scholarly journals AN IMPLEMENTATION OF IDS IN A HYBRID APPROACH AND KDD CUP DATASET

2014 ◽  
Vol 2 (3) ◽  
pp. 1-9
Author(s):  
Mala Bharti Lodhi ◽  
Vineet Richhariya ◽  
Mahesh Parmar
Keyword(s):  
Data Mining ◽  
Clustering Algorithm ◽  
Hybrid Approach ◽  
The Other ◽  
Data Mining Algorithm ◽  
Traffic Pattern ◽  
Detection Techniques ◽  
Network Intrusion ◽  
Other Hand ◽  
And Performance

Now in these days due to rapidly increasing network applications the data and privacy security in network is a key challenge. In order to provide effective and trustable security for network, intrusion detection systems are helpful. The presented study is based on the IDS system design for network based anomaly detection. Thus this system requires an efficient and appropriate classifier by which the detection rate of intrusions using KDD CPU dataset can be improved. Due to study there is various kind of data mining based, classification and pattern detection techniques are available. These techniques are promising for detecting network traffic pattern more accurately. On the other hand recently developed the hybrid models are providing more accurate classification. Thus a hybrid intrusion system is presented in this proposed work. That provides a significant solution even when the overall learning patterns are not available in database. Therefore, three different data mining algorithm is employed with system. Proposed system consists of K-mean clustering algorithm for finding the relationship among data in order to filter data instances. The implementation of the proposed classification system is performed using MATLAB environment and performance of designed classifier is evaluated. The obtained results from the simulation demonstrate after filtering steps. On the other hand the classification accuracy is adoptable with low number of training cycles with less time and space complexity.

Cognitive Reflection Task and Stumpers

2021 ◽  
Author(s):  
Wendy Ross ◽  
Frédéric Vallée-Tourangeau
Keyword(s):  
Cognitive Processes ◽  
Mental Model ◽  
The Other ◽  
Cognitive Reflection ◽  
Other Hand ◽  
And Performance ◽  
Shed Light

There is a type of riddle that Bar-Hillel, Noah and Frederick (2018) call “stumpers”. A stumper is a riddle which is initially intractable because the mental model or representation of the situation described in the riddle does not contain the vital information which is required to solve it. The Cognitive Reflection Task (CRT; Frederick, 2005) on the other hand relies on seemingly completely different cognitive processes. However, exploratory work from Bar-Hillel et al. (2019) suggests that success on stumpers correlates with performance on the CRT. This finding may shed light on the cognitive processes underlying both the resolution of stumpers and the CRT. We replicated the work from Bar-Hillel et al. (2019) suggesting a relationship between performance on the CRT and performance on stumpers as well as extending this to show a relationship between performance on the CRT-v. This may point to the underexplored importance of suppression in solving stumpers and traditional riddles.

scholarly journals Logical Circuits for Extended Content Matching in Hardware Based NIDPS

2013 ◽  
Vol 7 (3) ◽  
pp. 664-669
Author(s):  
Dejan Georgiev ◽  
Aristotel Tentov
Keyword(s):  
Intrusion Detection ◽  
The Other ◽  
Network Intrusion Detection ◽  
Network Intrusion ◽  
Other Hand ◽  
Efficient Detection ◽  
Network Speed ◽  
Intrusion Detection And Prevention

In this paper we present logical circuits for efficient detection of rolled out contents. As network speed increases and security matters  there is a demand for implementation of hardware based Network Intrusion Detection and Prevention Systems (NIDPS). On the other hand hardware based NIDPS are lacking the flexibility of detection of so named "evasion" techniques. Here we present simple but efficient enhancement to content matching in hardware with minimal basic memory elements (flip-flops) used.

scholarly journals Power Relation In Memoirs Of Geisha And The Dancer

2014 ◽  
Vol 7 (2) ◽  
pp. 151
Author(s):  
Mundi Rahayu ◽  
Lia Emelda ◽  
Siti Aisyah
Keyword(s):  
Symbolic Capital ◽  
Power Relation ◽  
Economic Capital ◽  
The Other ◽  
Female Character ◽  
Other Hand ◽  
Close Interaction ◽  
And Performance

