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Mardi Ne Ananda Parichina Vadina Puku, Ma Vadinanu Kasi Theera Denganu, Iddaru Marudula Muddula Vadina, Kaamaa Thuraanaam Na Bhayam Na Lajja, Vadina syam tho shobanam, Vadina Maridi dengudu boothu kathalu, vadina telugu kathalu vadina tho tholi anubhavam, maridi tho, vadina tho maridi telugu, maridi debba, maridi vadina, billanu pagala dengina maridi, vadina tho maridi, vadina tho maridi videos, maridi tho sarasam, vadina tho maridi kathalu. Types of brand names Despite the proliferation of number of brand names out there, they all fall into certain basic categories. You probably haven’t given them much thought (unless you’re in the naming business). But if you’re going to be naming something, it can be very helpful to identify—and employ—different naming constructions and strategies. Here’s a guide to them all. Descriptive Names These are names that clearly describe the goods or services being offered. (Think Toys R Us, PayPal, Architectural Digest, Best Buy, Monistat’s Soothing Care, and Schwab’s Real Life Retirement.) Descriptive names often work best when you want to: reinforce a strong master or parent brand rather than launch a new brand reach a B2B audience who just wants to know what the darn thing does name products with short lifecycles and low marketing budgets. On the other hand, purely descriptive names are difficult to trademark, because they use common, everyday language. So if having a legally protectable name is a big concern, a less descriptive name is probably a better bet for you. Suggestive Names Like descriptive names, suggestive names allude to the features and benefits of the goods and services being offered, only less directly. For instance, vSafe (Wells Fargo’s virtual safety deposit box), mPower (Cornerstone’s debit card), Quisitive (a trademark search service) and Target are all examples of suggestive names. Suggestive names are the middle ground in naming. They’re more evocative catchword and memorable than descriptive names, and more communicative than fanciful names (which we’ll get to in a moment). For these reasons, suggestive names are the most popular kind of brand name. Fanciful Names Fanciful names can either be completely made-up words with no inherent meaning (like Kodak or Exxon) or real words used out of context, such as Orange bank, Adobe software, and Shell gasoline. Fanciful names are the easiest to trademark because of their distinctiveness, and can attract a lot of attention if done well. But they can require serious marketing to help consumers make the connection with the goods or services they brand. Language Origins Names derived from different languages—whether a Germanic language (like English), a Romance language (like French or Italian), or an entirely non-Indo-European language (like Chinese or Swahili)—can help create a different tone or feel for your brand Exploring other languages when naming is an obvious approach when the target market includes many non-English speakers. But non-English names can also be appealing to native English speakers, especially when they’re familiar foreign words. For example, Tao (“the way” in Mandarin), is the name of an XM receiver, while Boku (from the French “beaucoup” meaning “much” or “many”), is the name of an online payment service, and Asana (both a yoga pose and Sanskrit for “sitting down”),is the name of a shared task list for managing business projects.catchword

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telugu aunty boothu kathalu, family boothu kathalu, soumya reddy boothu kathalu, srungaram telugu kathalu, doola kathalu, boothu kathalu telugu font, telugu hot kathalu, telugu hot story, telugu aunty boothu kathalu download, dengulata telugu kathalu, lanjala kathalu in telugu, New Telugu Boothu Kadhalu, Telugu Aunty Cute Sandlu, Telugu Dengudu Kadhalu,Boothu Kathalu Your brand name is the foundation for all your other marketing efforts. It’s part of your customers’ very first experience of your brand–and likely, every experience thereafter. It’s the verbal trigger that conjures up your brand in your customers’ minds. When customers see or hear your brand name for the first time, the associations and reactions they have will start to define your brand in their minds, for better or worse. A good brand name can go a long way toward: engaging your customers emotionally identifying what sort of product or service you’re offering differentiating you from competitors positioning your brand as the solution for a customer need or desire piquing their curiosity and interest helping your customers remember your brand Good brand names will do at least three of these things—even before you’ve spent a penny on marketing! On the other hand, a bad name will provoke little, if any, positive interest among your audience. It may even mislead them about the nature of your offering and how great it is. You’ll have lost a golden opportunity. Now don’t get us wrong. A great brand name can’t salvage a misconceived or ill executed product or idea. Or convey every relevant marketing message. That’s why you have a logo, and packaging design, and copy, and a website, and all your other marketing communications. But if you want to build a great brand, a good name one that captures the essence of your brand in a memorable way is the foundation. We’re glad you asked. People can be very promiscuous with the word brand. Even some marketing types. They bandy the word about when what they’re really referring to is the brand name. And vice versa. It drives us crazy. So what’s the difference between the two? A “brand” encompasses all of the experiences and expectations that have come to be associated with a company or product line in the customer’s mind. A brand name is just that. One way to look at it is that the brand name is a trigger. Say the word, and you call up all of those associations in the public mind that collectively define the brand and what it stands for. Say the word Apple, for instance, and chances are you think of the iPod and the iMac and the iPad. Of stores that broke all sorts of high-tech retail conventions with their light-filled designer showrooms and hands-on displays. Of cool geniuses at their cool genius bars. Of videotaping your kid’s birthday party or getting the latest ETA on your flight on your iPhone. Of Steve Jobs and MacWorld extravaganzas. Right? That’s the Apple brand for you. On the other hand, the brand name is simply Apple.

