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检索条件"任意字段=23rd International Conference on Control Systems and Computer Science Technologies, CSCS 2021"

共 285 条记录，以下是51-60 订阅

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Insights into Romania's Economic Development Using Satellite Imagery 23

Insights into Romania's Economic Development Using Satellite...

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Draghici, Marius-Robert Ciobanu, Radu Ioan University Politehnica of Bucharest Faculty of Automatic Control and Computers Bucharest Romania

ISBN: (纸本)9781665439398

The assessment of the economic development of a country, both at local and at national level, allows the government and other organizations to provide sufficient financial and material resources in order to ensure the well-being of the population. Such an assessment relies on data about key social, environmental and economic indicators such as healthcare and mortality data, food security, wealth inequality assessment among others. However, this kind of data is obtained through costly on-the-ground surveys which are conducted at intervals of several years and yield too few information to properly use it. In order to deal with this lack of data, other sources need to be found. The recent progress in space and imaging technologies has made satellite imagery with higher resolution more affordable and abundant. In particular, nighttime lights satellite imagery such as that provided by the DMSP-OLS and NPP-VIIRS programs has proven useful as a proxy for measuring the level of economic development of a certain region. The objective of this paper is to gain insights into the economic development of Romania by leveraging the available nighttime lights satellite imagery datasets and data analysis techniques. © 2021 IEEE.

关键词： Satellite imagery

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Detection and Diagnosis of Skin Cancer Based on K-Means Cluster and Convolutional Neural Network 23

Detection and Diagnosis of Skin Cancer Based on K-Means Clus...

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Shihab, Ahmed Salah, Hussein Mocanu, Mariana College of Nursing University of Baghdad Department of Basic Sciences Baghdad Iraq Department of Computer Systems Technical Institute-Suwaira University of Middle Technical Iraq Faculty of Automatic Control and Computer University POLITEHNICA of Bucharest Bucharest Romania Faculty of Automatic Control and Computer University POLITEHNICA Baghdad Iraq

ISBN: (纸本)9781665439398

Early detection of skin cancer can contribute significantly in preventing the exacerbation of the condition and its transformation into a benign tumor, reducing the number of deaths in skin cancer. This paper introduces the application of K-means cluster for detecting the skin tumor and the Convolutional Neural Network (CNN) for automatic diagnosis of skin tumor. The specific steps are as follows: The first step reads the skin cancer image, the second step 'preprocessing, which is achieved by applying the Gaussian filter, to improve the skin image and reduce noise, the third step: utilizing K-means cluster applied for segmentation image into two groups. The first group is represented by the background (largest area) and second group represents the skin tumor (least area). The last step (The fourth one): applying CNN to classify the skin tumor as benign or malignant. The results show that the proposed technique functions more efficiently by achieving 99.7% accuracy, obtained from the total of 22, 080 medical images based on DermQuest Digital Dataset. © 2021 IEEE.

关键词： Image segmentation

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The PIMEO AI project - A Cloud based platform for water quality monitoring 23

The PIMEO AI project - A Cloud based platform for water qual...

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Iordache, George Balanescu, Mihaela Suciu, George Birdici, Andrei Pasat, Adrian Zatreanu, Ionel Paun, Mirel Bucuci, Stefania Beia Consult International Research and Development Dept. Bucharest Romania Constanta Maritime University Electronics and Telecommunications Department Constanta Romania

ISBN: (纸本)9781665439398

The importance of assessing the water quality in different ecosystems is increasing with the continuous development of human activities, especially with water pollution. This article presents the PIMEO AI project that has the purpose of monitoring water quality in highly sensitive and fragile ecosystems. The article also presents a state of the art about how to model data when discussing about water quality management and modelling. Furthermore, we present the required functionalities of the platform that needs to be developed in the PIMEO AI project, some data validation and preprocessing methodologies that we propose for the project and the use cases that we consider within the project. © 2021 IEEE.

关键词： Machine learning

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On Complexity and Topology Measures for Evaluation of Intercellular Connectivity in Human Colon Adenocarcinomas 23

On Complexity and Topology Measures for Evaluation of Interc...

