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Informed Consent of the Patient
As a basic and general condition for the conclusion of the civil legal act, consent does not know a legal definition, this role being left to the doctrine. But the Romanian legislator dedicates a generous regulation to it in the Civil Code. Thus, consent was defined as a person's manifestation of will to conclude or perform a legal act. To produce legal effects, the consent must be conscious, free, and untainted. Consent, as provided by art. 1240 of the Romanian Civil Code, can be expressed verbally, in writing or through a behaviour that, according to the law, the parties, established between them, that leaves no doubt about the intention to produce the corresponding legal effects. Referring to the medical act and to the need for a valid and informed consent of the patient, we can define this informed consent, as representing the informed consent of the patient in relation to the interventions/medical acts that can have unpredictable consequences. However, to make an informed decision, the patient must be fully informed about his state of health, about the proposed medical procedures, about the potential risks and benefits of each procedure, about alternatives to the proposed procedures, about the diagnosis, the prognosis, and the progress of the treatment. As a rule, obtaining consent is done only after the patient is informed according to his capacity to understand, clearly and with direct reference to the medical act to be performed, communicating any useful information to make a fully informed decision of cause.
Case Comment: Matam Gangabhavani v. State of Andhra Pradesh
Transgender is as a broad term that defines individuals whose gender individuality or expression is different from the culturally-bound gender linked with one’s allotted birth sex, i.e., male or female. Transgenders face extensive bias, discernment, violence and other problems of stigma and trans-phobia, i.e., abhorrence of or bias against trans-sexual or transgender people. Stigma is the social process of tagging, labelling, and declining human difference as a system of social regulator. Studying several approaches whereby transgenders face the stigma and discrimination and to comprehend circumstances and environment under which they are susceptible towards stigma is an important field of contemporary research. This paper scrutinizes the judgment by The Hon'ble Sri Justice M. Satyanarayana Murthy of the case Matam Gangabhavani vs State of Andhra Pradesh (2022 SCC Online AP 200) in the light of the nature and approach of the judgment towards the transgender society. Society is a vast term which includes various kinds of communities and judgment like Matam Gangabhavani has an effect to the society about the social stigma and the legislations by the government. The paper analyses the judgment and criticize the non-inclusive approach of the bench and also discuss the effect of such judgment to the society as a whole.
Patent Landscape for ChatGPT
This research analyses the effect of patent regime on ChatGPT and proposes possible explanations to avoid these concerns. Intellectual property rights in general and patents in particular are very importance in the innovation ecosystem. Since ChatGPT is being increasingly used in patent perspectives suggesting various solutions, naturally there should be mechanisms to cope with its implications. At a broader level, ChatGPT can accelerate preparation of patent application, prior art search, and patent examination slashing costs and time while minimizing the system mistakes. ChatGPT can assist patent attorneys work more professionally and make more precise diagnoses, thus improving their productivity. It, however, is also raising concerns in stakeholders regarding various legal issues. New legal tools are needed to understand the development, regulation, and implementation of ChatGPT in patent regime to harness the tremendous possibilities of transformation for the better. Legislators and technical experts should join hands to formulate policies that balance the innovation and protect the rights of inventors.
Legal Challenges of Intellectual Property Rights for Quantum Computing
Quantum computing is a very multidisciplinary field, a blend of materials science, electronics, electromagnetism, thermodynamics, quantum physics and the corresponding mathematical framework. The study aimed to evaluate the existing scenario of the choice of the intellectual property rights (IPRs) protection mechanisms for quantum computing, choice of best applicable type, and suggesting some key alternative innovation protection mechanisms. The methodology used in this research consists of general scientific and specific legal (historical-legal, formal-legal) methods besides law interpretation and legal modelling. We critically analyzed the norms for IPR protection of quantum computing from the viewpoint of obtaining protection of inventions and increasing the innovation activity in quantum computing. One of the regulatory mechanisms for every disruptive technology is offering it IP protection. Currently quantum computing hardware is protected by patents while software is mostly protected as copyright besides protection by industrial design and trade secret exist as complementary mechanisms for this revolutionary technology. All available approaches were considered, and amendments are suggested in current IPR legislation to correspond to the reality. This interdisciplinary research revealed the uncertain nature of quantum computing and the difficulty in selecting one type of IPR as the best choice. The best way to establish a sufficient IPR mechanism is to acknowledge quantum computing as an emerging technological cocktail, and to sustain the innovation cycle of this technology. The conclusions of this study can be used to overcome the lacunas in existing IPR system for the quantum computing. This research can be used as torchbearer when preparing proposals for making revisions and additions to the existing legislation.
