Search
Filters
total: 356
filtered: 326
Search results for: phylogenetic tree metric
-
Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
-
Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublicationThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
-
Application of adjusted subpixel method (ASM) in HRCT measurements of the bronchi in bronchial asthma patients and healthy individuals
PublicationBackground: Recently, we described a model system which included corrections of high-resolution computedtomography (HRCT) bronchial measurements based on the adjusted subpixel method (ASM).Objective: To verify the clinical application of ASM by comparing bronchial measurements obtained bymeans of the traditional eye-driven method, subpixel method alone and ASM in a group comprised ofbronchial asthma patients and healthy individuals.Methods:...
-
Knowledge management in the IPv6 migration process
PublicationThere are many reasons to deploy IPv6 protocol with IPv4 address space depletion being the most obvious. Unfortunately, migration to IPv6 protocol seems slower than anticipated. To improve pace of the IPv6 deployment, authors of the article developed an application that supports the migration process. Its main purpose is to help less experienced network administrators to facilitate the migration process with a particular target...
-
Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
-
Antiproliferative, Antiangiogenic, and Antimetastatic Therapy Response by Mangiferin in a Syngeneic Immunocompetent Colorectal Cancer Mouse Model Involves Changes in Mitochondrial Energy Metabolism
PublicationIn spite of the current advances and achievements in cancer treatments, colorectal cancer (CRC) persists as one of the most prevalent and deadly tumor types in both men and women worldwide. Drug resistance, adverse side effects and high rate of angiogenesis, metastasis and tumor relapse remain one of the greatest challenges in long-term management of CRC and urges need for new leads of anticancer drugs. We demonstrate that CRC...
-
Spatial Distribution of Eucalyptus Plantation and its Impact on the Depletion of Groundwater Resources of Tehsil Swat Ranizai, District Malakand
PublicationNative to the continent of Australia, eucalyptus is a tall, evergreen tree belonging to the Myrtaceae family. Malakand district has the largest eucalyptus plantation in the province, covering an area of 22,071.29 ha. The present study aims to evaluate its impact on the groundwater table (GWT) in three selected union councils (UCs) of the study area, i.e., Agra, Totakan, and Kot. Both primary and secondary data support the study....
-
Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublicationGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...
-
Lignocellulosic waste biosorbents infused with deep eutectic solvents for biogas desulfurization
PublicationThis paper introduces an innovative method for treating biogas streams, employing lignocellulosic biosorbents infused with environmentally friendly solvents known as deep eutectic solvents (DES). The primary focus of this study was the elimination of volatile organosulfur compounds (VSCs) from model biogas. Biosorbents, including energetic poplar wood, antipka tree, corncobs, and beech wood, were used, each with varying levels...
-
Review of Recent Advancement on Nature/Bio-inspired Antenna Designs
PublicationThis article presents an extensive examination of antennas rooted in nature and biology, showcasing their remarkable performance across a wide spectrum of frequencies—from microwave to terahertz. The limitations of traditional antenna design have become increasingly evident in the face of burgeoning demands for novel communication technologies. Conventional analytical-equation-based approaches struggle to deliver the combined performance...
-
The effect of road restraint systems on the level of road safety - Polish experience
PublicationRoadside accidents happen when a vehicle runs off the road. The majority of these accidents are very severe because leaving the road is usually followed by hitting a solid obstacle (tree, pole, support, culvert front wall, barrier). Roadsides are some of the most important issues of road safety. They have been studied for years to identify roadside hazards and the effectiveness of road safety measures such as restraint systems....
-
Intelligent Decision Forest Models for Customer Churn Prediction
PublicationCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
-
Analysis of IPv6 handovers in IEEE 802.16 environment
PublicationThe second generation of WiMAX solutions, based on IEEE 802.16-2005 standard, offers limited mobility support. Unfortunately, after quickly changing the point of attachment on the WiMAX data link layer (DLL), very slow and inefficient IPv6 reconfiguration takes place. Delays introduced by automatic configuration (DHCPv6 and IPv6 protocols) and Mobile IPv6 can easily diminish or even render useless all benefits gained using the...
