Wyniki wyszukiwania dla: lstm
-
ARIMA vs LSTM on NASDAQ stock exchange data
PublikacjaThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
-
LSTM-based method for LOS/NLOS identification in an indoor environment
PublikacjaDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
-
Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
-
Using LSTM networks to predict engine condition on large scale data processing framework
Publikacja -
Using LSTM networks to predict engine condition on large scale data processing framework
PublikacjaAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
-
Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublikacjaIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
-
OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublikacjaCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
-
CORROSION TESTING OF SAMPLES ACCORDING TO ASTM G36
PublikacjaAt the end of the study, samples were found to have structures characteristic for intercrystalline corrosion. This indicates that the samples provided (fragments of the whole) were sensitized before starting the study in boiling MgCl2.On cross sections, fine cracks are observed on all samples tested.
-
Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublikacjaThis paper presents an algorithm for real‐time detection of the heart rate measured on a person’s wrist using a wearable device with a photoplethysmographic (PPG) sensor and accelerometer. The proposed algorithm consists of an appropriately trained LSTM network and the Time‐Domain Heart Rate (TDHR) algorithm for peak detection in the PPG waveform. The Long Short‐Term Memory (LSTM) network uses the signals from the accelerometer...
-
Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
Publikacja -
Nanostructure characterization of (SmS)1.19TaS2 by means of STM/STS
PublikacjaW publikacji przedstawiono badania za pomocą techniki STM i STS powierzchni kryształów warstwowego związki typu misfit(SmS)1.19TaS2. Badania pozwalają sądzić, że powierzchniową warstwą jest warstwa Sm-S.
-
Eksperymentalna weryfikacja procedury szacowania wytrzymałości młodego betonu wg normy ASTM C1074
PublikacjaW referacie przedstawiono metodę służącą oszacowaniu wytrzymałości betonu w trakcie procesu dojrzewania (ang. Maturity Method) bazującą na procedurze określonej zgodnie z amerykańską normą, która uwzględnia wpływ połączonych efektów temperatury i czasu na rozwój wytrzymałości betonu. Standardy ASTM C1074 zostały opracowane przez NBS (ang. National Bureau of Standards) z uwagi na powtarzające się wypadki na palcu budowy wynikające...
-
Wyznaczanie wytrzymałości betonu na podstawie funkcji dojrzałości wg amerykańskiej normy ASTM C1074-11
PublikacjaArtykuł poświęcono wyznaczaniu wytrzymałości betonu na podstawie funkcji dojrzałości wg normy ASTM C1074-11 (ang. Maturity Method). Metoda bazuje na rejestracji zmian tem - peratury w trakcie hydratacji dojrzewającego betonu. Wartykule zaprezentowano procedurę badawczą służącą wyznaczeniu funk - cji dojrzałości dla wybranej mieszanki betonowej oraz zależności wytrzymałość-dojrzałość. Celem badań jest wyznaczanie zmian w czasie...
-
Validation of result of STM probe fabrication
Dane BadawczeThe scanning tunneling microscope [1] is a powerful research tool that allows, among other things, to obtain images with atomic resolution. A serious limitation of the described microscope is its limited applicability relating to conductive and semiconductor materials and the reproducibility of measurements depending on the preparation of the measuring...
-
SEM images of SFM, LSFM and SFMNb in as-prepared state and reduced
Dane BadawczeThis dataset contains SEM images taken for pristine strontium ferrite molybdate, as well as ones doped with lanthanum or niobium. Materials were characterized in powder, under high vacuum in secondary electron mode. The images are divided into folders for as-prepared samples and reduced (H2, 800 deg, 4 h) ones.
-
Group-type analysis of middle distillates by test method IP-391/EN-12916/ASTM D6379 in terms of resolution and selectivity of chromatographic columns
PublikacjaNa podstawie wyników badań z zastosowaniem różnych kolumn typu NH2 opisano wpływ selektywności wypełnienia kolumn HPLC na wyniki analizy grupowej węglowodorów aromatycznych oraz określono wymagania jakie powinna spełniać kolumna do oznaczania grup węglowodorów aromatycznych w średnich destylatach ropy naftowej. Badania przeprowadzono stosując metodykę analityczną według normy IP-391/EN-12916 albo ASTM D 6379.
-
Measuring moisture damage of hot-mix asphalt (HMA) by digital imaging-assisted modified boiling test (ASTM D3625): Recent advancements and further investigation
Publikacja -
Toward mechanosynthesis of diamondoid sructures: viii. quantum-chemical molecular dynamics simulations of hexagonal silicon-iv structure synthesis with stm
Publikacjaw tej publikacji badano metodami kwantowo-chemicznymi różne strategie mechanosyntezy heksagonalnego krzemu iv. określono przybliżone warunki mechanosyntezy krzemu w formie lonsdaleitu za pomocą uhv-spm.
-
News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublikacjaStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
-
A Simple Neural Network for Collision Detection of Collaborative Robots
PublikacjaDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
-
Toward Mechanosynthesis of Diamondoid Structures: VI. Quantum-Chemical Molecular Dynamics Comparison of Conditions for the STM Tip Driven Mechanosynthesis on Hydrogenated Si(111), Si(110) and Si(100) Surfaces.