Patent Spectrum of Human Digital Twins
Although no "absolute" definition exists, a human digital twin (HDT) may be defined as a virtual physiological copy or counterpart in digital world of a real person existing in the physical world having active connection between the human and his corresponding twin in metaverse. The current study aims to explore the intellectual property rights (IPR) challenges of HDTs. Previously discussions on HDT have mostly focused their potential use in health system for predictions of diseases nearly ignoring the patent associated with them. Current study highlights patent landscape analysis of HDT indicating current trends in HDT patents and future scenario of this technology.
The Role of X-ray Images for Early Detection of Covid-19 using Machine Learning
The principal aim of the Covid Detection Using X-ray project is to develop a robust platform for accurate and efficient detection of COVID-19 through the analysis of X-ray scans. The proposed system aims to enhance the diagnostic process by leveraging artificial intelligence (AI) algorithms to identify specific patterns associated with COVID-19 in X-ray images. The platform will facilitate timely and precise diagnosis, enabling healthcare professionals to make informed decisions and optimize patient care. This project integrates advanced image processing techniques and machine learning algorithms to discern subtle patterns indicative of COVID-19 in X-ray scans. The system will provide a user-friendly interface for healthcare professionals, allowing seamless uploading and analysis of X-ray images. Additionally, the platform incorporates a comprehensive database of COVID-19-related patterns for accurate comparison and classification. The primary objective of the project is to contribute to the ongoing efforts in combating the COVID-19 pandemic by providing a reliable and efficient tool for early detection. The utilization of cutting-edge technologies, including deep learning and image analysis, ensures a high level of accuracy in identifying potential cases. The project aims to be a valuable resource for healthcare practitioners, aiding in the prompt and accurate diagnosis of COVID-19 through the analysis of X-ray imagery.
College Management System
This paper is aimed at developing an Online Intranet College Management System (CMS) that is of importance to either an educational institution or a college. The system (CMS) is an Intranet based application that can be accessed throughout the institution or a specified department. This system may be used for monitoring attendance for the college. Students as well as staffs logging in may also access or can be search any of the information regarding college. Attendance of the staff and students as well as marks of the students will be updated by staff. This system (C.M.S) is being developed for an engineering college to maintain and facilitate easy access to information. For this the users must be registered with the system after which they can access as well as modify data as per the permissions given to them. CMS is an intranet-based application that aims at providing information to all the levels of management within an organization. This system can be used as a knowledge/information management system for the college. For a given student/staff (technical/non-technical) can access the system to either upload or download some information from the database.
Deep Learning Approach for Diabetic Retinopathy Detection
One of the main causes of diabetic vision loss in the active population is diabetic retinopathy, which is more commonly abbreviated as DR. This condition is caused by changes in the vessels that line the retina. One of the most serious entanglements of diabetes, diabetic retinopathy can bring about long-lasting visual impairment whenever left untreated. One of the basic troubles is early distinguishing proof, which is fundamental for treatment accomplishment. One critical ensnarement is Diabetic Retinopathy. Diabetic retinopathy is an eye infirmity caused because of delayed diabetes. On the off chance that unacknowledged or incapable treatment can prompt irreversible vision misfortune. This illness can be recognized by examining variety fundus photos of the human retina. Our work evaluates in profound learning field which is utilized for the discovery and class isolation of diabetic retinopathy into parallel or multiclass and examine them in view of various measurement estimates like accuracy, review, precision. The characterization of diabetic retinopathy includes various advances like pre-handling of picture; include extraction, dimensionality decrease and order of exudates, woolen spot, hemorrhages and microaneurysm. The mechanized methods for Diabetic Retinopathy affirmation are versatile for cost and time decline and are more able over manual examination. Significant Learning technique performs PC upheld clinical end. This paper is an undertaking toward finding a modified response for Diabetic Retinopathy affliction in early phase unfortunately; the particular unmistakable evidence of the diabetic retinopathy stage is broadly fascinating and requires ace human interpretation of fundus pictures. Improvement of the revelation step is fundamental and can help an enormous number of people. Convolutional cerebrum associations (CNN) have been really applied in various adjoining subjects, and for examination of diabetic retinopathy itself. With the right treatment, numerous issues brought about by DR can be kept away from. Since the diabetic retinopathy progresses through a couple of stages, it is really trying for diabetic retinopathy acknowledgment and exploring of such pictures is a drawn-out manual connection. In this work, we are searching for a technique that consequently isolates a picture into different phases of diabetic retinopathy. This errand uses convolutional mind association (CNNs) power for DR area and usages an unreservedly open dataset of Aptos competition open on Kaggle for setting up these models. Each of the 3663 high-quality fundus images in the dataset was approximately 4000 * 2000. The calculation can order the given picture into various DR phases toward the end. In this undertaking we are using Convolutional Cerebrum Association computation. Execution and accuracy of the applied computations is discussed and examined.