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People are often surprised to hear what we do for a living. “You mean companies actually pay you to name things?” they say (or think). The perception of brand naming as something that anyone can do if they really put their mind to it as opposed to a highly specialized, rigorous craft—is widespread in our culture. Because who hasn’t named something at some point in their lives? So how hard can it be? Even companies that pay us good money to create brand names don’t always realize the complexities and challenges of the process. Fact is, brand naming—good brand naming—can be very hard in today’s marketplace. It needs to do a lot of things well. And avoid doing other things (like stepping on someone else’s brand name—also known as trademark infringement). What’s more, the stakes are really high. For while a great name can’t guarantee your company’s or product’s success, it can go a long way towards telegraphing what makes your brand great and attracting customers. Despite its vital importance, few people (and we’re including marketing professionals here) understand all that goes into a successful brand naming process and a great brand name. Which is why we wrote this naming guide. (And why we think you should read it.) If you have a naming challenge on your horizon and are thinking of hiring naming consultants, this guide is for you. We’re going to give you a concise but complete overview of the entire naming process, from brand naming strategy to domain acquisition and trademarking, and beyond. Along the way we’ll share tips and information we’ve gleaned from nearly 15 years in this exciting, challenging business. catch word This guide will help you figure out if you need to hire a naming agency, and how to go about it if you do. It’ll show you how get the most out of your naming agency or internal naming process. Develop appropriate naming strategies. Recognize winning names. And avoid common corporate mistakes when evaluating names and attempting to get internal consensus. It’ll show you that yes, there is a method to this madness; it’s not just about scribbling ideas on cocktail napkins (we wish!). And it’ll show you just what that method is. If you’re going to try to name something on your own, this guide will help you, too. It’s full of insights into every stage of the naming process, and ideas for opening out your creative explorations. Finally, if you just happen to be curious about that mysterious entity known as the naming business, well, this is your chance to get a peek behind the curtain, and witness this highly specialized craft where art meets science.

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For example,the receiver could add in he returned acknowledgement the list of the sequence numbers of all segments that have already been received. Such acknowledgements are sometimes called selective cknowledgements. This is illustrated in the figure below. In the figure above, when the sender receives C(OK,0,[2]), it knows that all segments up to and including D have been correctly received. It also knows that segment D(2,...) has been received and can cancel the retransmission timer associated to this segment. However, this segment should not be removed from the sending buffer before the reception of a cumulative acknowledgement (C(OK,2) in the figure above) that covers this segment. Note: Maximum window size with go-back-n and selective repeat A transport protocol that uses n bits to encode its sequence number can send up to 2n different segments. However, to ensure a reliable delivery of the segments, go-back-n and selective repeat cannot use a sending window of 2n segments. Consider first go-back-n and assume that a sender sends 2n segments. These segments are received in-sequence by the destination, but all the returned acknowledgements are lost. The sender will retransmit all segments and they will all be accepted by the receiver and delivered a second time to the user. It is easy to see thatthis problem can be avoided if the maximum size of the sending window is 2n 􀀀 1 segments. A similar problem occurs with selective repeat. However, as the receiver accepts out-of-sequence segments, a sending window of 2n 1 segments is not sufficient to ensure a reliable delivery of all segments. It can be easily shown that to avoid this problem, a selective repeat sender cannot use a window that is larger than 2n 2 segments. Go-back-n or selective repeat are used by transport protocols to provide a reliable data transfer above an unreliable network layer service. Until now, we have assumed that the size of the sliding window was fixed for the entire lifetime of the connection. In practice a transport layer entity is usually implemented in the operating system and shares memory with other parts of the system. Furthermore, a transport layer entity must support several (possibly hundreds or thousands) of transport connections at the same time. This implies that the memory which can be used to support the sending or the receiving buffer of a transport connection may change during the lifetime of the connection 4 . Thus, a transport protocol must allow the sender and the receiver to adjust their window sizes. To deal with this issue, transport protocols allow the receiver to advertise the current size of its receiving window in all the acknowledgements that it sends. The receiving window advertised by the receiver bounds the size of the sending buffer used by the sender. In practice, the sender maintains two state variables : swin, the size of its sending window (that may be adjusted by the system) and rwin, the size of the receiving window advertised by the receiver. At any time, the number of unacknowledged segments cannot be larger than min(swin,rwin) 5 . The utilisation of dynamic windows is illustrated in the figure below. The receiver may adjust