-
DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
-
Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
-
Ultrasound and Clinical Preoperative Characteristics for Discrimination Between Ovarian Metastatic Colorectal Cancer and Primary Ovarian Cancer: A Case-Control Study
PublicationThe aim of this study was to describe the clinical and sonographic features of ovarian metastases originating from colorectal cancer (mCRC), and to discriminate mCRC from primary ovarian cancer (OC). We conducted a multi-institutional, retrospective study of consecutive patients with ovarian mCRC who had undergone ultrasound examination using the International Ovarian Tumor Analysis (IOTA) terminology, with the addition of evaluating...
-
Data-driven Models for Predicting Compressive Strength of 3D-printed Fiber-Reinforced Concrete using Interpretable Machine Learning Algorithms
Publication3D printing technology is growing swiftly in the construction sector due to its numerous benefits, such as intricate designs, quicker construction, waste reduction, environmental friendliness, cost savings, and enhanced safety. Nevertheless, optimizing the concrete mix for 3D printing is a challenging task due to the numerous factors involved, requiring extensive experimentation. Therefore, this study used three machine learning...
-
Deep eutectic solvent-based shaking-assisted extraction for determination of bioactive compounds from Norway spruce roots
PublicationPolyphenolic compounds play an essential role in plant growth, reproduction, and defense mechanisms against pathogens and environmental stresses. Extracting these compounds is the initial step in assessing phytochemical changes, where the choice of extraction method significantly influences the extracted analytes. However, due to environmental factors, analyzing numerous samples is necessary for statistically significant results,...
-
A method of trust case templates to support standards conformity achievement and assessment
PublicationOsiąganie i ocena zgodności ze standardami stanowi poważne obciążenie finansowe dla współczesnych gospodarek. Pomimo znacznej wagi tego problemu, nie znalazł on jednak zadowalającego przełożenia na rozwiązania dostępne na rynku. W tej pracy zaproponowano metodę nazwaną Standards Conformity Framework (SCF), która wspiera stosowanie standardów. Jest ona oparta na spostrzeżeniu, że osiąganie i ocena zgodności ze standardem polega...
-
Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
-
Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
-
A perfect hashing incremental scheme for unranked trees using pseudo-minimal automata
PublicationWe describe a technique that maps unranked trees to arbitrary hash codes using a bottom-up deterministic tree automaton (DTA). In contrast to other hashing techniques based on automata, our procedure builds a pseudo-minimal DTA for this purpose. A pseudo-minimal automaton may be larger than the minimal one accepting the same language but, in turn, it contains proper elements (states or transitions that are unique) for every input...
-
Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
-
Use of LIDAR Data in the 3D/4D Analyses of the Krakow Fortress Objects
PublicationThe article presents partial results of studies within the framework of the international project "Cultural Heritage Through Time" (CHT2). The subject of the study were forts of the Krakow Fortress, which had been built by the Austrians between 1849-1914 in order to provide defence against the Russians. Research works were aimed at identifying architectural changes occurring in different time periods in relation to selected...
-
Analysis of IPv6 Handovers in IEEE 802.16 environment
PublicationZaprezentowano pełną analizę wpływu poszczególnych faz procesu przełączania w warstwie drugiej i trzeciej na przerwy w transmisji wynikające ze zmiany stacji bazowej BS przez przemieszczający się węzeł ruchomy MN. Zaproponowano i przebadano symulacyjnie 10 scenariuszy przełączania, w tym 8 różnych algorytmów stanowej autokonfiguracji węzłów MN, wspierających protokół IPv6 w środowiskach sieci WiMAX. W badaniach wskazano na możliwości...
-
Elective surgery system strengthening: development, measurement, and validation of the surgical preparedness index across 1632 hospitals in 119 countries
Publication