Intrusion Detection using Deep Learning
The focus of cloud computing nowadays has been reshaping the digital epoch, in which clients now face serious concerns about the security and privacy of their data hosted in the cloud, as well as increasingly sophisticated and frequent cyber attacks. Therefore, it has become imperative for both individuals and organizations to implement a robust intrusion detection system (IDS) capable of monitoring packets in the network, distinguishing between benign and malicious behaviour, and detecting the type of attacks. IDS based on ML are efficient and precise in spotting network threats. Yet, for large dimensional data sizes, the performance of these systems decreases. Thus, it is critical to build a suitable feature selection approach that selects necessary features without having an impact on the classification process or causing information loss. Furthermore, training ML models on unbalanced datasets show a rising false positive rate (FPR) and a lowering detection rate (DR). In this paper, we present an improved cloud IDS designed by incorporating the synthetic minority over-sampling technique (SMOTE) to address the imbalanced data issue, and for feature selection, we propose to use a hybrid approach that includes three techniques: information gain (IG), chi-square (CS), and particle swarm optimization (PSO). Finally, the random forest (RF) model is utilized for detecting and classifying various types of attacks. The suggested system has been verified by the UNSW-NB15 and Kyoto datasets, achieving accuracies of over 98% and 99% in the multi-class classification scenario, respectively. It was noticed that an intrusion detection system with fewer informative features would operate more effectively. The simulation results significantly outperform other methodologies proposed in the related work in terms of different evaluation metrics.
Smart Ambulance Service and Tracking Applications for Critical Needs
This abstract introduces a Smart Ambulance Service (SAS) along with its accompanying service application designed to address critical needs in emergency medical care. The SAS incorporates cutting-edge technologies such as Internet of Things (IoT) and real-time data analytics to enhance the efficiency and effectiveness of emergency response systems. The SAS aims to revolutionize traditional ambulance services by leveraging IoT devices installed within ambulances. These devices collect vital signs of patients en route to the hospital, such as heart rate, blood pressure, and oxygen levels, and transmit this data in real-time to healthcare providers. This real-time data transmission allows medical personnel to prepare for the patients arrival, making the transition from ambulance to hospital smoother and reducing delays in treatment. Furthermore, the service application is user-friendly interface accessible to both emergency responders and hospital staff. It provides a centralized platform for managing ambulance dispatch, tracking ambulance locations and monitoring patient conditions remotely. Emergency responders can input patient information, vital signs, and the nature of the emergency directly into the application, ensuring that hospital staffs are well- informed before the ambulance arrives.
Smart Home Automation System
In fast moving world, where people are very busy in their own things, there is a need for automation in all activities, not only industries and machineries; even home automation is of prime importance. As of now, for automation purposes we use different wireless technologies and that process uses a PC, voice processor etc., these have their own limitations and results in decreased accuracy. In order to provide more reliable and convenient automation we use android applications. Smart phones are becoming more popular now a days and each of us are having a smart phone in present situation. So by using dedicated applications on an android device complete automation can be done and this to a great level will decrease the drawbacks caused by other conventional wireless technological processes. It has a variety of advantages over conventional old microcontrollers such as RISC architecture, larger memory word, fast operation and a host of inbuilt features such as ADC, communication protocols etc., The project can be used to control any external environment where in the person may like to control all his surroundings such as fans, lights, TVs, etc; He may also like to open the door for someone or close the water tap.
