Volume 11 | Issue 5 |

 Abstract

Conventional agricultural practices can contribute to soil degradation and pollution, as well as pose health risks to humans. Organic farming practices can offer a more sustainable and environmentally friendly alternative to conventional methods. Organic farming focuses on building soil health through the use of natural processes and inputs, such as compost, cover crops, and crop rotation. By avoiding synthetic fertilizers and pesticides, organic farming can help reduce the negative impacts of conventional agriculture on human health and the environment. Brinjal, also known as eggplant, is an important crop in India and other parts of the world. There is growing interest in using organic amendments to improve the quality and yield of brinjal, while also reducing the use of synthetic pesticides and fertilizers. Research has shown that organic amendments, such as compost and vermicompost, can improve soil health and increase the availability of nutrients to plants. They can also help suppress pests and diseases, reducing the need for synthetic pesticides. In addition, studies have shown that organic farming practices can increase the antioxidant content of brinjal, making it a more nutritious crop. Overall, organic farming practices have the potential to promote sustainable agriculture cultivation, protect the environment, and improve human health. More research and investment in organic farming practices are needed to ensure that they can be implemented on a larger scale and provide a viable alternative to conventional agriculture.

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 Keywords

Brinjal, bio amendments, and enduring viability.

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Creative Commons Attribution 4.0 and The Open Definition

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Heart disease is a major global health issue and is primarily caused by coronary heart disease, which is characterized by plaque build-up in the arteries that supply blood to the heart. Detecting heart disease early is crucial for preventing its progression, and machine learning techniques can aid in this prediction. In this paper, a novel approach that combines Genetic Algorithm and Particle Swarm Optimization (PSO) with neural network algorithms is proposed to improve heart disease prediction. The Cleveland heart disease dataset is augmented with ECG (Electrocardiogram) images to create a hybrid model. Experimental results demonstrate that the proposed method achieves high classification accuracy in predicting heart disease in the Cleveland heart disease dataset with ECG images, surpassing other machine learning methods and existing studies.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Logistic Regression, Support Vector Machines, Naive Byers, Random Forest.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Computer vision and machine learning algorithms are used to design this system. In this system, we're using eye landmarks which determine the EAR (Eye Aspect Ratio) to check whether the driver is drowsy. Face recognition is determined by object detection techniques using Haar Cascade algorithm & LBPH in OpenCV and we're making this system user friendly by adding Graphical user Interface (GUI) using Tkinter. This model can predict with an accuracy rate of 90% and further can be improvised using huge datasets.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

OpenCV, Tkinter

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Median arcuate ligament syndrome is a rare disorder that is clinically characterized by the triad of post-prandial abdominal pain, weight loss, and often an abdominal bruit due to compression of the celiac artery by the median arcuate ligament.It is typically a diagnosis of exclusion and may be detected via several imaging techniques like ultrasonography and computed tomography angiography.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Post-Prandial Abdominal pain,Median Arcuate Ligament

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research paper explores the challenges and opportunities of international entrepreneurship (IE) research. The paper begins by discussing the importance of IE in today's global economy and the need for rigorous research to understand its complexities. The challenges facing IE research are then examined, including the lack of a clear definition and conceptual framework, difficulties in accessing data, and the complexity of studying a dynamic and rapidly changing phenomenon. Despite these challenges, the paper highlights the opportunities for IE research to contribute to our understanding of entrepreneurship in a global context and to inform policy and practice. The paper concludes by proposing avenues for future research, including the need for greater collaboration across disciplines and a focus on identifying best practices for successful IE.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

International, Entrepreneurship, Challenges, Opportunities

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The presented smart parking system integrates multiple private and public parking services under an integrated medium with the aim of providing one-stop parking information services to commuters in a smart city. However, the adaptation of such a system is prone to tampering, while large amounts of data are shared among various parties, leading to problems related to trust and enforcement. To address this challenge, we propose a specific blockchain-based solution for smart parking systems. The smart parking system offered facilitates checking the availability of parking slots. It is easy to find nearby private or public parking areas with pricing policies and a secure payment gateway. The system benefits in reducing pollution and fuel consumption by avoiding wastage of time. Finally, we propose a set of design principles that demonstrate the applicability of our proposed smart parking system.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Decentralization, Smart contract, Ganache, MetaMask, Mapbox, consortium blockchain, consensus mechanisms.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

