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Search results for: DEEP BELIEF NETWORK
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EMULACJA ŚRODOWISKA DLA ZASTOSOWANIA PROTOKOŁU IN-BAND NETWORK TELEMETRY
PublicationOkreślenie jakości obsługi strumieni pakietów w sieci przełączników wymaga odpowiedniego środowiska badawczego w którym prowadzi się doświadczenia i pomiary wybranych wielkości. Protokół In-band Network Telemetry jest jednym z narzędzi, które można wykorzystać do realizacji tych zadań. W pracy zaproponowano zwirtualizowane środowisko badawcze w którym można emulować sieć przełączników programowalnych w języku P4 wraz z implementacją...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Application of deep eutectic solvents in bioanalysis
PublicationThe application of deep eutectic solvents (DESs) is sharply surging as a green alternative to conventional solvents due to their unique properties in terms of simplicity of preparation, designability and low cost. A great deal of attention has been paid to the application of these green solvents in analytical chemistry in recent years, and a lot of interesting work has been reported. This review summarizes the most relevant applications...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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NATURAL DEEP EUTECTIC SOLVENTS IN EXTRACTION PROCESS
PublicationDeveloping new, eco-friendly solvents which would meet technological and economic demands is perhaps the most popular aspects of Green Chemistry. Natural deep eutectic solvents (NADES) fully meet green chemistry principles. These solvents offer many advantages including biodegradability, low toxicity, sustainability, low costs and simple preparation. This paper provides an overview of knowledge regarding NADES with special emphasis...
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Methods of deep modification of low-bearing soil for the foundation of new and spare air runways
PublicationAfter analyzing the impact of aircraft on the airport pavement (parking spaces, runways, startways), it was considered advisable to consider the problem of deep improvement or strengthening of its subsoil. This is especially true for low-bearing soil. The paper presents a quick and effective method of strengthening the subsoil intended for the construction of engineering structures used for civil...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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The influence of reinforcement on load carrying capacity and cracking of the reinforced concrete deep beam joint
PublicationThe paper presents the results of experimental research of the spatial reinforced concrete deep beam systems orthogonally reinforced and with additional inclined bars. Joint of the deep beams in this research was composed of the longitudinal deep beam with a cantilever suspended at the transversal deep beam. The cantilever deep beam was loaded throughout the depth and the transversal deep beam was loaded at the mid-span by longitudinal...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Application tool for IP QoS network design
PublicationDespite the fact that differentiated-service-aware network implementation has been a widely discussed topic for quite some time, network design still proofs nontrivial. Well developed software could put an end to network designer's problems. This chapter describes work, which has been aimed at creating a comprehensive network design tool, offering a fair range of functionality and high reliability. The presented tool is able to...
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Belief in the importance of socially responsible behaviors – the significance of trust and personal experiences with COVID-19
PublicationA vast number of studies have shown that trust is related to socially desirable traits and behaviors. In the present research we have investigated the relationship between generalized trust and beliefs about the importance of socially responsible behaviors (SRB) during the pandemic – namely, following the sanitary regime and getting vaccinated. Basing on the previous findings we assumed that trustful people...
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How to Sort Them? A Network for LEGO Bricks Classification
PublicationLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Hydrophobic deep eutectic solvents in microextraction techniques–A review
PublicationOver the past decade, deep eutectic solvents (DES) have been widely studied and applied in sample preparation techniques. Until recently, most of the synthesized DES were hydrophilic, which prevented their use in the extraction of aqueous samples. However, after 2015 studies on the synthesis and application of hydrophobic deep eutectic solvents (HDES) has rapidly expanded. Due to unique properties of HDES i.e. density, viscosity,...
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Software Agents for Computer Network Security
PublicationThe chapter presents applications of multi-agent technology for design and implementation of agent-based systems intended to cooperatively solve several critical tasks in the area of computer network security. These systems are Agent-based Generator of Computer Attacks (AGCA), Multi-agent Intrusion Detection and Protection System (MIDPS), Agent-based Environment for Simulation of DDoS Attacks and Defense (AESAD) and Mobile Agent...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Ionic Liquids and Deep Eutectic Mixtures: Sustainable Solvents for Extraction Processes
PublicationIn recent years, ionic liquids and deep eutectic mixtures have demonstrated great potential in extraction processes relevant to several scientific and technological activities. This review focuses on the applicability of these sustainable solvents in a variety of extraction techniques, including but not limited to liquid- and solid-phase (micro) extraction, microwave-assisted extraction, ultrasound-assisted extraction and pressurized...
