scholarly journals An Efficient Indexing Scheme for Network Traffic Collection and Retrieval System

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 191
Author(s):  
Chao Jiang ◽  
Jinlin Wang ◽  
Yang Li
Keyword(s):  
Network Traffic ◽  
Retrieval System ◽  
Compression Method ◽  
Construction Time ◽  
Vast Number ◽  
Indexing Scheme ◽  
Comparison Results ◽  
Speed Up ◽  
Traffic Collection ◽  
Storage Format

Historical network traffic retrieval, both at the packet and flow level, has been applied in many fields of network security, such as network traffic analysis and network forensics. To retrieve specific packets from a vast number of packet traces, it is an effective solution to build indexes for the query attributes. However, it brings challenges of storage consumption and construction time overhead for packet indexing. To address these challenges, we propose an efficient indexing scheme called IndexWM based on the wavelet matrix data structure for packet indexing. Moreover, we design a packet storage format based on the PcapNG format for our network traffic collection and retrieval system, which can speed up the extraction of index data from packet traces. Offline experiments on randomly generated network traffic and actual network traffic are performed to evaluate the performance of the proposed indexing scheme. We choose an open-source and widely used bitmap indexing scheme, FastBit, for comparison. Apart from the native bitmap compression method Word-Aligned Hybrid (WAH), we implement an efficient bitmap compression method Scope-Extended COMPAX (SECOMPAX) in FastBit for performance evaluation. The comparison results show that our scheme outperforms the selected bitmap indexing schemes in terms of time consumption, storage consumption and retrieval efficiency.

scholarly journals Agriculture Model Comparison Framework and MyGeoHub Hosting: Case of Soil Nitrogen

Inventions ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 25
Author(s):  
Anupam Bhar ◽  
Benjamin Feddersen ◽  
Robert Malone ◽  
Ratnesh Kumar
Keyword(s):  
Soil Nitrogen ◽  
Field Data ◽  
Model Comparison ◽  
Test Model ◽  
Soil N ◽  
N Dynamics ◽  
Benchmark Model ◽  
C Dynamics ◽  
Comparison Results ◽  
Speed Up

To be able to compare many agricultural models, a general framework for model comparison when field data may limit direct comparison of models is proposed, developed, and also demonstrated. The framework first calibrates the benchmark model against the field data, and next it calibrates the test model against the data generated by the calibrated benchmark model. The framework is validated for the modeling of the soil nutrient nitrogen (N), a critical component in the overall agriculture system modeling effort. The nitrogen dynamics and related carbon (C) dynamics, as captured in advanced agricultural modeling such as RZWQM, are highly complex, involving numerous states (pools) and parameters. Calibrating many parameters requires more time and data to avoid underfitting. The execution time of a complex model is higher as well. A study of tradeoff among modeling complexities vs. speed-up, and the corresponding impact on modeling accuracy, is desirable. This paper surveys soil nitrogen models and lists those by their complexity in terms of the number of parameters, and C-N pools. This paper also examines a lean soil N and C dynamics model and compares it with an advanced model, RZWQM. Since nitrate and ammonia are not directly measured in this study, we first calibrate RZWQM using the available data from an experimental field in Greeley, CO, and next use the daily nitrate and ammonia data generated from RZWQM as ground truth, against which the lean model’s N dynamics parameters are calibrated. In both cases, the crop growth was removed to zero out the plant uptake, to compare only the soil N-dynamics. The comparison results showed good accuracy with a coefficient of determination (R2) match of 0.99 and 0.62 for nitrate and ammonia, respectively, while affording significant speed-up in simulation time. The lean model is also hosted in MyGeoHub cyberinfrastructure for universal online access.

scholarly journals Speed and Sustainability When Entering New Market

2021 ◽  
Vol 13 (22) ◽  
pp. 12458
Author(s):  
Gwang Seok Kim ◽  
Young Hoon Lee
Keyword(s):  
Life Cycle ◽  
Entry Mode ◽  
The Other ◽  
Environmental Damage ◽  
Optimal Size ◽  
Construction Time ◽  
Business Excellence ◽  
Speed Up ◽  
Mature Market ◽  
Job Prospects

When constructing a factory to enter new markets, the optimal size to respond to demand is determined by the construction time. Hyundai Motor Company (Hyundai), on the other hand, standardizes the size of its factories to speed up the entry and response to demand. The Hyundai’s entry mode, called SPEED, is modeled as a strategy. The strategy is evaluated of excellence with capacity expansion rules formalized, key parameters identified, and mathematical programming. The SPEED strategy is suited for market followers who want to enter a midscale or mature market in terms of business excellence and more sustainable throughout the factory’s life cycle on the side of sustainability. Shorter construction times, as a result of the SPEED strategy, can help to prevent environmental damage while also standardization can increase job prospects for local workers.

