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Design and Construction of 5-Dof EMG Based Robotic Arm System
Electromyography (EMG) is an alternate method of obtaining muscle signal outputs. As a result, the current development in designing my electric plans has piqued the attention of researchers in this subject. This is because Standard controllers lack essential components, limiting the use of limbs to operate equipment, namely an arm controlled by robotics. EMG signals are subject to noise, including crosstalk, motion artifacts, ambient noise, and intrinsic noise. Electromyography preparation requires careful selection of muscle groups, electrode placement, and environment quality, all of which impact the signal output. The goal of this study is to create an EMG-based robotic arm control system that can be used to help the elderly, individuals with impairments, and those who operate in dangerous places. Initially, a literature review on current human-robot interaction approaches and analysis of the kinematics of a 5 DOF robotic arm has been conducted. Then, utilizing Electromyogram (EMG) data obtained from the muscles of the elbow, away for controlling a 5 DOF robotic arm is provided. Two accelerometers are utilized to record the human arm's gesture and posture, this information is then communicated to the robotic arm as an input. In the experiments, wrist rotation, left, right, up, and down movements were used to establish controlled motion of a 5 DOF robotic arm. The project's goal has been met with the successful development of an EMG-controlled robotic arm. The robotic arm may yet be improved by including Implementing a wireless sensor network with multiple channels.
The non-alcoholic fruit beverage market through patent prospecting
Non-alcoholic fruit beverages hold significant importance in the fruit processing chain. This article aimed to conduct a technological prospective study, through patents, in this specific beverage area. Patents were searched in the online databases of INPI (Brazil) and EPO (Europe), using keywords, the internation classification number, and filing dates. A total of 80 patents were retrieved, excluding duplicates and out of scope ones. The year 2020 witnessed the highest number of filings, followed by a decrease in subsequent years. Japan held 46% of the patents considered in this study, while Brazil accounted for 26%. Overall, the primary filers are from the industry, while 48% of Brazilian patents had educational and research institutions as filers. Lemon, orange, and grapefruit were the most cited fruits in the analyzed documents, indicating a wide participation of tropical fruits in beverage production. Despite Brazil being one of the world's largest fruit producers, Japan leads in innovations related to fruit beverages. Brazil needs to improve its innovation ecosystem to encourage domestic companies, achieve greater competitiveness in international trade, and add higher value to its traded goods.
The Role of Personality Rights in Indian Law: Lessons from Jackie Shroff's Legal Battle
Current research examines the landmark judgment of Jaikishan Kakubhai Saraf alias Jackie Shroff v. The Peppy Store & Ors. indicating the importance of developing personality rights jurisprudence in India, especially in digital content. Personality rights include both publicity rights and privacy rights. Right to control the commercial use of one's identity, i.e. publicity rights, is important for protecting personalities from unauthorized exploitation of their persona (name, image, voice, etc.). The case highlights the unauthorized use of Shroff's image for commercial gain without his consent, raising significant questions about the scope and enforcement of personality rights in India. The Court's decision to protect actor Jackie Shroff's identity from unauthorized commercial exploitation marks a pivotal moment in legal precedents safeguarding the identity of personality, especially for celebrities. This case underscores the evolving landscape of legal protections in the digital age, emphasizing the importance of rec-ognizing and upholding personality rights amidst increasing unauthorized commercial use. As a result, it stands as a landmark decision, guiding the future of personality rights and reinforcing the legal safeguards necessary to personality identity in an increasingly digital world. By dissecting this case, the paper aims to explore the im-plications for the ongoing development of personality rights in India and the growing importance of safeguarding individual identity in the digital era. Also, the paper critically assesses the current legal framework, including statutory provisions and judicial precedents. It has been compared with international standards to detect loopholes and propose improvements, in the evolving regime of personality rights in the digital era.