This article aims at comparing the ideas of power relation between themain female character and ―Mother‖ in Arthur Golden‘s Memoirs ofGeisha and Ahmad Tohari‘s The Dancer. These two novels share thesame main female character of traditional entertainers, as a Japanese geisha and a Javanese traditional dancer, respectively. As an entertainer in the traditional sphere, they are bounded with the other women and build close interaction as well as power relation with them who are called ―Mother‖ in the Geisha and ―ronggeng shaman‖ in The Dancer. Thepower relation between them are unique and dynamics. This is analyzed through Foucault‘s theory of power. The result of the analysis shows that the power relation is not stable, and the power practiced by each of them is influenced by the symbolic capital and economic capital they have. The negotiation and contestation come up between the actors in dailypractices as geisha and the mother, as the ―ronggeng‖ and the shaman. As the entertainers, the geisha and ―ronggeng‖ build and shape their body and performance to attract men. This geisha and ronggeng culture reproduce many other cultural product such as ―mizuage‖ in geisha, and ―bukak klambu‖ in ―ronggeng‖ both of which refer to the same thing, selling the woman‘s virginity to the highest bidder. In geisha it is used to benefit the Mother of Okiya and no rebellion of the geisha. On the other hand, Srintil does rebellious action in this ―bukak klambu‖ occasion. There seems to be different message from these two novels, The Dancer is much more questioning the norms covering the ―ronggeng‖ tradition while the Memoirs of Geisha tends to be accepting the geisha tradition as what it is.Keywords: Power Relation; Geisha ; Ronggeng ; Norms

Patronage and Performance: Factors in the Political Mobility of Provincial Leaders in Post-Deng China

2012 ◽  
Vol 212 ◽  
pp. 965-981 ◽  
Author(s):  
Eun Kyong Choi
Keyword(s):  
Economic Performance ◽  
Career Mobility ◽  
The Other ◽  
The Political ◽  
Performance Factors ◽  
Other Hand ◽  
And Performance ◽  
The Impact

AbstractThis paper attempts to estimate the impact of both factional ties and economic performance on the promotion of provincial Party secretaries and governors by analysing a person–year dataset of their career mobility for inclusive years 1989 to 2009. We found that for provincial Party secretaries whose promotion meant rising to a top national position, both factional ties and good economic performance increased their chance for promotion. On the other hand, for provincial governors whose promotion meant rising to a ministry-level position, only economic performance mattered for their promotion. Among provincial Party secretaries, the extent to which performance affected the likelihood of promotion was not different between factional members and non-members. This suggests that even factional members needed to show good performance to enhance the likelihood of their promotion.

Analytical Condition Inspection and Extension of Time Between Overhaul of F3-30 Engine

1991 ◽  
Author(s):  
Masato Nakao ◽  
Masataka Ikeyama ◽  
Shinji Abe
Keyword(s):  
The Other ◽  
Turbofan Engine ◽  
Field Service ◽  
Deterioration Rate ◽  
Self Defense ◽  
Other Hand ◽  
Field Operation ◽  
Actual Field ◽  
And Performance ◽  
Bypass Ratio

F3-30 is the low-bypass-ratio turbofan engine developed to power the T-4 intermediate trainer for the Japan Air Self Defense Force (JASDF). The actual field service was started in September, 1988. The program to extend time between overhaul (TBO) of the F3-30 has been running. Analytical condition inspection (ACI) and accelerated mission testing (AMT) were conducted to confirm the sufficient durability to extend TBO. Most deteriorations of parts and performance due to AMT were also found by ACI after field operation with approximately same deterioration rate. On the other hand, some deteriorations were found by ACI only. These results show that ACI after field operation is also necessary to confirm the TBO extension, though AMT simulates the deterioration in the field operation very well. The deteriorations which would be caused by the field operation during one extended-TBO were estimated with the results of ACI and AMT, and it was concluded that the F3-30 has the sufficient durability for TBO extension to the next step.

The Effect of Knowledge of Results on Learning and Performance IV. The Direction of the Error in Very Simple Skills

1951 ◽  
Vol 3 (1) ◽  
pp. 36-42 ◽  
Author(s):  
Valerie Dees ◽  
G. C. Grindley
Keyword(s):  
Short Interval ◽  
The Other ◽  
Time Interval ◽  
Knowledge Of Results ◽  
Short Intervals ◽  
Visual Knowledge ◽  
Other Hand ◽  
The Subject ◽  
And Performance ◽  
Learning And Performance

Re-examination of the data discussed in previous papers of this series shows a greater tendency toward “overshooting” when the time interval between trials, in some of the experiments, is short than when it is longer. The subject tends to make a bigger movement or exert more pressure with short intervals. This seems to be true with or without visual knowledge of results. On the other hand, with the experiments in which the task was to press a key for a given short interval, the effect was not conclusively shown. A hypothesis is put forward to explain these results in terms of proprioceptive adaptation.