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Model of control plane of ASON/GMPLS network
PublicationASON (Automatic Switched Optical Network) is a concept of optical network recommended in G.8080/Y.1304 by ITU-T. Control Plane of this network could be based on GMPLS (Generalized Multi-Protocol Label Switching) protocols. This solution, an ASON control plane built on GMPLS protocols is named ASON/GMPLS. In the paper, we decompose the control plane problem and show the main concepts of ASON network. We propose a hierarchical architecture...
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Deep Eutectic Solvents: Properties and Applications in CO2 Separation
PublicationNowadays, many researchers are focused on finding a solution to the problem of global warming. Carbon dioxide is considered to be responsible for the “greenhouse” effect. The largest global emission of industrial CO2 comes from fossil fuel combustion, which makes power plants the perfect point source targets for immediate CO2 emission reductions. A state-of-the-art method for capturing carbon dioxide is chemical absorption using...
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Simulator for Performance Evaluation of ASON/GMPLS Network
PublicationThe hierarchical control plane network architecture of Automatically Switched Optical Network with utilization of Generalized Multi-Protocol Label Switching protocols is compliant to next generation networks requirements and can supply connections with required quality of service, even with incomplete domain information. Considering connection control, connection management and network management, the controllers of this architecture...
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Application of deep eutectic solvents (DES) in analytical chemistry
PublicationRecent years have been associated with efforts to reduce the impact on the natural environment. A greener approach has been introduced in various areas of science, including analytical chemistry. One of the basic procedures for preparing a sample for analysis is its extraction. Traditional methods involve the use of large amounts of organic compounds, often toxic, with an unfavorable impact on the environment. A representative...
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Are deep eutectic solvents useful in chromatography? A short review
PublicationA literature update has been done concerning Deep Eutectic Solvents (DES) use in chromatography applications. The literature survey was based on the period from 2010 till 2020 and manuscripts reported in the data bases Web of Science and Scopus. The use of DES as mobile phase and mobile phase additives, stationary phases and solid phase modifiers and the use of DES as reaction solvents for chromatography use, were evaluated. Emphasis...
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The role of water in deep eutectic solvent-base extraction
PublicationDeep eutectic solvents (DESs) are currently being used in different sectors, such as electrochemistry, electrodeposition, organic synthesis, nanoparticle preparation, bioactive compound separation, etc. Their use in analytical chemistry has only recently begun to expand. Despite the publication of a sufficient number of DES-based analytical extraction procedures, some details, such as interaction of DESwith the sample and target...
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Remarks on use of the term “deep eutectic solvent” in analytical chemistry
PublicationAbout 20 years ago, Abbott and co-workers researched new solvents that were based on mixtures of choline chloride with urea and carboxylic acids and that were liquid at ambient temperature. The term “deep eutectic solvent” (DES) was later adopted for similar mixtures. As DESs have a number of interesting features, they quickly attracted the attention of researchers and found application in various branches of chemical and materials...
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Epoxy/Ionic Liquid-Modified Mica Nanocomposites: Network Formation–Network Degradation Correlation
PublicationWe synthesized pristine mica (Mica) and N-octadecyl-N’-octadecyl imidazolium iodide (IM) modified mica (Mica-IM), characterized it, and applied it at 0.1–5.0 wt.% loading to prepare epoxy nanocomposites. Dynamic differential scanning calorimetry (DSC) was carried out for the analysis of the cure potential and kinetics of epoxy/Mica and epoxy/Mica-IM curing reaction with amine curing agents at low loading of 0.1 wt.% to avoid particle...
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A test of construct isomorphism of the Belief in a Zero-Sum Game scale: A multilevel 43-nation study
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Evolutionary Algorithms in MPLS network designing
PublicationMPLS technology become more and more popular especially in core networks giving great flexibility and compatibility with existing Internet protocols. There is a need to optimal design such networks and optimal bandwidth allocation. Linear Programming is not time efficient and does not solve nonlinear problems. Heuristic algorithms are believed to deal with these disadvantages and the most promising of them are Evolutionary Algorithms....
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Outlier detection method by using deep neural networks
PublicationDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Novel “acid tuned” deep eutectic solvents based on protonated L-proline
PublicationThe paper presents new types of deep eutectic solvents (DESs) based on L-proline protonated using three different acids (hydrochloric, sulfuric and phosphoric)and playing the role of a hydrogen bond acceptor(HBA). Glucose and xylitol were used as hydrogen bond donors (HBD). A series of deep eutectic solvents with various mole ratios were obtained for the systems L-proline: glucose and L-proline: xylitol. Density, melting point,...
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Deep eutectic solvents vs ionic liquids: Similarities and differences
PublicationDeep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Musical Instrument Identification Using Deep Learning Approach
PublicationThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Network effects—do they matter for digital technologies diffusion?
