline of unresponsiveness) score is an accurate predictor of outcome in children with altered level of consciousness. DISCUSSION: In this study we prospectively examined in 173 children in the age group of 6 months to 12 years. This is slightly different from Jennifer Cohen et al., study, done in 70 children between the age group of 2 to 18 years.46 We observed in our study among the four variables of the FOUR score; respiration has the least correlation with total score compared with other variables (eye response, 0.91; motor response, 0.89; brainstem reflexes, 0.84; and respiration, 0.76). This can be explained by the fact that 85% of children were in mechanical ventilation support in our study and in a child under mechanical ventilation, only two patterns were included in the scoring; either “apnea or triggered ventilation”, which could have lead a poor correlation with the total score. While applying the normal functioning motor scale of FOUR score, we noted some difficulty in less than 2 years, because the developmental differentiation of language and motor milestones in this age group interference with assessment of response. So we used in our study, spontaneous movement/ obey commands instead of thumbs up, fist or peace sign as in original validation study. 34, 40 In our study, we observed there was no statistically significant different in the mean FOUR score among the age group, sex and place of referral. We also noted there was significant difference in the mean FOUR score with respect to duration of hospitalisation, mechanical ventilation and diagnosis. CONCLUSION: 1. The FOUR score is able to accurately predict outcome in children with altered level of consciousness admitted at paediatric intensive care unit with respect to in-hospital mortality and survival at discharge. 2. The score is uniformly applicable to different age groups and to different aetiological factors that resulted in altered level of consciousness

A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users

Rapid growth of web and its applications has created a colossal importance for recommender systems. Being applied in various domains, recommender systems were designed to generate suggestions such as items or services based on user interests. Basically, recommender systems experience many issues which reflects dwindled effectiveness. Integrating powerful data management techniques to recommender systems can address such issues and the recommendations quality can be increased significantly. Recent research on recommender systems reveals an idea of utilizing social network data to enhance traditional recommender system with better prediction and improved accuracy. This paper expresses views on social network data based recommender systems by considering usage of various recommendation algorithms, functionalities of systems, different types of interfaces, filtering techniques, and artificial intelligence techniques. After examining the depths of objectives, methodologies, and data sources of the existing models, the paper helps anyone interested in the development of travel recommendation systems and facilitates future research direction. We have also proposed a location recommendation system based on social pertinent trust walker (SPTW) and compared the results with the existing baseline random walk models. Later, we have enhanced the SPTW model for group of users recommendations. The results obtained from the experiments have been presented

A Hybrid Linear Iterative Clustering and Bayes Classification-Based GrabCut Segmentation Scheme for Dynamic Detection of Cervical Cancer

Cervical cancer earlier detection remains indispensable for enhancing the survival rate probability among women patients worldwide. The early detection of cervical cancer is done relatively by using the Pap Smear cell Test. This method of detection is challenged by the degradation phenomenon within the image segmentation task that arises when the superpixel count is minimized. This paper introduces a Hybrid Linear Iterative Clustering and Bayes classification-based GrabCut Segmentation Technique (HLC-BC-GCST) for the dynamic detection of Cervical cancer. In this proposed HLC-BC-GCST approach, the Linear Iterative Clustering process is employed to cluster the potential features of the preprocessed image, which is then combined with GrabCut to prevent the issues that arise when the number of superpixels is minimized. In addition, the proposed HLC-BC-GCST scheme benefits of the advantages of the Gaussian mixture model (GMM) on the extracted features from the iterative clustering method, based on which the mapping is performed to describe the energy function. Then, Bayes classification is used for reconstructing the graph cut model from the extracted energy function derived from the GMM model-based Linear Iterative Clustering features for better computation and implementation. Finally, the boundary optimization method is utilized to considerably minimize the roughness of cervical cells, which contains the cytoplasm and nuclei regions, using the GrabCut algorithm to facilitate improved segmentation accuracy. The results of the proposed HLC-BC-GCST scheme are 6% better than the results obtained by other standard detection approaches of cervical cancer using graph cuts

A Comprehensive Framework for Direct Lightning-Structure-Human Interaction Modelling in Heritage Monuments and Safety Assessment

Lightning is a perilous and unavoidable event of nature that presents major deleterious consequences on humans, tall structures, electrical power systems, forests, etc. Though several research studies have been carried out to analyse the sufficiency of a Lightning Protection System (LPS), very few research findings have been reported to assess the extent of risk due to lightning-human interaction in the vicinity of tall structures. This research aims at carrying out detailed modelling and simulation studies of LPS for heritage structure. Several current waveshapes as stipulated in IEC 62305 are modelled appropriately and presented to the electrical equivalent circuit representation of a heritage monument in South India (Brihadisvara Temple) to ascertain the impact of lightning parameters on heritage monuments. In addition, to assess the effectiveness of the earthing system, detailed earthing models during lightning is developed to assess the role played by aspects such as soil resistivity (single and double), earth electrode dimensions, nature of elements in the equivalent circuit, etc. Further, the role of lightning strikes on human due to step and touch potential is ascertained by formulating a lumped electrical equivalent model of human to assess its role and impact on dry and wet skin

Comparative Study of DC-DC Converters for Solar PV with Microgrid Applications

This review emphasizes the role and performance of versatile DC-DC converters in AC/DC and Hybrid microgrid applications, especially when solar (photo voltaic) PV is the major source. Here, the various converter topologies are compared with regard to voltage gain, component count, voltage stress, and soft switching. This study suggests the suitability of the converter based on the source type. The merits of a coupled inductor and interleaved converters in micro gird applications are elucidated. The efficiency and operating frequencies of converts for different operating modes are presented to determine the suitable converters for inductive and resistive loads. The drawbacks of converters are discussed. Finally, the mode of operation of different converts with different grid power sources and its stability and reliability issues are highlighted. In addition, the significance of the converter’s size and cost-effectiveness when choosing various PV source applications are discussed