Publikacjamożliwość prototypowania przejściowych generacji nano-urządzeń otrzymanych drogą pozycjonowanej mechanosyntezy za pomocą stm wyposażonego w ostrze typu swcnt są analizowane metodą kwantowo-chemicznej dynamiki molekularnej. proponowana strategia syntezy polega na insercji atomów si oraz cząsteczek sih2 we wiązania si-h na uwodornionej powierzchni si(111), si(110) oraz si(100) kryształu krzemu. rezultaty modelowania sugerują, że...
-
Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublikacjaLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
-
Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublikacjaPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
-
An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
-
Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
PublikacjaInstalling photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based...
-
Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublikacjaThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
-
Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublikacjaIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
-
Characteristics of La0.8Sr0.2Ga0.8Mg0.2O3-delta -supported micro-tubular solid oxide fuel cells with bi-layer and tri-layer electrolytes
PublikacjaIn this study, La0.8Sr0.2Ga0.8Mg0.2O3−δ (LSGM)-supported micro tubular solid oxide fuel cells (T-SOFCs) with two different configurations, one containing an LSGM–Ce0.6La0.4O2−δ (LDC) bi-layer electrolyte (Cell A) and one containing an LDC–LSGM–LDC tri-layer electrolyte (Cell B), were fabricated using extrusion and dip-coating. After optimizing the paste formulation for extrusion, the flexural strength of the dense and uniform LSGM...
-
Characteristics of La 0.8 Sr 0.2 Ga 0.8 Mg 0.2 O 3-δ -supported micro-tubular solid oxide fuel cells with LaCo 0.4 Ni 0.6-x Cu x O 3-δ cathodes
PublikacjaIn this study, micro-tubular solid oxide fuel cells (T-SOFCs) with extruded La0.8Sr0.2Ga0.8Mg0.2O3-δ (LSGM) electrolyte as the mechanical support and LaCo0.4Ni0.6O3-δ (LCNO) or LaCo0.4Ni0.4Cu0.2O3-δ (LCNCO) as cathodes were prepared and characterized. Partial substitution of Cu for the Ni-ion positions in the LCNO lattices was found to significantly enhance the densification and accelerate the grain growth. The porosity-corrected...
-
Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
-
Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublikacjaThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
-
APPLICATION OF SATELLITE IMAGERY AND GIS TOOLS FOR LAND SURFACE TEMPERATURE ESTIMATION AND VERIFICATION
PublikacjaLand surface temperature (LST) plays an important role in many land-surface processes on regional as well on global scales. It is also a good indicator of energy flux phenomena and is used as a parameter in various Earth observation related studies. However, LST estimation based on processing and utilisation of satellite derived data constitutes several problems in terms of time limitations, accessibility, atmospheric influence...
-
Development of an AI-based audiogram classification method for patient referral
PublikacjaHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
-
Investigation methods of ionic conductivity measurements in polycrystalline MIEC (mixed ionic-electronic conductor) based on perovskite ceramics
PublikacjaPaper about the measurements of ionic conductivity in LSM and strontium titanate ceramics.
-
Identification of Shift in Sowing and Harvesting Dates of Rice Crop (L. Oryza sativa) through Remote Sensing Techniques: A Case Study of Larkana District
PublikacjaThe present study aimed to determine the impact of climate variability on rice crops in terms of sowing and harvesting dates and crop period. The identification of sowing and harvesting dates were spotted by mask identification, variations in land surface temperature (LST) on a temporal scale in the respective months, and a field-level social inquiry. The study was conducted during a time period (1994–2017), in which geo-referenced...
-
High temperature XRD diffraction patterns collected during the reoxidation process of SFM-based compounds
Dane BadawczeThis dataset contains three file folders for SFM, LSFM (La-doped) and SFMNb (Nb-doped) respectively. Samples were reduced prior to the XRD measurements. The measurements were performed on Philipps X’Pert Pro diffractometer using a high-temperature Anthon Paar HT-1200 oven adapter. Scans were performed each 50 deg. in air. The data in dataset were already...
-
Neural networks and deep learning
PublikacjaIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
-
Pawel Polaczyk dr inż.
OsobyDr. Pawel Polaczyk is a scholar in civil engineering and a civil engineering practitioner in pavement engineering. Dr. Polaczyk is originally from Warsaw, Poland, where he received his B.Sc. degree in Civil Engineering with a concentration in Transportation from Warsaw University of Technology. His Master`s and Doctorate degrees in Civil Engineering with a concentration in Geotechnology and Materials Engineering are from the University...
-
Mechanical properties of two-stage concrete modified by silica fume
PublikacjaAbstract. Two-stage concretes, despite the fact that they have proven themselves in various types of construction, have not been studied to the same extent as traditional heavy concretes. Therefore, the article developed the composition of frame concrete with various additives in the composition of the cement-sand mortar. A comparison of the mechanical characteristics of the developed compositions with the addition of silica fume...