Machine Learning Approaches Predicting the Best Features of Child Birth Using Support Vector Machine (SVM) Algorithm
Cesarean childbirth, though often necessary for medical reasons, carries inherent risks and impacts maternal and neonatal health. Predicting the likelihood of cesarean delivery can assist healthcare providers in making informed decisions and optimizing maternal care. In this study, we propose an ensemble machine learning approach to predict cesarean childbirth based on maternal and fetal health data. First, we collect comprehensive data including maternal age, BMI, gestational age, fetal weight, previous cesarean history, and other relevant factors. After preprocessing the data to handle missing values and encode categorical variables, we select informative features using correlation analysis and domain expertise. Next, we employ various ensemble machine learning methods, including Voting Classifiers, Bagging, Random Forest, Boosting, and Stacking. These methods combine predictions from multiple base learners, leveraging their diverse strengths to enhance predictive accuracy.
Find Missing Person Using Artificial Intelligence
Face recognition is a biometric grounded technology that mathematically charts particular person’s or individual’s facial features and stores all that data as a face print. By using this fashion, the information of the face of a person is saved mathematically or in the format of graphs in the database, which is used for detecting that particular face. Face recognition model in our system will find a match of that person in the database. If a match is found, it will be notified to the police and the guardian of that person. The face recognition model in our system will try to find a match in the database with the help of Tensor Flow Face recognition algorithm. It is performed by comparing the face encodings of the uploaded image to the face encodings of the images in the database. If a match is found, it will be notified to the police and the people related to that person along with the position of where the person is found. Face recognition models in Deep and Machine Learning are primarily created to ensure the security of identity. There are several frameworks used in building a face recognition model and one of them is Tensor Flow. The Tensor Flow face recognition model has so far proven to be popular. Using Tensor Flow to build face recognition and discovery models might bear trouble, but it is worth it in the end. As mentioned, Tensor Flow is the most used Deep Literacy framework and it has pre-trained models that fluently help with image bracket.
An Integrated Smart Metering System Using LORA Technology
Precise meter readings are essential for effectively regulating residential energy systems in India's smart city context. However, due to the high number of users and the absence of daily consumption monitoring, standard meter reading methods are expensive and time-consuming, which causes consumer unhappiness. The suggested approach to address this issue is to put in place an integrated wireless smart energy system that makes use of smart metering technologies. The way utilities manage energy could be completely changed by this method. The integrated system is intended to take the place of the traditional digital energy meters, which are primarily used to record meter readings properly for payment purposes. This allows for automatic meter readings without the need for frequent travels to the location where the meters are located. Low Power Wide Area Networks (LPWAN) technology, which is renowned for its low power consumption, cost-effectiveness, long-range coverage, and efficient penetration, are used in this technology to enable the transfer of accurate and secure data on energy usage in real-time. The experiments that resulted from the trials allowed the energy to successfully communicate and documented reliable readings. By providing users with real-time usage data and guarding against overloaded scenarios, the system also benefits consumers. Additionally, the device reports electricity theft to the utility company. The shortcomings of the conventional systems and design difficulties are addressed by the suggested system.
Alternative Arrangement for Roof Tops Rural Housing Catching Rain Water in the Semi-Arid
Harvesting rainwater for human consumption through rooftops is becoming an increasingly common practice, especially in regions where there are no community water supplies, such as much of the Indian semi-arid region. The water collection systems installed in this region are based on the construction of cisterns to collect water collected through roofs. In order to contribute to the improvement of the performance of these systems, this work aimed to study the problems preventing the proper functioning of this important water supply and to propose design solutions adapting appropriate technologies for the rural population of the Indian hemisphere, Arid region. The starting point was a field study conducted in the rural community of Namakkal Taluk in Tamil Nadu between 2020 and 2021. The results showed that 80% of the residential buildings surveyed have a water intake system, but only 16% store enough water for a year-round supply. It was found that this low rate is mainly due to unreliable conditions for installation and maintenance of water conduit subsystems (gutters and channels). Based on this finding, and taking into account functional and aesthetic-formal aspects, five alternative devices for rainwater harvesting systems, consisting of roofs, gutters and channels, were developed. In order to simplify and, as a result, reduce the cost, the gutter supports were eliminated, which gave a performance advantage over conventional systems.