its advertised receive window based on its current memory consumption, but also to limit the bandwidth used by the sender. In practice, the receive buffer can also shrink as the application may not able to process the received data quickly enough. In this case, the receive buffer may be completely full and the advertised receive window may shrink to 0. When the sender receives an acknowledgement with a receive window set to 0, it is blocked until it receives an acknowledgement with a positive receive window. Unfortunately, as shown in the figure below, the loss of this acknowledgement could cause a deadlock as the sender waits for an acknowledgement while the receiver is waiting for a data segment. To solve this problem, transport protocols rely on a special timer : the persistence timer. This timer is started by the sender whenever it receives an acknowledgement advertising a receive window set to 0. When the timer expires, the sender retransmits an old segment in order to force the receiver to send a new acknowledgement, and hence send the current receive window size. To conclude our description of the basic mechanisms found in transport protocols, we still need to discuss the impact of segments arriving in the wrong order. If two consecutive segments are reordered, the receiver relies on their sequence numbers to reorder them in its receive buffer. Unfortunately, as transport protocols reuse the same sequence number for different segments, if a segment is delayed for a prolonged period of time, it might still be accepted by the receiver. This is illustrated in the figure below where segment D is delayed.

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For example, consider the coding scheme that encodes each source bit as follows is encoded as 111 is encoded as For example, consider a sender that sends 111. If there is one bit in error, the receiver could receive 011 or 101 or 110. In these three cases, the receiver will decode the received bit pattern as a 1 since it contains a majority of bits set to 1. If there are two bits in error, the receiver will not be able anymore to recover from the transmission error. This simple coding scheme forces the sender to transmit three bits for each source bit. However, it allows the receiver to correct single bit errors. More advanced coding systems that allow to recover from errors are used in several types of physical layers. Transport protocols use error detection schemes, but none of the widely used transport protocols rely on error correction schemes. To detect errors, a segment is usually divided into two parts : a header that contains the fields used by the transport protocol to ensure reliable delivery. The header contains a checksum or Cyclical Redundancy Check (CRC) [Williams1993] that is used to detect transmission errors a payload that contains the user data passed by the application layer. Some segment headers also include a length , which indicates the total length of the segment or the length of the payload. The simplest error detection scheme is the checksum. A checksum is basically an arithmetic sum of all the bytes that a segment is composed of. There are different types of checksums. For example, an eight bit checksum can be computed as the arithmetic sum of all the bytes of (both the header and trailer of) the segment. The checksum is computed by the sender before sending the segment and the receiver verifies the checksum upon reception of each segment. The receiver discards segments received with an invalid checksum. Checksums can be easily implemented in software, but their error detection capabilities are limited. Cyclical Redundancy Checks (CRC) have better error detection capabilities [SGP98], but require more CPU when implemented in software. Note: Checksums, CRCs, Most of the protocols in the TCP/IP protocol suite rely on the simple Internet checksum in order to verify that the received segment has not been affected by transmission errors. Despite its popularity and ease of implementation, the Internet checksum is not the only available checksum mechanism. Cyclical Redundancy Checks (CRC) are very powerful error detection schemes that are used notably on disks, by many datalink layer protocols and file formats such as zip or png. They can easily be implemented efficiently in hardware and have better error-detection capabilities than the Internet checksum [SGP98] . However, when the first transport protocols were designed, CRCs were considered to be too CPU-intensive for software implementations and other checksum mechanisms were used instead. The TCP/IP community chose the Internet checksum, the OSI community chose the Fletcher checksum [Sklower89] . Now, there are efficient techniques to quickly compute CRCs in software [Feldmeier95] , the SCTP protocol initially chose the Adler-32 checksum but replaced it recently with a CRC (see RFC 3309). The second imperfection of the network layer is that segments may be lost. As we will see later, the main cause of packet losses in the network layer is the lack of buffers in intermediate routers. Since the receiver sends an acknowledgement segment after having received each data segment, the simplest solution to deal with losses is to use a retransmission timer. When the sender sends a segment, it starts a retransmission timer. he value of this retransmission timer should be larger than the round-trip-time, i.e. the delay between the transmission of a data segment and the reception of the corresponding acknowledgement. When the retransmission timer expires, the sender assumes that the data segment has been lost and retransmits it. This is illustrated in the figure below. Unfortunately, retransmission timers alone are not sufficient to recover from segment losses. Let us consider, as an example, the situation depicted below where an acknowledgement is lost. In this case, the sender retransmits.