-
Experimental and Numerical Study on Mechanical Characteristics of Aluminum/Glass Fiber Composite Laminates
PublikacjaThe fiber-metal composites made of aluminum sheets and glass fibers reinforced with a polyester resin as the matrix were studied. The composites were prepared by hand lay-up method. Some aspects of manufacturing affecting the composite behavior were considered. In particular, the influences of the arrangement of layers and their number on the mechanical and physical properties of composites with ten different compositions were...
-
Functionalization of electrode surfaces with monolayers of azocompounds and gold clusters.
PublikacjaWłaściwości monowarstw z azokoron na powierzchni złota były badane przy pomocy woltametrii i STM. Powierzchnia przypadająca na cząsteczkę została wyznaczona przy pomocy woltametrii i wynosi 0,65 nm kwadratowych. Wartość ta jest zgodna z wyznaczoną w oparciu o monowarstwę utworzoną na granicy powietrze-woda techniką Langmir-Blodgett. Tworzenie się klasterów złota i innych struktur obserwowano przy pomocy STM w przypadku gdy złota...
-
Effects of La0.8Sr0.2MnO3 and Ag electrodes on bismuth-oxide-based low-temperature solid electrolyte oxygen generators
PublikacjaIn this study, La0.8Sr0.2MnO3 (LSM) was used as the ceramic electrode in a (Bi1.50Y0.50)0.98Zr0.04O3+δ (BYO)-based solid electrolyte oxygen generator (SEOG) and its performance was compared with that of a previously studied high-fire Ag electrode. Among La0.6Sr0.4Co0.2Fe0.8O3, LaNi0.6Fe0.4O3, Cu1.4Mn1.6O4, and LSM materials, only LSM materials did not trigger any chemical reaction or interdiffusion with BYO at temperatures up to...
-
Corrosion resistance of dissimilar austenite and duplex steels welded joints
PublikacjaW artykule przedstawiono wpływ warunków spawania, a zwłaszcza energii liniowej, na odporność korozyjną złączy różnoimiennych stali austenitycznej 316L i typu duplex 2203. Przedstawiono wyniki testów korozyjnych:korozji wżerowej wg ASTM G48 oraz korozji naprężeniowej badanej w próbach odkształcania z małą pędkością w środowisku roztworu chlorku magnezowego.
-
Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk
PublikacjaSatellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth’s environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land...
-
The SEM micrographs of the synergistic action between cavitation erosion and pitting corrosion on stainless steel 304
Dane BadawczeThe dataset contains Scanning Electron Micrographs of stainless steel AISI304 samples made after cavitation erosion-corrosion exposure using a vibratory transducer (in accordance with ASTM G32). The micrographs compare the topography of samples subjected to either cavitation erosion (in deionized water), pitting corrosion (in 8% FeCl3 solution, without...
-
Evaluation of antimicrobial properties of thermomelt adhesives modified with zinc compounds
Dane BadawczeThe dataset contains the results of microbiological tests of thermomelt adhesives modified with zinc compounds, whose activity was assessed for their ability to reduce the number of Escherichia coli and Staphylococcus aureus strain, representing the Gram (-) and Gram (+) bacteria, respectively. The evaluation of antimicrobial properties of samples were...
-
High-performance anode-supported solid oxide fuel cells with co-fired Sm0.2Ce0.8O2-δ/La0.8Sr0.2Ga0.8Mg0.2O3−δ/Sm0.2Ce0.8O2-δ sandwiched electrolyte
PublikacjaIn this study, intermediate-temperature solid oxide fuel cells (IT-SOFCs) with a nine-layer structure are constructed via a simple method based on the cost-effective tape casting-screen printing-co-firing process with the structure composed of a NiO-based four-layer anode, a Sm0.2Ce0·8O2-δ(SDC)/La0·8Sr0.2Ga0.8Mg0·2O3−δ (LSGM)/SDC tri-layer electrolyte, and an La0·6Sr0·4Co0·2Fe0·8O3-δ (LSCF)-based bi-layer cathode. The resultant...
-
Decision making process using deep learning
PublikacjaEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
-
The SEM micrographs of the cavitation erosion-corrosion process of selected copper alloys degradation
Dane BadawczeThe dataset contains Scanning Electron Micrographs of CuZn40Mn3Fe brass compared with Superston and Novoston bronze after cavitation erosion-corrosion exposure using a vibratory transducer (in accordance with ASTM G32). The micrographs compare the topography of samples subjected cavitation erosion in 3% NaCl at room temperature, leading to the surface...
-
SEM micrographs of cavitation erosion-corrosion of aluminium alloy 2024 with anodic polarization
Dane BadawczeThe dataset contains Scanning Electron Micrographs of aluminium alloy 2024 samples made after cavitation erosion-corrosion exposure using a vibratory transducer (in accordance with ASTM G32). The experiment duration was 240 min, with cyclic cavitation exposure in on/off cycles 30s:30s. The electrolyte was 0.1 M KNO3 solution. Some samples were anodically...