scholarly journals Effect of Sodium Starch Glycolate on Formulation of Fexofenadine Hydrochloride Immediate Release Tablets by Direct Compression Method

2018 ◽  
Vol 10 (1) ◽  
pp. 31-38 ◽  
Author(s):  
S. Karim ◽  
A. Biswas ◽  
A. Bosu ◽  
F. R. Laboni ◽  
A. S. Julie ◽  
...  
Keyword(s):  
Immediate Release ◽  
Direct Compression ◽  
Compression Method ◽  
Release Formulation ◽  
The Core ◽  
Sodium Starch Glycolate ◽  
Zero Order Kinetics ◽  
Speed Up ◽  
Usp Apparatus ◽  
Paddle Apparatus

Present study aspires at the design of an immediate release formulation with prospective use of fexofenadine hydrochloride by exploring the effect of sodium starch glycolate as super disintegrant. Fexofenadine hydrochloride immediate release tablets (Formulations F-1, F-2, F-3, F-4 and F-5) using different ratios of sodium starch glycolate as a disintegrant were prepared by direct compression method. Standard physicochemical tests were performed for all the formulations. Dissolution studies of the formulations were done in phosphate buffer, pH 6.8 using USP apparatus II (paddle apparatus) at 50 rpm. Percent release of fexofenadine hydrochloride of formulations F-1, F-2, F-3, F-4 and F-5 were 89.98%, 90.98%, 92.95, 96.92% and 99.85%, respectively after 1 h and the release pattern followed the zero order kinetics. The release rate in the formulation F-5 was higher compared to other formulations and the studied market products. Sodium starch glycolate speed up the release of the drug from the core tablets, and the release of fexofenadine hydrochloride from tablets was directly proportional to the amount of sodium starch glycolate present in the formulations and there by produced immediate action.

scholarly journals A REVIEW ON MULTIQUERY SYSTEM FOR CONTENT BASED IMAGE RETRIEVAL

2016 ◽  
Vol 15 (13) ◽  
pp. 7342-7346
Author(s):  
Meenu Meenu ◽  
Sonika Jindal
Keyword(s):  
Image Retrieval ◽  
Visual Information ◽  
Retrieval System ◽  
Image Similarity ◽  
Content Based Image Retrieval ◽  
Color Similarity ◽  
Image Retrieval System ◽  
Speed Up ◽  
Similarity Computation ◽  
Main Components

In recent years, very large collections of images and videos have grown rapidly. In parallel with this growth, content-based retrieval and querying the indexed collections are required to access visual information. Two of the main components of the visual information are texture and color. In this thesis, a content-based image retrieval system is presented that computes texture and color similarity among images. Content based image retrieval from large resources has become an area of wide interest now a days in many applications.  To speed up retrieval and similarity computation, the database images are analysed and the extracted regions are clustered according to their feature vectors. This process is performed offline before query processing, therefore to answer a query our system does not need to search the entire database images; instead just a number of candidate images are required to be searched for image similarity.

scholarly journals Prediction of Protein-Protein Interactions Based On Weighted Extreme Learning Machine And Speed Up Robot Features

2021 ◽  
Author(s):  
JinXuan Zhai ◽  
Ji-Yong An
Keyword(s):  
Extreme Learning Machine ◽  
Protein Interactions ◽  
Evolutionary Information ◽  
Protein Protein Interactions ◽  
Prediction Ability ◽  
Great Ability ◽  
Weighted Extreme Learning Machine ◽  
Comparison Results ◽  
Speed Up ◽  
Learning Machine

Abstract Background：Protein–protein interactions (PPIs) are involved in a number of cellular processes and play a key role inside cells. The prediction of PPIs is an important task towards the understanding of many bioinformatics functions and applications, such as predicting protein functions, gene-disease associations and disease-drug associations. Given that high-throughput methods are expensive and time-consuming, it is a challenging task to develop efficient and accurate computational methods for predicting PPIs .Results：In the study, a novel computational approach named WELM-SURF was developed to predict PPIs. The proposed method used Position Specific Scoring Matrix (PSSM) to capture protein evolutionary information and employed Speed Up Robot Features (SURF) to extract key features from PSSM of protein sequence. Weighted Extreme Learning Machine (WELM) is featured with short training time and great ability to execute classification efficiently by optimizing the loss function of weight matrix. Therefore, WELM classifier was used to carry out classification. The cross-validation results show that WELM-SURF obtains 97.36% and 95.12% of average accuracy on yeast and human dataset, respectively. The prediction ability of WELM-SURF was also compared with those of ELM-SRUF, SVM-SURF and other existing approaches. The comparison results further verify that WELM-SURF is obviously better than other methods.Conclusion：The experimental results proved that the WELM-SURF method is very useful for predicting PPIs and can also be applied to other bioinformatics studies of protein.