Video Forgery Detection with Deep Learning Using RESNET and CNN Algorithm
Video forgery is continuously increasing in the digital world due to breaches of information security, consequently establishing a scenario for image and video content monitoring for forgery identification. The spread of fake videos raises security risks and anarchy in society. The reason for video forgery is to the augmentation in the malware, which has facilitated user (anyone) to upload, download, or share objects online comprising audio, images, or video. With the development of technology and ease of creation of fake content, the manipulation of media is carried out on a large scale in recent times. Video forgery detection has applications in media science, forensic analysis, digital investigations, and authenticity verification of a video. The purpose of video forensic technology is to extract features to distinguish fake content frames from original videos.
Study of Insulation Loss in Boiler
Thermal is the main source for power generation in India. The percentage of thermal power generation as compare to other sources is 65%. The main objective of thermal power plant is to fulfill the energy demands of the market and to achieve these demands; plant requires technical availability with the parts reliability and maintenance strategy. This paper deals with the determination of current operating efficiency of Boiler and calculates major losses for Super thermal power plant (India) of 210MW units. Then identify the causes of performance degradation. Also find the major causes of heat losses by Fault Tree Analysis (FTA) and recommends its appropriate strategy to reduce major losses. The aim of performance monitoring is continuous evaluation of degradation i.e. decrease in performance of the steam boiler. These data enable additional information which is helpful in problem identification, improvement of boiler performance and making economic decisions about maintenance schedule.
Design and Fabrication Pneumatic Expandable Vehicle
Thermal is the main source for power generation in India. The percentage of thermal power generation as compare to other sources is 65%. The main objective of thermal power plant is to fulfill the energy demands of the market and to achieve these demands; plant requires technical availability with the parts reliability and maintenance strategy. This paper deals with the determination of current operating efficiency of Boiler and calculates major losses for Super thermal power plant (India) of 210 MW units. Then identify the causes of performance degradation. Also find the major causes of heat losses by Fault Tree Analysis (FTA) and recommends its appropriate strategy to reduce major losses. The aim of performance monitoring is continuous evaluation of degradation i.e. decrease in performance of the steam boiler. These data enable additional information which is helpful in problem identification, improvement of boiler performance and making economic decisions about maintenance schedule.
Multifunction Controlled 3D Printed Hand Prosthesis with the Myo Arm-Band by Hand Amputees
Upper limb amputations are highly impairing injuries that can substantially limit the quality of life of a person. The most advanced dexterous prosthetic hands have remarkable mechanical features. However, in most cases, the control systems are a simple extension of basic control protocols, making the use of the prosthesis not intuitive and sometimes complex. Furthermore, the cost of dexterous prosthetic hands is often prohibitive, especially for the pediatric population and developing countries. 3D-printed hand prostheses can represent an opportunity for the future. Open 3D models are increasingly being released, even for dexterous prostheses that are capable of moving each finger individually and actively rotating the thumb. However, the usage and testing of such devices by hand amputees (using electromyography and classification methods) is not well explored. This article aims to investigate the usage of a cost-effective system composed of a 3D-printed hand prosthesis and a low-cost myo electric armband. Two subjects with trans-radial amputation were asked to wear a custom-made socket supporting the Hand and the Thalmic Labs Myo armband. Afterward, the subjects were asked to control and use the prosthetic and to grasp several objects by attempting to perform a set of different hand gestures. Both the Hand and the Myo armband performed well during the test, which is encouraging considering that the Hand was developed as a research platform. The results are promising and show the feasibility of the multifunction control of dexterous 3D- printed hand prostheses based on low-cost setups. Factors such as the level of the amputation, neuromuscular fatigue, and mechanical limitations of the 3D-printed hand prosthesis can influence the performance of the setup. Practical aspects such as usability and robustness will need to be addressed for successful application in daily life.
Health Care in India before 2000 & After 2000
The advancement of health care gear some time recently and after 2000 implies a transformative jump in therapeutic hone. Pre-2000, restricted capabilities in conclusion, treatment, and persistent are won. Be that as it may, post-2000 progressions, counting high-resolution imaging, AI integration, and negligibly obtrusive surgical strategies, have revolutionized restorative hones, moving forward understanding results. Telemedicine advances expand health care get to, whereas progressed checking frameworks empower ceaseless farther checking and early intercession, promising a future of accuracy pharmaceutical and personalized healthcare conveyance.