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Waliszewski, Przemyslaw Banaszak, Grzegorz Ameos Clinics GmbH Dept. of Urology Alfeld Germany Adam Mickiewicz University Fac. of Mathematics and Computer Sci. Poznań Poland

ISBN: (纸本)9781665439398

We report here on the results of co-application of complexity and topological measures in the evaluation of intercellular connectivity;a critical feature of cancer cells that determines their metastatic potential. We studied fractal geometry and topology of intestinal crypts in 10 different specimens of human normal colon and in 40 colon carcinomas. Our findings confirm the previous observations made in a model of prostate carcinomas. The natural evolution of the spatial structure in carcinomas is determined by increasing values of entropy and goes towards increased complexity. Intercellular connectivity in colon carcinomas is decreased in comparison with normal intestinal crypts. That conclusion is supported by changes in both global and local measures of complexity as well as topology. The values of both the global and local spatial fractal dimensions are increased and the values of the 1st-Betti numbers are decreased. At the local scale, one observes variability of the local clustering coefficient from zero to one. The combination of complexity and topology measures enables the objective selection of the reference set of carcinomas for the quantitative evaluation of biological tumor aggressiveness by convoluted neural network. © 2021 IEEE.

关键词： Topology

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Anomaly detection in water supply infrastructure systems 23

Anomaly detection in water supply infrastructure systems

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Sebestyen, Gheorghe Hangan, Anca Czako, Zoltan Technical University of Cluj-Napoca Department of Computer Science Cluj-Napoca Romania

ISBN: (纸本)9781665439398

Water provisioning is a critical public service that has a direct impact on the welfare and security of the population. Modern water supply infrastructures are complex cyber-physical systems that involve physical equivalents (e.g. pipes, pumps, containers, treatment stations, etc.) as well as automation and monitoring devices. The main challenges for such a system are: uninterrupted supply of quality water, optimal distribution of water reserves and efficient use of existing resources. Anomaly detection in water supply infrastructures is an important aspect that influences the proper functioning and the security of the entire system. As such infrastructures become more and more complex, anomaly detection must be performed in an automated way. But, making the difference between a normal and an abnormal behavior is not a simple task;it requires machine learning (ML) techniques and artificial intelligence (AI) algorithms. This paper presents an automated method of selecting and tuning the best AI model that has the ability to classify the input data as normal or abnormal. © 2021 IEEE.

关键词： Anomaly detection

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Cyber-Physical systems - A New Approach for Keyless Entry systems 23

Cyber-Physical Systems - A New Approach for Keyless Entry Sy...

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Balaban, Beatrix-May Sacala, Ioan Stefan Petrescu-Nita, Alina Claudia Pop, Florin University Politehnica of Bucharest Department of System Engineering Faculty of Automatic Control and Computers Bucharest Romania

ISBN: (纸本)9781665439398

Nowadays, intelligent vehicles are becoming more and more important in the transportation field. What makes such a vehicle vulnerable is the number of interconnected components that individually have a strong security but can cause weakness points when they are connected. The challenge is to design and build a powerful system that uses both cyber-physical components. The proposed model is a system with integrated modules for fingerprint and face recognition to certify that a driver has the right to access the vehicle. The aim is to develop a security system for intelligent vehicles that can be also a secure keyless entry system using the power of biometrics. When a driver approaches the car, a sensor will activate the recognition modules. Only after the total completion of the recognition process the driver is authenticated and has the right to use the vehicle. We simulated real-time face detection and eye tracking using Matlab 2020a. Face detection is performed using Viola-Jones algorithms and the tracking is made with bbox-es. Besides normal conditions, other tests were made to challenge the algorithm, for example: angle rotations, the use of glasses, face mask, glasses and face mask together. © 2021 IEEE.

关键词： Cyber Physical System

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Balancing objects on DOORS nodes 23

Balancing objects on DOORS nodes

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Palanciuc, Dorin Pop, Florin University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science Department Romania National Institute for Research and Development in Informatics ICI Bucharest Romania

ISBN: (纸本)9781665439398

In the context of DOORS, a medium-scale distributed system, running on tens of 'normal PCs and/or embedded devices, we propose a solution for the problem of efficient allocation of execution and storage resources. We distinguish between the node-level problem of scheduling the execution of object methods and the system-level problem of optimally placing objects on nodes such that locality is maximised: inter-communicating objects are kept as close to each other as possible and the most 'active' objects are hosted on nodes with the highest processing capacity and/or the highest amount of memory available. DOORS aims for architectural simplicity and achieves this by providing more control to the solution implementer, such that the behaviour of the object balancer can be tailored to the specifics of the problem addressed by the implementation. The proposed design for the balancer provides a simple relocation service, and a set of perpetually updated set of metrics, such that the solution implementer may define, 'plug in' and enforce a balancing policy out of an unlimited number of alternatives. © 2021 IEEE.