scholarly journals Model and Algorithms for User Identification by Network Traffic

2021 ◽  
Author(s):  
Vasily Gai ◽  
Irina Ephode ◽  
Roman Barinov ◽  
Igor Polyakov ◽  
Vladimir Golubenko ◽  
...  
Keyword(s):  
Machine Learning ◽  
Network Traffic ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Feature Descriptor ◽  
User Identification ◽  
Redundant Data ◽  
Boosting Method ◽  
Object Feature ◽  
Traffic Collection

This paper proposes a method of user identification by network traffic. We describe the information model created, as well as the implementation of each of the proposed problem solving stages. During the network traffic collection stage, a method of capturing network packets on the user's device using specialized software is used. The information obtained is further filtered by removing redundant data. During the object feature descriptor construction stage, we extract and describe the characteristics of network sessions from which the behavioral habits of users are derived. Classification of users according to the extracted characteristics of the network sessions is performed using machine learning techniques. When analyzing the test results, the most appropriate machine learning algorithms for solving the problem of user identification by network traffic were proposed, such as: logistic regression, decision trees, SVM with a linear hyperplane and the boosting method. The accuracy of the above methods was more than 95%. The results proved that it is possible to identify a particular user with a sufficiently high accuracy based on the characteristics of the data transmitted through the network, without examining the contents of the transmitted packets. Comparison of the developed model has shown that the proposed model of user identification by network traffic works as effectively as the existing analogues.

scholarly journals A NOVEL FAST FRACTAL IMAGE COMPRESSION METHOD BASED ON DISTANCE CLUSTERING IN HIGH DIMENSIONAL SPHERE SURFACE

Fractals ◽  
2017 ◽  
Vol 25 (04) ◽  
pp. 1740004 ◽  
Author(s):  
SHUAI LIU ◽  
ZHENG PAN ◽  
XIAOCHUN CHENG
Keyword(s):  
Image Compression ◽  
High Dimensional ◽  
Dimensional Sphere ◽  
Compression Method ◽  
Sphere Surface ◽  
Fractal Image Compression ◽  
Fractal Compression ◽  
Fractal Image ◽  
Speed Up ◽  
Encoding Method

Fractal encoding method becomes an effective image compression method because of its high compression ratio and short decompressing time. But one problem of known fractal compression method is its high computational complexity and consequent long compressing time. To address this issue, in this paper, distance clustering in high dimensional sphere surface is applied to speed up the fractal compression method. Firstly, as a preprocessing strategy, an image is divided into blocks, which are mapped on high dimensional sphere surface. Secondly, a novel image matching method is presented based on distance clustering on high dimensional sphere surface. Then, the correctness and effectiveness properties of the mentioned method are analyzed. Finally, experimental results validate the positive performance gain of the method.

scholarly journals Overview of the ways to reduce telemetric information redundancy

2019 ◽  
Vol 29 (2) ◽  
pp. 8-16
Author(s):  
F. N. Baibekova ◽  
V. V. Podoltsev ◽  
N. M. Bespalova ◽  
L. A. Sologubova
Keyword(s):  
High Speed ◽  
Compression Method ◽  
Information Redundancy ◽  
Real Time Processing ◽  
Advantages And Disadvantages ◽  
Redundancy Reduction ◽  
Speed Up ◽  
Huffman Algorithm ◽  
Multi Level ◽  
Target Data

The redundancy of telemetric information significantly complicates the real-time processing of the information flows. To speed up the telemetry processing process, the methods for telemetric information redundancy reduction should be applied in order to reduce its flows entering the monitoring systems while maintaining a high speed of processing and reliability of the information. The article provides an overview of the methods for reduction of telemetric information redundancy, such as the increase in PHY-rate of telemetry channel, the Huffman algorithm, the batch mechanism for generation and transmission of telemetry information, the adaptive difference algorithm, the algorithm for transmission of the information based on its representation by residual images, Golomb-Rice codes, reversible compression method. The advantages and disadvantages of each of them are considered. Recommendations on the use of multi-level telemetry information compression system are given, which makes it possible to effectively combine target data compression algorithms that give the highest compression ratio depending on the type of telemetry information transmitted.

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