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ఆంటీ తో మంచం మీద ఒక రాత్రి, The transport layer must deal with the imperfections of the network layer service. There are three types of imperfections that must be considered by the transport layer : Segments can be corrupted by transmission errors Segments can be lost Segments can be reordered or duplicated To deal with these types of imperfections, transport protocols rely on different types of mechanisms. The first problem is transmission errors. The segments sent by a transport entity is processed by the network and datalink layers and finally transmitted by the physical layer. All of these layers are imperfect. For example, the physical layer may be affected by different types of errors : random isolated errors where the value of a single bit has been modified due to a transmission error random burst errors where the values of n consecutive bits have been changed due to transmission errors random bit creations and random bit removals where bits have been added or removed due to transmission errors The only solution to protect against transmission errors is to add redundancy to the segments that are sent. Information Theory defines two mechanisms that can be used to transmit information over a transmission channel affected by random errors. These two mechanisms add redundancy to the information sent, to allow the receiver to detect or sometimes even correct transmission errors. A detailed discussion of these mechanisms is outside the scope of this chapter, but it is useful to consider a simple mechanism to understand its operation and its limitations. Information theory defines coding schemes. There are different types of coding schemes, but let us focus on coding schemes that operate on binary strings. A coding scheme is a function that maps information encoded as a string of m bits into a string of n bits. The simplest coding scheme is the even parity coding. This coding scheme takes an m bits source string and produces an m+1 bits coded string where the first m bits of the coded string are the bits of the source string and the last bit of the coded string is chosen such that the coded string will always contain an even number of bits set.

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telugu aunty boothu kathalu, kamapisachi telugu boothu kathalu, exbii telugu boothu kathalu, newboard telugu boothu kathalu, tappevaridi telugu boothu kathalu, hansika telugu boothu kathalu, telugu boothu kathalu youtube, telugu boothu kathalu archana. The figure above illustrates an internetwork, i.e. a network that interconnects other networks. Each network is illustrated as an ellipse containing a few devices. We will explain throughout the book the different types of devices and their respective roles enabling all hosts to exchange information. As well as this, we will discuss how networks are interconnected, and the rules that guide these interconnections. We will also analyse how the bus, ring and mesh topologies are used to build real networks.The last point of terminology we need to discuss is the transmission modes. When exchanging information through a network, we often distinguish between three transmission modes. In TV and radio transmission, broadcast is often used to indicate a technology that sends a video or radio signal to all receivers in a given geographical area. Broadcast is sometimes used in computer networks, but only in local area networks where the number of recipients is limited. The first and most widespread transmission mode is called unicast . In the unicast transmission mode, information is sent by one sender to one receiver. Most of today’s Internet applications rely on the unicast transmission mode. The example below shows a network with two types of devices : hosts (drawn as computers) and intermediate nodes (drawn as cubes). Hosts exchange information via the intermediate nodes. In the example below, when host S uses unicast to send information, it sends it via three intermediate nodes. Each of these nodes receives the information from its upstream node or host, then processes and forwards it to its downstream node or host. This is called store and forward and we will see later that this concept is key in computer networks. A second transmission mode is multicast transmission mode. This mode is used when the same information must be sent to a set of recipients. It was first used in LANs but later became supported in wide area networks. When a sender uses multicast to send information to N receivers, the sender sends a single copy of the information and the network nodes duplicate this information whenever necessary, so that it can reach all recipients belonging to the destination group. To understand the importance of multicast transmission, consider source S that sends the same information to destinations A, C and E. With unicast, the same information passes three times on intermediate nodes 1 and 2 and twice on node 4. This is a waste of resources on the intermediate nodes and on the links between them. With multicast transmission, host S sends the information to node 1 that forwards it downstream to node 2. This node creates a copy of the received information and sends one copy directly to host E and the other downstream to node 4. Upon reception of the information, node 4 produces a copy and forwards one to node A and another to node C. Thanks to multicast, the same information can reach a large number of receivers while being sent only once on each link.