Legal Protection of Industrial Drawings, Models and Designs in Yemen
Industrial revolution contributed to the emergence of industrial property rights and the accompanying inventions. Technological development and the expansion of the use of electronic technologies in various industrial fields contributed to increasing competition between economic entities, regarding their ownership of the elements of industrial property rights. These rights distinguish their products from others, besides their role in increasing the economic growth rates of countries that possess patents or technical knowledge, which supports their economy. National laws and international agreements have been designed to protect industrial property rights as patents, designs and trademarks. Work on imposing specific controls to protect their owners and creators of those rights from a legal perspective, as well as establishing an economic balance between the owners of those rights and those with the right to monopolize them on the one hand and the general public on the other hand to provide the appropriate environment to achieve more innovation and creativity to maximize their economic return. This research aims to study the legal protection of industrial drawings and models, and to investigate the problems that arise regarding them. The researcher used the descriptive approach based on describing the legal texts included in Yemeni law, and analyzing them to reach useful results on the subject. The research reached the most important results, which is that the law provided protection for industrial models and drawings. The researcher recommends keeping pace with technical developments and updating legislation to include technical drawings and models as well.
<b>The Crossroad between Intellectual Property and Clinical Trials: Balancing Incentives for Innovation w</b>ith Access to Healthcare
The interplay between intellectual property rights (IPRs) and clinical trials presents a complex challenge in the realm of healthcare innovation. This paper examines the critical role of IPRs, particularly patents, in incentivizing pharmaceutical research and development while simultaneously addressing their implications for access to essential medicines, especially in low- and middle-income countries (LMICs). We explore the phases of clinical trials that underpin medical advancements and highlight the significant financial and temporal investments required for drug development. The discussion also delves into the tensions created by monopolistic pricing, data exclusivity, and evergreening practices that hinder equitable access to healthcare. Through a review of international agreements like the TRIPS Agreement and case studies on HIV/AIDS, hepatitis C treatments, and COVID-19 vaccines, we illustrate the urgent need for policy reforms and alternative incentive models, including prize funds, patent pools, and tiered pricing strategies. Our findings underscore the necessity for a balanced approach that fosters innovation while ensuring that life-saving medications are accessible to all populations. Ultimately, this paper calls for collaborative efforts among governments, international organizations, and the private sector to create an equitable healthcare landscape that prioritizes public health needs without stifling innovation.
Khewra Pink Rock Salt as a registered Geographical Indication of Pakistan
Khewra Pink Rock Salt also known as Himalayan Pink Salt, extracted from the Khewra Salt Mines, in Pakistan is appreciated due to its pink color, rich mineral content, culinary usage and associated health benefits. The problem arose when it was highlighted that it is being sold in global markets as a product of India. It was quite concerning for local communities and regions which are hub of its production since centuries. Pakistan is already bearing the brunt of not claiming many geographical indications timely. After the implementation of Geographical Indications Act of Pakistan in 2020, it’s now tagged as a GI of Pakistan. Current study explores the origin of salt, its economic potential, health benefits, and the increasing market demand. Registration of this Pink Salt as a GI of Pakistan is also discussed, that will safeguard its authenticity a Pakistani product. Suitable branding, sustainable mining practices, and value-added products are necessary to meet the increasing demand for high-quality pink salt and to ensure the long-term success of the Himalayan pink salt industry.
Vehicle Collision Detection and Alert System
In modern vehicles, the collision detection system has become a crucial safety feature, mainly because after the evolution of autonomous and self-driving vehicles. It is proved to be very effective in minimizing the number of road accidents. This proposed system is a working model based system to detect the vehicle collision and give information to the authorities. This project proposes an automated system for vehicle collision detection during high traffic and inform the concerned people using the application. This approach will work on still images, recorded- videos and will detect, classify, track and compute moving object velocity and direction using a convolution neural network. By using YOLO, it will be able to detect the front and rear views of the vehicle and alert us in advance. The advantages of the proposed system are secured, interpretability, high accuracy, lightweight model & fast processing. Moreover, this system can be used in self-driving cars. Where it would analyse the collision possibility automatically and drive accordingly. It could be used in self-driving cars, traffic surveillance systems, traffic management, and automated driving applications.
