How to write an effective e-mail copy

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Hisham Nabawi

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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...

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Machine learning for text classification is the underpinning of document cataloging , news filtering, document steering and exemplif ication . In text mining realm, effective feature selection is significant to make the learning task more accurate and competent. One of the traditional lazy text classifier k - Nearest Neighborhood ( k NN) has a major pitfall in calculating the similarity between all the objects in training and testing se t s, there by leads to exaggeration of both computational complexity of the algorithm and massive consumption of main memory . To diminish these shortcomings in viewpoint of a data - mining practitioner a n amalgamati ve technique is proposed in this paper using a novel restructured version of k NN called Augmented k NN (AkNN) and k - Medoids (kMdd) clustering. The proposed work comprises preprocesses on the initial training set by imposing attribute feature selection for reduc tion of high dimensionality, also it detects and excludes the high - fliers samples in t he initial training set and re structure s a constricted training set . The kMdd clustering algorithm generates the cluster centers (as interior objects) for each category and restructures the constricted training set with centroids . This technique is amalgamated with AkNN classifier that was prearranged with text mining similarity measure s. Eventually, s ignifican tweights and ranks were assigned to each object in the new training set based upon the ir accessory towards the object in testing set . Experiments conducted on Reuters - 21578 a UCI benchmark text mining data set , and comparisons with traditional k NN classifier designates the referred method yield spreeminentrecital in b oth clustering and classification

Novel text categorization by amalgamation of augmented k nearest neighbourhoo...

ijcsity

Personal branding is all the rage. But what does it really mean. And, more importantly, how can you get started? In this presentation I delivered during a lunch session at Atlantic BT, I provided an overview of the topic and explained what I see as the three critical components of a solid personal branding strategy. Atlantic BT conducts a weekly lunch and learn session for our team members on a variety of topics. The aim is to create a knowledgeable workforce that is up-to-date on the latest topics in our industry.

What is Personal Branding

Jon Parks

By the advances in the Evolution Algorithms (EAs) and the intelligent optimization metho ds we witness the big revolutions in solving the optimization problems. The application of the evolution algorithms are not only not limited to the combined optimization problems, but also are vast in domain to the continuous optimization problems. In this paper we analyze and study the Genetic Algorithm (GA) and the Artificial Immune System (AIS) algorithm which are capable in escaping the local optimization and also fastening reaching the global optimization and to show the efficiency of the GA and AIS th e application of them in Solving Continuous Optimization Functions (SCOFs) are studied. Because of the multi variables and the multi - dimensional spaces in SCOFs the use of the classic optimization methods, is generally non - efficient and high cost. In other words the use of the classic optimization methods for SCOFs generally leads to a local optimized solution. A possible solution for SCOFs is to use the EAs which are high in probability of succeeding reaching the local optimized solution. The results in pa per show that GA is more efficient than AIS in reaching the optimized solution in SCOFs.

Convergence tendency of genetic algorithms and artificial immune system in so...

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The countdown to the end of third-party cookies has begun in Google Chrome, and the impact will be big for those reliant on them for data collection. Are you ready? Check out the experts from CallRail and Workshop Digital as we dive into the impending changes driven by Google Chrome's upcoming phase-out, and how you can navigate the challenges of a post-third-party cookie world. You’ll learn: - What the death of third-party cookies means for your current marketing strategies. - What marketers should be doing to prepare for these changes. - Strategies for success and the importance of utilizing marketing tools with zero- or first-party cookie collection. Watch Ryan Johnson and Andrew Miller as they explore the differences between third- and first-party cookies, analyze the profound implications of this transition for marketers, and introduce innovative solutions and strategies for what you should do next. If you’re reliant on third-party data and want to unlock the secrets to navigating a world without third-party cookies, then this webinar is for you. Stay ahead of the game with the best marketing tools and ensure your tactics are primed for success in this new era of digital marketing.

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