FEATURES OF MOLECULAR ANALYSIS AS A REAL-TIME INTERNET SERVICE

2021 ◽  
Author(s):  
М.В. ЗАХАРОВ
Keyword(s):  
Traffic Flow ◽  
Simulation Modeling ◽  
General Purpose ◽  
Service Delivery Model ◽  
State University ◽  
Network Delay ◽  
Software Environment ◽  
Internet Service ◽  
Saint Petersburg ◽  
Proposed Model

Приведен обзор особенностей применения портативныхNIR спектрометров общего назначения, используемых для анализа состава продуктов питания и лекарственных средств. Представлена модель агрегированного потока сетевого трафика от нескольких спектрометров и модель предоставления услуги, обеспечивающая снижение сетевой задержки и объема передаваемых данных. Рассмотрен метод построения сети на основе граничных вычислений для снижения сетевой задержки. Для проверки предложенной модели и метода проведено имитационное моделирование в среде AnyLogic. The Bonch-Bruevich Saint-Petersburg State University of Telecommunications The article provides an overview of the features of the use of portable general-purpose NIR spectrometers to analyze the composition of food or medicines. A model of the aggregated network traffic flow of several spectrometers and a service delivery model, which provides the reduction of network delay and amount of transmitted data, are presented. A method of constructing a network based on edge computing for reduction of network delay is considered. To verify the proposed model and method simulation modeling was carried out in the software environment AnyLogic.

The All-Russian conference «Development of Geobotany: History and Present» (Saint Petersburg, 31 January—2 February 2011)

2011 ◽  
pp. 93-97
Author(s):  
O. I. Sumina
Keyword(s):  
Plant Ecology ◽  
State University ◽  
Saint Petersburg ◽  
Russian Conference

From 31 January to 2 February 2011 in St. Petersburg state University was held All-Russian conference "Development of geobotany: history and modernity" devoted to the 80 anniversary of the Department of geobotany and plant ecology of St. Petersburg state University and anniversaries of its teachers.

scholarly journals GAMPAL: an anomaly detection mechanism for Internet backbone traffic by flow size prediction with LSTM-RNN

2021 ◽  
Author(s):  
Taku Wakui ◽  
Takao Kondo ◽  
Fumio Teraoka
Keyword(s):  
Anomaly Detection ◽  
Short Term Memory ◽  
Denial Of Service ◽  
General Purpose ◽  
Traffic Information ◽  
Traffic Patterns ◽  
Detection Mechanism ◽  
Internet Service ◽  
Internet Backbone ◽  
Backbone Network

AbstractThis paper proposes a general-purpose anomaly detection mechanism for Internet backbone traffic named GAMPAL (General-purpose Anomaly detection Mechanism using Prefix Aggregate without Labeled data). GAMPAL does not require labeled data to achieve general-purpose anomaly detection. For scalability to the number of entries in the BGP RIB (Border Gateway Protocol Routing Information Base), GAMPAL introduces prefix aggregate. The BGP RIB entries are classified into prefix aggregates, each of which is identified with the first three AS (Autonomous System) numbers in the AS_PATH attribute. GAMPAL establishes a prediction model for traffic sizes based on past traffic sizes. It adopts a LSTM-RNN (Long Short-Term Memory Recurrent Neural Network) model that focuses on the periodicity of the Internet traffic patterns at a weekly scale. The validity of GAMPAL is evaluated using real traffic information, BGP RIBs exported from the WIDE backbone network (AS2500), a nationwide backbone network for research and educational organizations in Japan, and the dataset of an ISP (Internet Service Provider) in Spain. As a result, GAMPAL successfully detects anomalies such as increased traffic due to an event, DDoS (Distributed Denial of Service) attacks targeted at a stub organization, a connection failure, an SSH (Secure Shell) scan attack, and anomaly spam.