Data Mining Clustering Algorithm Research and Application

2014 ◽  
Vol 926-930 ◽  
pp. 3608-3611 ◽  
Author(s):  
Yi Fan Zhang ◽  
Yong Tao Qian ◽  
Tai Yu Liu ◽  
Shu Yan Wu
Keyword(s):  
Data Mining ◽  
Cluster Analysis ◽  
Clustering Analysis ◽  
Clustering Algorithm ◽  
Dimensional Space ◽  
Data Mining Algorithm ◽  
Practical Application ◽  
Advantages And Disadvantages ◽  
Analysis Theory ◽  
Data Points

In this paper, first introduce data mining knowledge then focuses on the clustering analysis algorithms, including classification clustering algorithm, and each classification typical cluster analysis algorithms, including the formal description of each algorithm as well as the advantages and disadvantages of each algorithm also has a more detailed description. Then carefully introduce data mining algorithm on the basis of cluster analysis. And using cohesion based clustering algorithm with DBSCAN algorithm and clustering in consumer spending in two-dimensional space, 2,000 data points for each area, and get a reasonable clustering results, resulting in hierarchical clustering results valuable information, so as to realize the practical application of the algorithm and clustering analysis theory combined.

scholarly journals A Two-level Calculus for Composing Hybrid QVT Transformations

2010 ◽  
Vol 13 (1) ◽  
Author(s):  
Claudia Pons ◽  
Roxana Giandini ◽  
Gabriela Pérez ◽  
Gabriel Baum
Keyword(s):  
Hybrid Approach ◽  
Software Tool ◽  
The Other ◽  
Model Transformations ◽  
Other Hand ◽  
Transformation Approach ◽  
Compositional Approaches ◽  
Composition Technique

The standard for model transformations QVT offers two dialects: Relations Language andOperational Mappings Language. Each one of these dialects can be used in isolation, resulting inpurely declarative transformations or purely imperative transformation respectively; alternatively, bothdialects can be combined resulting in a hybrid transformation approach. On the other hand, theavailability of compositional approaches to produce complex transformations from smaller units is amajor concern in the area of model transformations. Compositional approaches for pure QVTtransformations are supported by a number of tools; however no composition technique exists that canconsistently manage the hybrid approach. Such partial techniques provide suitable answers to mostpractical needs; but they do not cover the entire composition spectrum. The aim of this article is todescribe a technique for composing model transformations embracing both dimensions - declarativeand imperative - so that the hybrid approach can be smoothly supported. Additionally, we report theimplementation of a software tool supporting such technique and we sketch its validation.

scholarly journals Dbscan Assisted by Hybrid Genetic K Means Algorithm

2020 ◽  
Vol 8 (6) ◽  
pp. 1973-1979
Keyword(s):  
Data Mining ◽  
Time Complexity ◽  
Clustering Algorithm ◽  
Hybrid Approach ◽  
Research Direction ◽  
Computational Time ◽  
Main Concern ◽  
Complex Data ◽  
Data Mining Algorithms ◽  
Mining Algorithms

The data mining algorithms functioning is main concern, when the data becomes to a greater extent. Clustering analysis is a active and dispute research direction in the region of data mining for complex data samples. DBSCAN is a density-based clustering algorithm with several advantages in numerous applications. However, DBSCAN has quadratic time complexity i.e. making it complicated for realistic applications particularly with huge complex data samples. Therefore, this paper recommended a hybrid approach to reduce the time complexity by exploring the core properties of the DBSCAN in the initial stage using genetic based K-means partition algorithm. The technological experiments showed that the proposed hybrid approach obtains competitive results when compared with the usual approach and drastically improves the computational time.

scholarly journals Effect of Academic Interest and Emotional Happiness on Academic Performance in Learning Environment.

2020 ◽  
Vol 9 (1) ◽  
pp. 2486-2489
Keyword(s):  
Data Mining ◽  
Academic Performance ◽  
Clustering Algorithm ◽  
Reference Model ◽  
Educational Data Mining ◽  
Positive Association ◽  
Academic Interest ◽  
Education Data ◽  
Learning Techniques ◽  
And Performance

According to Bloom's Taxonomy, the motto of education is to groom the students' as a better personality in knowledge, skill set and emotions under the supervision of academicians. Development of information technology paves the way to analyse the data from the educational environment and make decisions which help to be in track to achieve the motto. i.e. Educational Data mining. Education Data mining is one of the research domains of data mining which convert the data from the educational sector as insights for decision making. This paper is to analyse the effect of student's academic interest on emotional happiness and academic performance by applying supervised and unsupervised learning techniques. Students' Emotional Happiness and students' academic performance is evaluated by the Oxford Happiness Inventory and criterion reference model. Academic interest is received as yes or no responses from the students. Naive Bayes classification algorithm and K Means clustering algorithm is applied to categorise the student participants based on their happiness scale, academic interest and academic performance. The association between academic interest and performance is determined using predictive and descriptive mining. By this research, it is witnessed the positive association between academic interest, happiness and performance. The insights of this investigation will allow the teachers' to understand the students in a better way and do the needful to enhance academic efficiency.

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