Comparative Analysis of Rights of Victim in The Criminal Proceedings in India: Need for improving Victim Justice
The victims of crime have long remained the forgotten identity in a judicial proceeding. Crime has been treated as wrong against society and thus the cases have been dealt as having two parties, the State and the accused. The aim of the criminal laws was focused on punishing the criminal and the plight of victims had been continuously ignored with no regard being paid to the needs or relevance of recognition of a victim as the actual sufferer of the crime. Gradually in India, the rights of victims have been recognized by the law and majorly by the courts. However, in comparison to the rights of the accused or other victim rights in other jurisdictions like UK, USA, and Canada, the Indian laws are still far behind. There is lack of specific legal provisions and uniformity in the sphere of victim rights. This study aims at in-depth analysis of the victim rights in the three stages of the criminal proceedings, i.e., investigation, enquiry and crime by simultaneously indulging in comparative analysis with rights of accused and victim rights in other jurisdiction and thereby suggesting the way forward.
Legal Evaluation of Premium Payment as a Condition Precedent for a Valid Insurance Contract
The idea of insurance is widely recognized in commercial law and has evolved into a fundamental tenet of contemporary business dealings and contracts. It was designed to satisfy the requirements of contracting parties and has been supported as a workable and commercial tool that an insured can use to reasonably mitigate the effects of a disaster or other occurrence by purchasing an insurance policy. A service known as insurance exchanges risk for monetary responsibilities known as premiums. It is not uncommon for an insured party, before the advent of Insurance Decree 1997 after negotiating and executing an insurance policy, to defer payment of premium until a later date; or for insurance companies to accept part payment of premium, on the condition that payment would be made in full before the end of the insurance policy period. This position changed with the provision of ‘no premium no cover’ under Section 37 of the Insurance Decree, 1997. In an action for enforcement of a contract, the party who alleges breach must prove the existence and validity of a contract between him and the other party. A very important ingredient of the insurance contract is consideration; that is, for a contract to be valid, something of some value, e.g. money or services, must be exchanged for the promise under the contract. Offer and acceptance refers to an offer being made and then being accepted by the other party. Fulfilment of this legal requirement implies that negotiations have been settled and parties have come to an agreement. Current study examined and evaluated premium payment of premiums as a prerequisite to enforceable insurance agreements and claims. It revealed that payment of full insurance premiums is imperative if a contract of insurance is legal and enforceable under section 50(1) of the 2003 Insurance Act. Also, it will be unreasonable and unjustifiable for an insured to be expecting indemnity when a full premium has not been paid to the insurer for proper coverage.
Recent Development of Arbitration Law in Brazil
Arbitration in Brazil has undergone a remarkable transformation, graduating from a tentative start to a robust and thriving practice. Like many jurisdictions with complex judicial systems, Brazil has found in commercial arbitration a valuable tool to foster economic growth and provide efficient dispute resolution for both domestic and international parties. Initially, when the Arbitration Act was enacted in 1996, it was met with skepticism. Many Brazilian scholars and legal practitioners questioned its constitutionality, as the concept of removing cases from the traditional judiciary's purview seemed far-fetched. The turning point came when Brazil's Supreme Court upheld the constitutionality of the Arbitration Act, providing a significant boost to its adoption and legitimacy. Since then, the country has witnessed rapid advancements in arbitration practices, making it an increasingly attractive venue for resolving commercial disputes. This development reflects a growing confidence among businesses and legal experts in the efficiency and effectiveness of arbitration as a complementary mechanism to the traditional court system. This article aims to delve into the evolving legal environment surrounding arbitration in Brazil. It will explore the dynamic trends that have emerged, such as the increasing sophistication of arbitration procedures, the establishment of dedicated arbitration centers, and the rising number of professionals specializing in this field. Additionally, the article will analyze how these developments have influenced Brazil's attractiveness as a hub for international arbitration, and the impact this has on the nation's legal and economic landscape. By examining these aspects, the article will provide a comprehensive overview of the current state and future potential of arbitration in Brazil.