Investigation on Evaluation of Terminal Departure Capacity Based on Route Intersection

2013 ◽  
Vol 655-657 ◽  
pp. 2262-2265
Author(s):  
Jian Guo Kong
Keyword(s):  
Mathematical Model ◽  
Traffic Flow ◽  
Air Traffic ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Flight Data ◽  
Proposed Model ◽  
Combining Data ◽  
Traffic Flow Management ◽  
Airport Terminal

Air traffic flow management is the key to evaluate airspace capacity reasonably and accurately. Based on the flight features of terminal route intersection, this paper builds a mathematical model for scattered flight of departure aircraft, and then evaluates the terminal capacity based on this model. By combining data from Flight Data Recorder (FDR) and flight schedule with the model, an example-runway 02R of Guangzhou Baiyun airport terminal was given to show the effectiveness of the proposed model.

An extended optimal velocity difference model in a cooperative driving system

2015 ◽  
Vol 26 (05) ◽  
pp. 1550054
Author(s):  
Jinliang Cao ◽  
Zhongke Shi ◽  
Jie Zhou
Keyword(s):  
Traffic Flow ◽  
Linear Stability Theory ◽  
Difference Model ◽  
Optimal Velocity ◽  
Driving System ◽  
Cooperative Driving ◽  
Proposed Model ◽  
De Vries ◽  
The Stability ◽  
Theoretical Results

An extended optimal velocity (OV) difference model is proposed in a cooperative driving system by considering multiple OV differences. The stability condition of the proposed model is obtained by applying the linear stability theory. The results show that the increase in number of cars that precede and their OV differences lead to the more stable traffic flow. The Burgers, Korteweg–de Vries (KdV) and modified Korteweg–de Vries (mKdV) equations are derived to describe the density waves in the stable, metastable and unstable regions, respectively. To verify these theoretical results, the numerical simulation is carried out. The theoretical and numerical results show that the stabilization of traffic flow is enhanced by considering multiple OV differences. The traffic jams can be suppressed by taking more information of cars ahead.

scholarly journals Traffic flow features as metrics (TFFM): detection of application layer level DDOS attack scope of IOT traffic flows

2018 ◽  
Vol 7 (2.7) ◽  
pp. 203 ◽  
Author(s):  
Kalathiripi Rambabu ◽  
N Venkatram
Keyword(s):  
Traffic Flow ◽  
Traffic Flows ◽  
Application Layer ◽  
Continuous Growth ◽  
Loosely Coupled ◽  
Ddos Attack ◽  
Proposed Model ◽  
Flow Features ◽  
Target Network ◽  
Iot Devices

The phenomenal and continuous growth of diversified IOT (Internet of Things) dependent networks has open for security and connectivity challenges. This is due to the nature of IOT devices, loosely coupled behavior of internetworking, and heterogenic structure of the networks.  These factors are highly vulnerable to traffic flow based DDOS (distributed-denial of services) attacks. The botnets such as “mirae” noticed in recent past exploits the IoT devises and tune them to flood the traffic flow such that the target network exhaust to response to benevolent requests. Hence the contribution of this manuscript proposed a novel learning-based model that learns from the traffic flow features defined to distinguish the DDOS attack prone traffic flows and benevolent traffic flows. The performance analysis was done empirically by using the synthesized traffic flows that are high in volume and source of attacks. The values obtained for statistical metrics are evincing the significance and robustness of the proposed model

scholarly journals Eds. Lobanov, N. A., Mažeikienė, N., Skvortsov, V. N. 2013. Continuous education as a prerequisite of the development of professional competences

2014 ◽  
Vol 26 (31) ◽  
pp. 304-307
Author(s):  
Ewa Kula ◽  
Tomasz Maliszewski
Keyword(s):  
State University ◽  
Continuous Education ◽  
Saint Petersburg

Continuous education as a prerequisite of the development of professional competences. Monography. Eds. N. A. LOBANOV, N. MAŽEIKIENĖ, V. N. SKVORTSOV. Saint-Petersburg: Pushkin Leningrad State University, 2013. 280 pp. ISBN 978-5-8290-1275-5.

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