A Fresh Look at Google Analytics

A mobile peer-to-peer computer network is the one in which each computer in the network can act as a client or server for the other computers in the network. The communication process among the nodes in the mobile peer to peer network requires more no of messages. Due to this large number of messages passing, propose an interconnection structure called distributed Spanning Tree (DST) and it improves the efficiency of the mobile peer to peer network. The proposed method improves the data availability and consistency across the entire network and also reduces the data latency and the required number of message passes for any specific application in the network. Further to enhance the effectiveness of the proposed system, the DST network is optimized with the Ant Colony Optimization method. It gives the optimal solution of the DST method and increased availability, enhanced consistency and scalability of the network. The simulation results shows that reduces the number of message sent for any specific application and average delay and increases the packet delivery ratio in the network.

ANALYSE THE PERFORMANCE OF MOBILE PEER TO PEER NETWORK USING ANT COLONY OPTIM...

Introducing OfficeBox (Oct.2013)

Office box user_guide_v3.0

A La Mierda Todo,Yo Voy A Dormir

34번 서누리 예방논문1 발표

Benedict Choi

Ingles jess

La Terra nell'Universo

Affascinante

Nodes are easily exposed from generated attacks on various layers because they compose simple functions in sensor networks. The false data injection attack drains finite energy resource in a compromised node,and the false HELLO flood attack threatens constructed routing paths in an adversary node. A localized encryption and authentication protocol (LEAP) was developed to prevent the aforementioned attacks through the use of four keys. However, when these attacks occur simultaneously, LEAP may not prevent damage from spreading rapidly throughout the network. In this paper, we propose a method that addresses these attacks through the use of four types of keys, including two new keys. We also improve energy consumption while maintaining a suitable security level. The effectiveness of the proposed method was evaluated relative to that of LEAP when multiple attacks occur. The experimental results reveal that the proposed method enhances energy saving by up to 12% while maintaining sufficient detection power

AN ENERGY EFFICIENT COUNTERMEASURE AGAINST MULTIPLE ATTACKS OF THE FALSE DATA...

Introducing ViewToo v.2.0

Clustering is an important data mining technique where we will be interested in maximizing intracluster distance and also minimizing intercluster distance. We have utilized clustering techniques for detecting deviation in product sales and also to identify and compare sales over a particular period of time. Cl ustering is suited to group items that seem to fall naturally together, when there is no specified class for any new item . We have utilizedannual sales data of a steel major to analyze Sales V olume & Value with respect to dependent attributes like products , customers and quantities sold. The demand for steel products is cyclical and depends on many factors like customer profile, price ,Discounts and tax issues. In this paper, we have analyzed sales data with clustering algorithms like K - Means & EMwhich revealed many interesting patterns useful for improving sales revenue and achieving higher sales volume . Our study confirms that partition methods like K - Means & EM algorithms are better suited to analyze our sales data in comparison to D ensity based methods like DBSCAN & OPTICS or H ierarchical methods like COBWEB

Performance evaluation of clustering algorithms

Office box user guide_v3.0

Questione di prospettiva

Introducing view too v.2.1

Face recognition is one of the most challenging problems in the domain of image processing and machine vision. Face recognition system is critical when individuals have very similar biometric signature such as identical twins. In this paper, new efficient facial-based identical twins recognition is proposed according to the geometric moment. The utilized geometric moment is Pseudo-Zernike Moment (PZM) as a feature extractor inside the facial area of identical twins images. Also, the facial area inside an image is detected using Ada Boost approach. The proposed method is evaluated on two datasets, Twins Days Festival and Iranian Twin Society which contain scaled, which contain the shifted and rotated facial images of identical twins in different illuminations. The results prove the ability of proposed method to recognize a pair of identical twins. Also, results show that the proposed method is robust to rotation, scaling and changing illumination.

Ibrahim Idrissi

FaceBook Advertising Tactics

Hisham Nabawi

An efficient feature extraction method with pseudo zernike moment for facial ...

You have a great mobile recruiting strategy. But are you using one of the most powerful social networks available today? Google Plus can provide a powerful boost to your mobile recruiting efforts as long as you know how to make the best use of the platform. In this presentation, I provide an overview of Google Plus, the personal Google Plus profile, Google Plus Communities and Hangouts on Air. The presentation concludes with three key tactics you can begin using today to improve your use of Google Plus in your mobile recruiting strategy. This presentation was delivered at the 2013 Mobile Recruiting Conference in Atlanta, GA on September 24, 2013 (www.mrec.net).

Google Plus and Your Mobile Recruiting Strategy

Jon Parks

The large a v ailable am ou n t of non - structured texts that b e - long to differe n t domains su c h as healthcare (e.g. medical records), justice (e.g. l a ws, declarations), insurance (e.g. declarations), etc. increases the effort required for the analysis of information in a decision making pro - cess. Differe n t pr o jects and t o ols h av e pro p osed strategies to reduce this complexi t y b y classifying, summarizing or annotating the texts. P artic - ularl y , text summary strategies h av e pr ov en to b e v ery useful to pr o vide a compact view of an original text. H ow e v er, the a v ailable strategies to generate these summaries do not fit v ery w ell within the domains that require ta k e i n to consideration the tem p oral dimension of the text (e.g. a rece n t piece of text in a medical record is more im p orta n t than a pre - vious one) and the profile of the p erson who requires the summary (e.g the medical s p ecialization). T o co p e with these limitations this pa p er prese n ts ”GRe A T” a m o del for automatic summary generation that re - lies on natural language pr o cessing and text mining te c hniques to extract the most rele v a n t information from narrati v e texts and disc o v er new in - formation from the detection of related information. GRe A T M o del w as impleme n ted on sof tw are to b e v alidated in a health institution where it has sh o wn to b e v ery useful to displ a y a preview of the information a b ou t medical health records and disc o v er new facts and h y p otheses within the information. Se v eral tests w ere executed su c h as F unctional - i t y , Usabili t y and P erformance regarding to the impleme n ted sof t w are. In addition, precision and recall measures w ere applied on the results ob - tained through the impleme n ted t o ol, as w ell as on the loss of information obtained b y pr o viding a text more shorter than the original

Great model a model for the automatic generation of semantic relations betwee...