The Changes Proposed by Law no. 14.879/2024 and the Limitations on the Forum Selection Clause in International Contracts
This study analyzes the possible impacts of the Law nº. 14.879/24, which amended article 63 of the Brazilian code of civil procedure, in the international contracts. The purpose of the law is regulating the application of the forum selection clause for actions arising from rights and obligations. Due to the changes brought in by the law, some requirements have become indispensable for the effectiveness of the forum selection clause which are the relevance to the domicile or residence of one of the parties or to the place of obligation, considering non-compliance with such requirements to be an abusive practice. However, international commercial contracts are characterized by the plurality of parties and legal systems involved in the relationship, leading to the fact that parties commonly adopt the forum selection clause indicating a neutral forum to settle problems arising from these contracts, without necessarily having any connection with the parties or the obligation. Therefore, the purpose is to debate whether the proposed changes constitute a real step backwards and could affect the autonomy of the parties will in international contracts, creating legal uncertainty in transnational legal transactions. It can be concluded that the real setback generated by the modification of the legal provision that deals with the choice of forum clause, by making it possible for the Brazilian judiciary to stop recognizing the autonomy of the parties' procedural will in international contracts, will generate uncertainty and legal insecurity in transnational legal transactions.
Civil Liability of The Air Carrier for Errors of The Aircraft Crew in Jordanian Law
The aircraft crew bears significant responsibility as they operate the aircraft in the sky, carrying numerous duties and exercising various authorities to perform their tasks effectively. The aircraft crew is obligated to fulfill their commitments towards the air carrier. Current study addresses the issues surrounding the extent of the air carrier's liability for errors committed by the aircraft crew. These errors may be personal, technical, or administrative during flight. We used a comparative, descriptive, and analytical approach to achieve the objectives of the thesis and answer its questions, which focus on defining the obligations and authorities of the aircraft crew and determining the nature of the air carrier's responsibility for errors of the aircraft crew. The key finding of study is that the Jordanian legislator has largely held the air carrier responsible for damages resulting from errors committed by the aircraft crew. Both the air carrier and the aircraft crew share responsibility for these damages towards third parties based on solidarity and mutual assistance. It is suggested to amend the text of Article (42/C) to include detailed provisions specifying the extent of responsibility for each member of the aircraft crew, the responsibility of the aircraft commander, operator, and air carrier in the face of actions leading to harm.
Enhancing E-commerce Content Management Systems with AI: Predictive Analytics and Personalization for Automated Content Creation
In the digital era of e-commerce, effective content management is crucial for engaging and retaining online consumers. Traditional manual approaches to content creation often fall short in terms of speed, scalability, and adaptability. With over 26.5 million e-commerce stores worldwide, staying competitive requires leveraging all available tools. This research paper investigates the efficiency and effectiveness of AI-driven content generation compared to traditional methods. We examine AI technologies for creating titles, subtitles, and SEO optimization against content writers. The study involves five authors and an AI tool generating content for five products, with time taken for content creation measured and compared. Additionally, a group of 15 participants will evaluate the professional quality and click ability of the generated content. Using Python, we will analyze the potential time savings for generating 100 titles and assess the overall quality improvement. The results aim to provide empirical evidence on the benefits of AI in content creation for e-commerce. Our findings reveal that AI significantly reduces the time required for content creation. Specifically, AI-generated titles are 84.17% faster and AI-generated subtitles are 77.31% faster compared to those created by content writers. The content writers worked without the aid of any tools, relying solely on provided specifications. Additionally, 81.33% of participants preferred the titles generated by AI, while 88% favoured the AI-generated subtitles. These results underscore the potential of AI to enhance efficiency and effectiveness in e-commerce content management.
