AN INFLUENCER NODE IDENTIFICATION USING HYBRID MACHINE LEARNING TECHNIQUES
Influential node detection in networks is vital in diverse applications, particularly with the online social networks (OSNs). Measures of centrality, traditional ones, fail to sufficiently describe the influence of nodes on complex and multilayered networks. This paper presents a novel hybrid method that combines traditional topological centrality ...
By CS. Saradha
PERFORMANCE ANALYSIS OF DOWN SYNDROME DETECTION SYSTEM USING ULTRA SOUND FETUS IMAGES AND DEEP LEARNING CLASSIFICATION METHODS
Down Syndrome (DS) is a genetic disorder due to a partial copy of the 21 st chromosome in the fetus, usually detected by invasive techniques like Amniocentesis and Chorionic Villus Sampling (CVS) which have chances of miscarriage. This paper suggests a completely automated and computer-aided method of non-invasive detection of DS by ultrasound fetu...
By V. Gokulakrishnan, S. Selvakumar
ACCURACY ANALYSIS WITH ZYCOTHERM ADDITIVE TO IMPROVE THE PHYSICAL-MECHANICAL PROPERTIES OF THE ASPHALT LAYER IN CLAYEY SOILS
This research examines how asphalt mixtures that are modified with Zycotherm can help the mixtures have an enhanced resistance to damage caused by moisture which has not been well researched in previous studies. Hydraulic deterioration of asphalt and in particular the clay soils contribute greatly to the strength and lifespan of the road surfaces. ...
By Jeremy Mel Garcia Bazan, Manuel Alejandro Torres Arroyo, Neicer Campos Vasquez, Abel Carmona Arteaga
A DEEP ENSEMBLE LEARNING AND INTELLIGENT HYBRID FEATURE EXTRACTION MODEL FOR THE PEST DETECTION AND CLASSIFICATION IN CLOUD COMPUTING
This study presents an advanced approach for Pest Detection (PD) through automatic identification of invasive insects using Deep Ensemble Learning (DEL) and intelligent Feature Extraction (FE) techniques. The process begins with Z-score normalization (ZSN) to eliminate noise and improve classifier performance. Improved Feature Weighted Fuzzy Cluste...
By P. Bharathi, K. Dhanalakshmi
PRECIPITATION GENERATION FOR VARIOUS RETURN PERIODS USING RAIN4PE AND PISCOP V2.1 GRIDDED PRODUCTS IN THE SUPE RIVER BASIN
This paper examines the distribution of maximum precipitation of the Supe basin at the return periods of 10, 100, 1000, and 10,000 years using Weibull technique to estimate return time. They compare PISCOp v2.1 and RAIN4PE which are two gridded rain products to evaluate their predictability in terms of extreme precipitation occurrences. These gridd...
By Rengifo-Arevalo Jhon Filips, Agramonte-Monge Henry Fabian, Abel Carmona Arteaga, Campos-Vasquez Neicer
DETERMINATION OF CACAO QUALITY USING THE MUMFORD-SHAH FUNCTIONAL ALGORITHM AND IMAGE SEGMENTATION
One of the major issues in the agricultural industry is cocoa quality determination that may be based on subjective sensory assessment techniques that may cause inconsistency and losses after harvesting. The following research will solve the set of issues by taking the Mumford-Shah functional algorithm with the image segmentation, to evaluate the q...
By Eduardo Arturo Guillen Bazan, Pablo Cesar Medrano Nina, Neicer Campos Vasquez
PROPERTIES, SYNTHESIS, AND APPLICATIONS OF NANOMATERIALS: FOCUS ON METAL OXIDE NANOPARTICLES
Nanoscience and nanotechnology transformed material science with the introduction of nanomaterials that have special physical, chemical, optical, and mechanical characteristics because of their tiny size on the nanoscale. The materials have superior surface areas, quantum imagery, and unique electrical properties when compared to bulk materials, wh...
By Anil Kumar, Swati, Niharika
LEVERAGING STRATEGIC MARKETING ANALYTICS TO DRIVE COMPETITIVE ADVANTAGE IN DATA-DRIVEN MARKETS
This research paper examines how the strategic marketing analytics, which combines big data, artificial intelligence (AI), and knowledge management can be used to improve the competitive advantage in data-driven markets. The research tests the effectiveness of AI-driven analytics in enhancing the performance of the market, customer high retention a...
By M. Venith Vijay, Vijayakanthan Selvaraj, R. Muzhumathi, P. Sundara BalaMurugan
PROXIMAL CARIES DETECTION USING YOLOV11 IN NEAR-INFRARED LIGHT TRANSILLUMINATION IMAGES
The study will be conducted to complement the diagnosis of proximal caries lesions that are difficult to improve due to their location between the teeth, as shown in Near-Infrared Light Transillumination (NILT) photographs. It was proposed to enhance caries detection with a semantic segmentation model based on YOLOv11, which is more specific in det...
By Asma Alatawi, Wdaee Alhalabi, Hani Nassar, Arwa Basbrain, Hattan Jamalellail, Mohammed Alsadat
A NOVEL TRANSFER DEEP LEARNING FRAMEWORK WITH CROSS-LINGUAL EMBEDDINGS FOR HIGH-RESOURCE AND LOW RESOURCE LANGUAGES FOR SENTIMENT ANALYSIS
Sentiment analysis (SA) is important in comprehending the opinions and online discussions of people in different languages, particularly in high-resource and low-resource languages. In the present paper, a new model of transfer deep learning is presented, which incorporates cross-lingual embeddings in an attempt to boost sentiment analysis in both ...
By Jayaprakash Vattikundala, M. Siva Ganga Prasad