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A crime is a deliberate act that can cause physical or psychological harm, as well as property damage or loss, and can lead to punishment by a state or other authority according to the severity of the crime. The number and forms of criminal activities are increasing at an alarming rate, forcing agencies to develop efficient methods to take preventive measures. In the current scenario of rapidly increasing crime, traditional crime-solving techniques are unable to deliver results, being slow paced and less efficient.
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467 Views
Abstract- Cardiovascular diseases (CVDs) remain a sig- nificant global health challenge, emphasizing the critical need for accurate predictive models to address early detec- tion and intervention. This study presents a comprehensive framework for heart disease prediction using advanced ma- chine learning techniques.
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2677 Views
Drug development is a process that is incredibly expensive and time-consuming. Computational drug repurposing can help to assign new indications for approved drugs. It is capable to reduce the cost of drug developments. Machine learning models have been introduced to repurpose drugs long before. Recent studies formulate computational drug repurposing problem as a latent link prediction task on a heterogenous network. A number of computational methods have been developed based on graph neural networks.
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18 Views
The requirements, their types and priorities are gathered from 43 project teams which will be uselful to automate the phases of requirement engineering i.e. requirements classification and prioritisation. As the publicly available datasets do not contain the complete information (type and priority) about requirements, the dataset is created by collecting the data from 43 BTech project groups. This dataset includes 11 different types of software requirements. The dependency of requirements is also considered while gathering requirements from the project teams.
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521 Views
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191 Views
The inquiry into the impact of diverse transitions between cross-reality environments on the user experience remains a compelling research endeavor.
Existing work often offers fragmented perspectives on various techniques or confines itself to a singular segment of the reality-virtuality spectrum, be it virtual reality or augmented reality.
This study embarks on bridging this knowledge gap by systematically assessing the effects of six prevalent transitions while users remain immersed in tasks spanning both virtual and physical domains.
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81 Views
The dataset aims to facilitate research in the optimization of the carbon footprint of recipes. Consisting of 30 Excel files processed through various Python scripts and Jupyter notebooks, the dataset serves as a versatile resource for both performance analysis and environmental impact assessment. The unique attribute of this dataset lies in its ability to calculate representative values of carbon footprint optimization through multiple algorithmic implementations.
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231 Views
The dataset, titled "SensorNetGuard: A Dataset for Identifying Malicious Sensor Nodes," comprises 10,000 samples with 21 features. It is designed to facilitate the identification of malicious sensor nodes in a network environment, specifically focusing on IoT-based sensor networks.
General Metrics
§ Node ID: The unique identifier for each node.
§ Timestamp: The time at which data or a packet is sent or received.
§ IP Address: Internet Protocol address of the node.
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2094 Views
This dataset provides valuable insights into Received Signal Reference Power (RSRP) measurements collected from four User Equipment (UE) devices strategically positioned within a moving train.
Additionally, it includes RSRP values obtained from an external reference source using the rooftop train antenna, all systematically interpolated on a cell and frequency basis, with both datasets available.
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783 Views
To test the effectiveness of different ambiguity models in representing real decision-making under ambiguity, we ran an incentivized experiment of choice under ambiguity. The study involved 310 participants recruited using the online international labor market, Amazon Mechanical Turk (MTurk), to participate in an experimental study implemented on the survey platform, Qualtrics. Each of the 310 subjects made 150 preference choices between two options involving variations of the four ambiguity problems with varying levels of ambiguity and risk.
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167 Views