INTEGRATIVE APPROACHES TO ANAEMIA TREATMENT: THE POTENTIAL OF INDIAN HERBAL REMEDIES
Anaemia, which affects more than 2 billion people worldwide is defined as a situation in which the quantity of red blood cells (RBCs) or haemoglobin are so low that oxygen delivery to tissues cannot satisfactorily meet all the cellular metabolic demand. It has serious health implications such as hazards to the brain, loss of physical productivity and death in general especially children, pregnant women. Traditional approaches to treatment consist mostly of oral iron replacement and dietary modifications, with increasing interest in use Indian traditional herbal medicine as adjunctive treatments. I feel this is a really deep exploration of how different types impact health (iron-deficiency, vit B12 deficiency and anaemia of chronic disease to name just three). Ayurvedic Herbs and Anaemia -It discusses a detailed application of Ayurveda to anaemic condition with case-studies, it also covers the therapeutic potential as Ashwagandha. Shatavari, Punarnava seeds and leaves (CMN), Moringa (Leaves) in management of anaemia. Loaded with nutrients like iron and Vitamin C these herbs uplift haemoglobin levels, facilitate the absorption of nutrients besides promoting overall health.
Cyber Security and Artificial Intelligence in Aviation
Airports are becoming increasingly interconnected and technologically advanced ecosystems. Airports handle sensitive data and depend on interconnected systems, which, while improving efficiency, also heighten vulnerability to cyber threats like data breaches and ransom ware. Additionally, with technological advancements artificial intelligence also plays a huge role, providing a new definition to cyber security in aviation. This paper examines the current state of cyber security in the aviation industry, implementation of artificial intelligence and how we can make the best use of technology, whilst focusing on the vulnerabilities and threats that accompany the adoption of advanced technologies such as Internet of Things (IoT) and Supervisory Control and Data Acquisition (SCADA) systems. The paper also explores the types of cyber attacks that can target smart airport systems, emphasising the need for robust cyber security measures to protect these critical infrastructures.
Security Risks and Mitigation Strategies in Mobile Banking Applications
Financial services have undergone a change thanks to mobile banking apps, which give consumers quick and easy access to their accounts. Significant security risks, such as phishing attacks, data breaches, and unauthorized access, are associated with this convenience. In order to assess mitigation measures, this study employs a variety of algorithms to explore major security concerns related to mobile banking applications. Intrusion detection and data encryption are our two main areas of concentration.We evaluate the capability of Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) for intrusion detection in terms of their ability to recognize hostile activity. Our findings show that CNNs achieve a 15% accuracy gain in detecting sophisticated attacks compared to SVMs due to their superior capacity to understand complicated patterns. We assess the Elliptic Curve Cryptography (ECC) and Advanced Encryption Standard (AES) algorithms in the field of data encryption. While ECC provides a more effective solution with similar security standards, AES performs better in terms of speed and durability.Based on the findings, mitigation options such as the implementation of hybrid encryption schemes and improved anomaly detection systems are suggested. In order to safeguard mobile banking applications from new dangers, the study emphasizes the significance of integrating diverse security methods.
AI-Powered Mental Health Monitoring using Wearable Devices and Mobile Sensing
Artificial intelligence (AI)-powered mental health monitoring has new opportunities thanks to the quick developments in wearable technology and mobile sensing. In order to enable real-time, continuous monitoring of mental health indicators, such as stress, anxiety, and depression, this project investigates the integration of AI algorithms with wearable and mobile sensors. Artificial intelligence (AI)-powered models can accurately forecast mental health states by utilising data from activities, skin conductance, and heart rate variability. We assess how well-performing a number of well-known algorithms are at predicting mental health disorders from sensor data, including Recurrent neural networks (RNN), convolutional neural networks (CNN), random forests (RF), and support vector machines (SVM). The comparison demonstrates that CNNs perform better than other methods when handling multi-dimensional time-series data from wearable, with up to 92% accuracy rates. Although they require greater processing power, RNNs - especially LSTM networks—offer reliable long-term prediction capabilities. SVMs have trouble processing the massive datasets that wearable devices usually produce, despite their effectiveness in managing non-linear connections. Real-time applications can benefit from Random Forests because they strike a balance between computing efficiency and accuracy. By collecting both the spatial and temporal aspects of the data, hybrid models that fuse CNNs and RNNs have the potential to significantly increase prediction accuracy, as this study also demonstrates. To overcome the problem of limited labelled data in mental health monitoring, the integration of Generative Adversarial Networks (GANs) for data augmentation is suggested. Overall, this research highlights how wearable technology and cutting-edge It is possible to develop scalable and personalised solutions for mental health therapy by smoothly integrating computational learning algorithms.