According to several suicide studies, there are about 800 000 suicides per year and it is still difficult to identify suicidal individuals. Social media usage has increased, and we have seen that users openly discuss their suicide attempts and plans on these platforms. This study attempts to prevent suicide by identifying suicidal profiles on social networks. First, we analyse social media profiles to extract various elements, such as account features connected to the profile and features related to social media data. Second, we present our approach for leveraging Twitter data to identify suicidal profiles based on machine learning techniques. Then, we make use of a profile data set made up of individuals who have already committed suicide. Experimental findings attest to the recall and accuracy efficacy of our technique in identifying suicidal characteristics. Finally, we demonstrate our research using a Python-based prototype that demonstrates the identification of suicidal characteristics.

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 Keywords

Machine learning Algorithms, Suicidal Dataset, Python Based Prototype.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid development of information technology over the last decade means that data appears in a wide range of sensor data, tweets, photos, raw data and unstructured data formats. With such an overwhelming flood of information, current data management systems cannot scale to this enormous quantity of raw, unstructured data -- Big Data, today. We show the basic concepts and designs of big data tools, algorithms and techniques in the present study. We compare the classical data mining algorithms with the Big Data algorithms by using Hadoop / MapReduce as the core scalable algorithm implementation of Big Data. We implemented the K-means and A-priori algorithms on a 5-node Hadoop cluster with Hadoop / MapReduce. We use MongoDB as an example to explore NoSQL databases for semi-structured, massive data scaling. Finally, we show the performance of these two algorithms between HDFS (Hadoop Distributed File System) and MongoDB data storage.

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 Keywords

Data Storage, Big Data Algorithm, Data Mining,

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Bhitarkanika is a combination of two words: Bhitar means "inside" and Kanika means "exceptionally beautiful". Mangroves forests serve as ecotones between land and sea and elements from both are stratified horizontally and vertically, between forest canopy and subsurface soil. In India the mangroves are grown in two groups, the mangroves of the West coast and the mangroves of the East coast. Bhitarkanika National Park is a 145 km2 (56 sq mi) large national park in northeast Kendrapara district in Odisha in eastern India. It was designated on 16 September 1998 and obtained the status of a Ramsar site on 19 August 2002. The area is also been designated as second Ramsar site of the State after the Chilika Lake. It is surrounded by Bhitarkanika Wildlife Sanctuary, which spread over 672 km2 (259 sq mi). Gahirmatha Beach and Marine Sanctuary are to the east, separating swamp region and mangroves from the Bay of Bengal. The national park and wildlife sanctuary is inundated by the rivers Brahmani, Baitarani, Dhamra, Pathsala. It hosts many mangrove species, and is the second largest mangrove ecosystem in India. There are different species of Flora, Fauna, mammals, avifauna, aquafuna, marine mammals etc. The national park is home to Salt water crocodile (Crocodylus porosus), Indian python, king cobra, black ibis, darters and other species of flora and fauna. There are about 15 species of mammals, 120 species of fish, 271 species of birds, 25 species of reptiles.

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River Delta, Mangrove, Saltwater Crocodile, Species Diversity, Eco-tourism

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Creative Commons Attribution 4.0 and The Open Definition

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The ability to automatically recognize human faces based on dynamic facial images is important in security, surveillance and the health/independent living domains. Specific applications include access control to secure environments, identification of individuals at a particular place and intruder detection. This research proposes a real-time system for surveillance using cameras. The process is broken into two steps: (1) face detection and (2) face recognition to identify particular persons. For the first step, the system tracks and selects the faces of the detected persons. An efficient recognition algorithm is then used to recognize detected faces with a known database. The proposed approach exploits the Viola-Jones method for face detection, the Kanade-Lucas-Tomasi algorithm as a feature tracker and Principal Component Analysis (PCA) for face recognition. This system can be implemented at different restricted areas, such as at the office or house of a suspicious person or at the entrance of a sensitive installation. The system works almost perfectly under reasonable lighting conditions and image depths.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Face Detection, Face Recognition,Database,Monitering.

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Creative Commons Attribution 4.0 and The Open Definition