Flyback converter employed non-dissipative cell equalization in electric vehicle lithium-ion batteries

The effective and dependable usage of rechargeable batteries has emerged as a central topic for automobile manufacturers in the wake of the rise of electric vehicle technology. When it comes to rechargeable batteries with high specific energy and specific power, lithium-ion battery technology is the most well-known. The low terminal voltage battery cells in the lithium-ion battery pack are linked in series to provide the necessary voltage for the electric vehicle system. The low charge cell in the string limits the usable capacity of the battery pack, though. Disturbances in the battery pack's charge are due to variations in manufacturing quality and to the unique operating circumstances of each individual cell. These inconsistencies cause a decline in usable capacity, a quickening of cell deterioration, and, most significantly, substantial safety issues including overcharging. The cell balancing controller is a critical component of the battery management system in all electric vehicle and hence performs a crucial function in extending battery life and ensuring the battery's safety. This paper presents a hardware-in-the-loop simulation of a RCD buffer included fly-back converter-based active cell equaliser for lithium-ion batteries in electric vehicles. With the equaliser, all the series-connected cells may be brought to a more even State of Charge. All of the MOSFETs employed in the proposed approach are selected for their low conduction loss. The suggested equaliser is able to produce equalization without the need for a switch driving circuit or sophisticated control method, allowing it to function automatically. The system's overall price is reduced, and the balanced circuit's complexity is considerably reduced. In-depth discussions on circuit configuration, operating principle, modeling, and design consideration are presented. Finally, both Matlab simulation results and Hardware-in-loop based experimental findings are offered to back up the claims that the suggested cell equaliser is both practical and effective

A Review on Hydrogen-Based Hybrid Microgrid System: Topologies for Hydrogen Energy Storage, Integration, and Energy Management with Solar and Wind Energy

Hydrogen is acknowledged as a potential and appealing energy carrier for decarbonizing the sectors that contribute to global warming, such as power generation, industries, and transportation. Many people are interested in employing low-carbon sources of energy to produce hydrogen by using water electrolysis. Additionally, the intermittency of renewable energy supplies, such as wind and solar, makes electricity generation less predictable, potentially leading to power network incompatibilities. Hence, hydrogen generation and storage can offer a solution by enhancing system flexibility. Hydrogen saved as compressed gas could be turned back into energy or utilized as a feedstock for manufacturing, building heating, and automobile fuel. This work identified many hydrogen production strategies, storage methods, and energy management strategies in the hybrid microgrid (HMG). This paper discusses a case study of a HMG system that uses hydrogen as one of the main energy sources together with a solar panel and wind turbine (WT). The bidirectional AC-DC converter (BAC) is designed for HMGs to maintain power and voltage balance between the DC and AC grids. This study offers a control approach based on an analysis of the BAC’s main circuit that not only accomplishes the function of bidirectional power conversion, but also facilitates smooth renewable energy integration. While implementing the hydrogen-based HMG, the developed control technique reduces the reactive power in linear and non-linear (NL) loads by 90.3% and 89.4%

Efficient Control of DC Microgrid with Hybrid PV—Fuel Cell and Energy Storage Systems

Direct current microgrids are attaining attractiveness due to their simpler configuration and high-energy efficiency. Power transmission losses are also reduced since distributed energy resources (DERs) are located near the load. DERs such as solar panels and fuel cells produce the DC supply; hence, the system is more stable and reliable. DC microgrid has a higher power efficiency than AC microgrid. Energy storage systems that are easier to integrate may provide additional benefits. In this paper, the DC micro-grid consists of solar photovoltaic and fuel cell for power generation, proposes a hybrid energy storage system that includes a supercapacitor and lithium–ion battery for the better improvement of power capability in the energy storage system. The main objective of this research work has been done for the enhanced settling point and voltage stability with the help of different maximum power point tracking (MPPT) methods. Different control techniques such as fuzzy logic controller, neural network, and particle swarm optimization are used to evaluate PV and FC through DC–DC boost converters for this enhanced settling point. When the test results are perceived, it is evidently attained that the fuzzy MPPT method provides an increase in the tracking capability of maximum power point and at the same time reduces steady-state oscillations. In addition, the time to capture the maximum power point is 0.035 s. It is about nearly two times faster than neural network controllers and eighteen times faster than for PSO, and it has also been discovered that the preferred approach is faster compared to other control methods

Real-Time Automatic Investigation of Indian Roadway Animals by 3D Reconstruction Detection Using Deep Learning for R-3D-YOLOv3 Image Classification and Filtering

Statistical reports say that, from 2011 to 2021, more than 11,915 stray animals, such as cats, dogs, goats, cows, etc., and wild animals were wounded in road accidents. Most of the accidents occurred due to negligence and doziness of drivers. These issues can be handled brilliantly using stray and wild animals-vehicle interaction and the pedestrians’ awareness. This paper briefs a detailed forum on GPU-based embedded systems and ODT real-time applications. ML trains machines to recognize images more accurately than humans. This provides a unique and real-time solution using deep-learning real 3D motion-based YOLOv3 (DL-R-3D-YOLOv3) ODT of images on mobility. Besides, it discovers methods for multiple views of flexible objects using 3D reconstruction, especially for stray and wild animals. Computer vision-based IoT devices are also besieged by this DL-R-3D-YOLOv3 model. It seeks solutions by forecasting image filters to find object properties and semantics for object recognition methods leading to closed-loop ODT