关键词： Balancing

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Determining on-shelf availability based on RGB and ToF depth cameras 23

Determining on-shelf availability based on RGB and ToF depth...

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Craciunescu, Mihai Baicu, Diana Mocanu, Stefan Dobre, Cristian Faculty of Automatic Control and Computer Science Department of Automatic Control and Applied Informatics Bucharest Romania Rinftech Bucharest Romania

ISBN: (纸本)9781665439398

In this paper, a method of calculating the occupancy of a shelf will be presented. A vision pillar composed of two RGB cameras and two ToF depth cameras will be used to scan a shelf and determine the percentage of emptiness for the products. Since the cameras will scan a small section of the shelf at the time, a stitching method will be applied on both depth and RGB stream. In order to identify categories of products, along with their spatial delimitation within a shelf, a segmentation neural network is used. By combining the segmentation output with the depth information, the distance from the pillar to the product can be determined. Since this type of information does not help a human operator or a supervisor in understanding the state of the shelf or in making an appropriate decision, such as restocking, a method for computing the shelf occupancy is proposed. Optimization must be done to the processing algorithms to enable them to run on an embedded platform, which will allow for the implementation of the proposed architecture on a platform deployed in a production environment. All the computation is done on board of the mobile robot without transmitting the data to an external server. © 2021 IEEE.

关键词： Cameras

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A Framework for Analyzing GPU-Executed Malware 23

A Framework for Analyzing GPU-Executed Malware

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Apostol, Teodor-Petrut Velea, Radu Deaconescu, Razvan University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science and Engineering Department Romania

ISBN: (纸本)9781665439398

Graphics processing units (GPU) are an integral part of today's computing environment. The marketing emphasis on user experience pushes vendors to constantly look for better graphics hardware and newer drivers to integrate into their products. Most commodity GPUs function as accelerators for image and video processing tasks and are present (either as dedicated or integrated form factor) in everyday devices including desktops, laptops, smartphones or other portable gadgets. Recent trends have seen the GPU move to perform additional tasks such as offloading some of the computation from the CPU or solve highly parallel problems. As GPUs become more powerful and widespread they will naturally become a very attractive target for attackers. Cybercriminals will look for any vulnerability in the GPU hardware or software, and will try to use it as an attack vector to compromise the system. This paper presents some of the incidents that involve the use of GPUs to perform malicious actions and proposes a framework to allow analysts to inspect the code executed on the GPU and trigger security alerts. The proposed solution will look at the processes running inside an operating system, it will identify which of them require access to the GPU and will try to intercept and scan for any suspicious activities, similar to a conventional security solution. © 2021 IEEE.

关键词： Graphics processing unit

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Development of Novel 3D Face Masks for Assessment of Face Recognition systems 23

Development of Novel 3D Face Masks for Assessment of Face Re...

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23rd international conference of the Biometrics Special Interest Group, BIOSIG 2024

作者： Igene, Lambert Hossain, Afzal Plesh, Richard Purnapatra, Sandip Singh, Surendra Imtiaz, Masudul Schuckers, Stephanie Clarkson University Department of Electrical and Computer Engineering PotsdamNY United States

ISBN: (纸本)9798350373714

Face recognition is integral to identity management and access control systems, but the rise of biometric face recognition has raised concerns about the vulnerability of Presentation Attack Detection (PAD) to various attacks. This paper focuses on developing and evaluating novel, low-cost 3D presentation attack instruments (PAIs) to test the performance of advanced biometric systems. Our PAIs include specialized bobbleheads, white resin 3D-printed masks, white filament 3D masks, masks with image projections, and projections on generic mannequin heads. This project aims to create a diverse, cost-effective PAI dataset to enhance PAD training. We evaluated the effectiveness of these 3D PAIs using three algorithms (Fraunhofer IGD, CLFM, and FaceMe) from the Liveness Detection Face Competition 2021 (LivDet Face, 2021). Additionally, we conducted a comparison between PAIs and bona fide samples using the ArcFace face comparator, achieving an Imposter Attack Presentation Match Rate (IAPAR) of 70% for bobbleheads and 43% for white resin with projection. Our preliminary assessment indicates an Average Classification Error Rate (ACER) of 10.6%, demonstrating the potential of these new PAIs to improve PAD training. © 2024 IEEE.

关键词： Comparators (optical)

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