AI-Driven Predictive Modelling for Cardiovascular Disease Risk Assessment
Advanced predictive modelling is necessary for early identification and risk assessment of cardiovascular disease (CVD), as it continues to be a significant cause of death globally. This study compares established algorithms with novel ideas to investigate AI-driven predictive modelling tools for estimating the risk of cardiovascular disease. Support vector machines (SVM), random forests, and logistic regression are examples of machine learning methods used in the current models. Although these have demonstrated effectiveness in managing organised clinical data, they frequently struggle to include diverse data sources such genetic, lifestyle, and imaging data.To improve prediction accuracyand we present an approach that introduces deep learning models: recurrent neural networks (RNN) for time-series data and convolutional neural networks (CNN) for picture analysis. In order to take use of the advantages of both paradigms, we also investigate hybrid models that integrate neural networks with gradient boosting machines (GBM). The outcomes show that, in important categories like accuracy, sensitivity, and specificity, our suggested models perform better than conventional algorithms. Additional strengthening of the model resilience is achieved by integrating generative adversarial networks (GAN) for data augmentation. Clinical decision-making is improved by the comparative analysis, which shows a notable decrease in false positives and negatives.
AI-Assisted Diagnosis of Rare Genetic Disorders : A Case Study
Artificial intelligence (AI) has completely changed the diagnostics of medical conditions, especially when it comes to finding uncommon genetic abnormalities. In order to improve the precision and speed of diagnosing uncommon genetic disorders, this case study investigates the effectiveness and promise of AI-assisted diagnostic tools. We examine patient genomic data to find patterns and abnormalities suggestive of particular genetic illnesses by utilising cutting-edge machine learning methods, especially deep learning and neural networks. To develop and validate our AI models, our research combines information from various sources, such as clinical observations, patient medical histories, and genomic sequences. Researchers highlight the intricacy and rarity of these illnesses provides significant hurdles that AI can help us overcome. The possibility for early diagnosis, which is critical for patient outcomes, and notable gains in diagnostic accuracy are among the key results. In order to fully utilise AI, our research emphasises how crucial it is for geneticists, data scientists, and doctors to collaborate across academic boundaries. Our findings have implications for a paradigm change in genetic diagnostics, opening the door to more individualised and successful therapies.
AI-Driven Personalized Nutrition: A system for Tailored Dietary Recommendations
Employing deep neural networks (DNNs) and machine learning (ML) to provide individualised nutrition programs based on user demands, AI-driven personalised nutrition is a revolutionary approach to nutritional recommendations. Nutritional intake, metabolic reactions, and dietary patterns have all been studied in the past using classical machine learning (ML) techniques including Random Forests (RF), Support Vector Machines (SVM), and k-Nearest Neighbours (k-NN). Though useful in identifying some dietary patterns, these models frequently suffer from the complexity and high dimensionality of nutritional data, which results in less than ideal personalisation.Alternatively, the suggested architecture of a deep neural network (DNN) is made to manage this complexity by identifying complicated connections between food inputs and personal metabolic profiles. The DNN model can better analyse and forecast the effects of particular foods on an individual's health since it integrates multi-layered architectures and attention mechanisms. Personalised nutrition can be approached more holistically when important aspects including metabolic responses, food absorption rates, genetic predispositions, and lifestyle factors are included.A comparison test between the proposed DNN model and current ML methods shows that the DNN is superior in terms of model interpretability, prediction accuracy, and capacity to handle multi-dimensional, large-scale datasets. Compared to classic ML approaches, which typically reach between 70-85% accuracy, the DNN delivers up to 95% accuracy in dietary recommendations. In addition, the DNN's capacity to learn from fresh data and adjust accordingly guarantees that dietary recommendations change as an individual's preferences and health state do. The aforementioned study highlights the capacity of artificial intelligence (AI) to transform personalised nutrition by providing more accurate, dynamic, and empirically supported dietary recommendations.