PublicationPurpose The main research target of this paper is to capture the network effects using the case of mobile cellular telephony, identified in European telecommunication markets, and its determinants enhancing the process of digital technologies diffusion. Design/methodology/approach This research relies on panel and dynamic panel regression analysis. The empirical sample covers 30 European countries, and the period for the analysis...
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DWDM Network Laboratory Solution for Telecommunication Education Engineering
PublicationDevelopment of network architectures in the field of optical telecommunications technologies is an indicator of changes in telecommunication education engineering. Conducting didactic classes requires hardware infrastructure and research in terms of teaching needs. In the paper we present DWDM network laboratory solution for telecommunication education engineering on the basis of the ADVA Optical Networking equipment. We have to...
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Information-driven network resilience: Research challenges and perspectives
PublicationInternet designed over 40 years ago was originally focused on host-to-host message delivery in a best-effort manner. However, introduction of new applications over the years have brought about new requirements related with throughput, scalability, mobility, security, connectivity, and availability among others. Additionally, convergence of telecommunications, media, and information technology was responsible for transformation...
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Force transfer and stress distribution in short cantilever deep beams loaded throughout the depth with a various reinforcement
PublicationDeep beams used as the main reinforced concrete structural elements which taking over the load and stiffening construction are often found in high-rise buildings. The architecture of these buildings is sometimes sophisticated and varied, arouse the admiration of the majority of recipients, and thus causing an engineering challenge to correctly design the structural system and force transfer. In such structures is important to shape...
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Application of deep eutectic solvents in atomic absorption spectrometry
PublicationAtomic absorption spectrometry (AAS) is a widely applied technique for metal quantification due to its practicality, easy use and low cost. However, to improve the metrological characteristics of AAS, in particular the sensitivity and the detection limit, sample pretreatment is commonly used before the detection step itself. In consideration of the principles of Green Analytical Chemistry, new solvents are being introduced into...
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublicationIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Transmission protocol simulation framework for the resource-constrained sensor network
PublicationIn this paper the simulation framework for simulation of the sensor network protocol is presented. The framework enables the simultaneous development of the sensor network software and the protocol for the wireless data transmission. The advantage of using the framework is the convergence of the simulation with the real software, because the same software is used in real sensor network nodes and in the simulation framework. The...
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Methods of Network Resource Provisioning for the Future Internet IIP Initiative
PublicationIn this paper, we present specification, design and implementation aspects of a network resource provisioning module introduced for the Polish Initiative of Future Internet called System IIP. In particular, we propose a set of novel LP optimization models of network resource provisioning designed to minimize the network resource consumption, either bandwidth or node’s computational power, as well as to maximize the residual capacity....
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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublicationThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
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Full Network Coverage Monitoring Solutions – The netBaltic System Case
PublicationThis paper defines the problem of monitoring a specific network, and more precisely – part of reporting process, which is responsible for the transport of data collected from network devices to station managers. The environment requires additional assumptions, as a specific network related to the netBaltic Project is to be monitored. Two new monitoring methods (EHBMPvU and EHBMPvF) are proposed, which priority is full network coverage....
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The secure transmission protocol of sensor Ad Hoc network
PublicationThe paper presents a secure protocol of radio Ad Hoc sensor network. This network operates based on TDMA multiple access method. Transmission rate on the radio channel is 57.6 kbps. The paper presents the construction of frames, types of packets and procedures for the authentication, assignment of time slots available to the node, releasing assigned slots and slots assignment conflict detection.
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Challenges and Possibilities of Deep Eutectic Solvent-Based Membranes
PublicationDeep eutectic solvents (DES) are a category of a new class of solvents that can overcome some of the main drawbacks of typical solvents and ionic liquids (ILs). DES have been widely investigated and applied by the research community in several applications since their invention. Over the past years, the use of DES has been directed to the production of new materials and items for new products and processes. This is the case for...
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Generalized access control in hierarchical computer network
PublicationThe paper presents the design of the security layer for a distributed system located in the multizone hierarchical computer network. Depending on the zone from which a client’s request comes to the system and the type of the request, it will be either authorized or rejected. There is one common layer for the access to all the business services and interactions between them. Unlike the commonly used RBAC model, this system enforces...
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Self-Organizing Wireless Nodes Monitoring Network
PublicationThe concept of data monitoring system and self-organizing network of multipurpose data transfer nodes are presented. Two practical applications of this system are also presented. The first of these is the wireless monitoring system for containers, and the second is the mobile monitoring system for gas air pollution measurements.
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...