931 research outputs found
OB00090 - Eran Stone Boar
No full text<a class="mw-redirect" href="https://en.wikipedia.org/wiki/Eran,_India" title="">Eran, Madhya Pradesh</a>.
<a href="https://upload.wikimedia.org/wikipedia/commons/1/10/5th_century_Varaha_boar_statue_with_goddess_earth_hanging%2C_sages_and_saints_reliefs_on_its_body.jpg"></a>
Stone Boar, inscribed with a record of Toramāṇa
OB00045 - Eran Pillar of Goparāja
No full textEran, Madhya Pradesh.
Hero-stone of Goparāja, mentioning Bhānugupta and located near the hamlet of Pahlejpur
DeepMatch: A BERT-powered talent matchmaking approach
No full textConsultancy companies aim to match their employees to customer projects based on their employee’s talents. Traditional matchmaking methodologies are founded on manual processes that rely on rules of thumb or algorithms that are based on handcrafted heuristics, which cause the matchings to be not only sub-optimal, but also time-consuming, subjective, and prone to human errors. In this paper, we propose a novel consultancy matching algorithm that utilizes BERT to semantically find the most optimal consultant-project matchings for a given set of consultants and projects, pairing relevant project specifications with consultant specifications using the JVSAP algorithm. In doing so, our proposed talent matchmaking system may be utilized to improve the accuracy and efficiency of consultancy matching, thereby facilitating more effective consultancy engagements. Our findings suggest that the pairings demonstrate a discernible alignment with human intuition, as evidenced by the consistent correlation between consultants possessing domain-specific expertise and projects characterized by corresponding thematic descriptions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025
Relationships between mobile phone usage and activity-travel behavior: A review of the literature and an example
No full textAlmost everyone has a mobile phone today. In addition to calls and text messages, people are utilizing mobile apps and websites to connect to the world and explore different content anytime and anywhere. The use of smart phones generates billions of records, including spatiotemporal trajectories, and various mobile phone usage details, such as call duration, and frequency of visiting a certain type of website. Most transportation researchers have only focused on spatiotemporal traces, which represent activity-travel behavior of users. However, it is worth making full use of smart phone data to study how mobile phone usage is related to activity-travel behavior. This chapter first reviews the existing literature on the relevant topics to demonstrate the lack of research on the relationship between mobile internet usage and activity-travel behavior. Based on an 11-day dataset from Shanghai that includes not only spatiotemporal traces but also the frequencies of browsing different categories of mobile internet content (e.g., tourism and finance), we examine several relationships between mobile internet usage and activity-travel behavior.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
Empowering Healthcare with Deep Learning:An Application for Early Detection of Skin Cancer
No full textSkin cancer is a hazardous ailment and a leading contributor to mortality. Early diagnosis of skin cancer can significantly minimize or prevent these fatalities. The diagnostic process can be both lengthy and costly. This study aims to establish a basis for creating an exact and effective convolutional neural network (CNN) model for detecting skin cancer. This model aims to enhance the early and accurate diagnosis of skin cancers, potentially leading to a decrease in the number of associated fatalities. The model utilizes a convolutional neural network with Keras Tensor flow as the backend to categorize seven distinct categories of skin cancer. Subsequently, the results are analyzed to determine the practical applications of the model. The Mobile Net optimizer is used for classification. A web application has been developed that offers dermatologists the three most likely diagnostics for a specific blister. It will aid in swiftly recognizing patients with high priorities and accelerating their workflow. The application generates a result within a time frame of 5–10 seconds
Explainable artificial intelligence approach to predict student entrepreneurial competency
No full textThis research employs LightGBM and Explainable Artificial Intelligence (XAI) to forecast entrepreneurial competencies in university students, utilizing a dataset comprising 219 responses from university students. The research processed a diverse dataset by integrating standardization and One-Hot Encoding, resulting in 22 predictive features. The LightGBM model demonstrated a promising accuracy of 71%, with distinct precision and recall metrics. Applying XAI methods like LIME and SHAP, the study ensures interpretability and transparency in model predictions, which is crucial for educational policy and curriculum development. The research underscores the significance of data-centric methodologies in evaluating entrepreneurial skills, which is essential for adapting academic frameworks to current economic landscapes. The outcomes are designed to guide educators and policymakers, supporting and cultivating entrepreneurial talent conducive to innovation and societal advancement
Data compression of stereo images and video
No full textSIGLEAvailable from British Library Document Supply Centre-DSC:DXN032703 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Decentralized multi-agent path finding framework and strategies based on automated negotiation
No full textThis paper introduces a negotiation framework to solve the Multi-Agent Path Finding (MAPF) Problem for self-interested agents in a decentralized fashion. The framework aims to achieve a good trade-off between the privacy of the agents and the effectiveness of solutions. Accordingly, a token-based bilateral negotiation protocol and two negotiation strategies are presented. The experimental results over four different settings of the MAPF problem show that the proposed approach could find conflict-free path solutions albeit suboptimally, especially when the search space is large and high-density. In contrast, Explicit Estimation Conflict-Based Search (EECBS) struggles to find optimal solutions. Besides, deploying a sophisticated negotiation strategy that utilizes information about local density for generating alternative paths can yield remarkably better solution performance in this negotiation framework.Interactive Intelligenc
Novel approach to enhance face recognition using depth maps
No full textFace recognition, although being a popular area of research and study, still has many challenges, and with the appearance of the Microsoft Kinect device, new possibilities of
research were uncovered, one of which is face recognition using the Kinect. With the goal of enhancing face recognition, this
paper is aiming to prove how depth maps, since not effected by illumination, can improve face recognition with a benchmark
algorithm based on the Eigenface. This required some experiments to be carried out, mainly in order to check if algorithms created to recognize faces using normal images can be as effective if not more effective with depth map images. The OpenCV Eigenface algorithm implementation was used for the purpose of training and testing both normal and depth-map images. Finally, results of the experiments are presented to prove the ability of the tested algorithm to function with depth maps, also, proving the capability of depth maps face recognition’s task in poor illumination
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