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telugu aunty boothu kathalu, telugu boothu kathalu, telugu aunty boothu kathalu, kamapisachi telugu boothu kathalu, exbii telugu boothu kathalu, newboard telugu boothu kathalu, tappevaridi telugu boothu kathalu, hansika telugu boothu kathalu, telugu boothu kathalu youtube, telugu boothu kathalu archana. There is as yet no single, commonly-agreed definition of "cloud computing". The United States National Institute of Standards and Technology has defined it as follows "Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction." Under this definition, the cloud model promotes availability and is composed of five essential characteristics, three delivery models and four deployment models. The five key characteristics of cloud computing are on-demand self service, ubiquitous network access, location-independent resource pooling, rapid elasticity and measured service, all of which are geared towards seamless and transparent cloud use. Rapid elasticity enables the scaling up (or down) of resources. Measured services are primarily derived from business model properties whereby cloud service providers control and optimize the use of computing resources through automated resource allocation, load balancing and metering tools. The three cloud service delivery models (see figure 1) are: Application/Software as a Service (SaaS),Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). ITU Technology Watch published a separate report on the cloud computing phenomenon in March 2009 [15]. These three classic cloud service models have different divisions of responsibility with respect to personal data protection. The risks and benefits associated with each model will also differ, and need to be determined on a case-by-case basis and in relation to the nature of the cloud services in question. SaaS enables the consumer to use the provider’s applications running on a cloud infrastructure. The applications are accessible from various client devices through a client interface such as a web browser (e.g. web-based email such as Gmail or CRM from Salesforce). With the SaaS model, the consumer has little or no influence how input data is processed, but should be able to have confidence in the cloud provider’s responsibility and compliance or can control which input he gives to a SaaS. First of all he can avoid to give sensible data to a SaaS. Secondly he might be able to "secure" the sensible data before he inputs them into the SaaS (e.g. their exists plugins for browsers supporting encryption of input form fields. This could be used to send only encrypted mails using Gmail). PaaS provides tools, supported by a cloud provider, that enable developers to deploy applications (e.g. Salesforce's Force.com, Google App Engine, Mozilla Bespin, Zoho Creator). On the one hand, a big responsibility lies with the developer to use best practices and privacy-friendly tools. On the other hand the developer has to rely on the trustworthiness of the underlying PaaS (and related infrastructure). Assume for instance that some developer has developed a cloud application which encrypts all data before it is stored within the cloud storage provided by the PaaS. In this case the developer has to trust that the platform/infrastructure is not compromised. Otherwise the attacker might get access to the clear text (i.e. before encryption happens) – because he can control the execution environment (e.g. virtual machine monitor, hardware etc.). IaaS provides the consumer with computing resources to run software. One example of IaaS is Amazon EC2 Web Services. An IaaS provider will typically take responsibility for securing the data centres, network and systems, and will take steps to ensure that its employees and operational procedures comply with applicable laws and regulations. However, since an IaaS provider may have little application-level knowledge, it will be difficult for that provider to ensure data-level compliance, such as geographic restriction of data transfers. In this case, the responsibility lies with the cloud user to maintain compliance controls. IaaS is the model that guarantees more direct control but also leaves the customer responsible for the implementation of technical and procedural security and resilience measures [6]. With respect to standardization there.

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Just a few years ago, people used to carry their documents around on disks. Then, more recently, many people switched to memory sticks. Cloud computing refers to the ability to access and manipulate information stored on remote servers, using any Internet-enabled platform, including smartphones. Computing facilities and applications will increasingly be delivered as a service, over the Internet. We are already making use of cloud computing when, for example, we use applications such as Google Mail, Microsoft Office365 1 or Google Docs. In the future, governments, companies and individuals will increasingly turn to the cloud. The cloud computing paradigm changes the way in which information is managed, especially where personal data processing is concerned. End-users can access cloud services without the need for any expert knowledge of the underlying technology. This is a key characteristic of cloud computing, which offers the advantage of reducing cost through the sharing of computing and storage resources, combined with an ondemand provisioning mechanism based on a pay-per-use business model. These new features have a direct impact on the IT budget and cost of ownership, but also bring up issues of traditional security, trust and privacy mechanisms. Privacy, in this report, refers to the right to self-determination, that is, the right of individuals to ‘know what is known about them’, be aware of stored information about them, control how that information is communicated and prevent its abuse. In other words, it refers to more than just confidentiality of information. Protection of personal information (or data protection) derives from the right to privacy via the associated right to self-determination. Every individual has the right to control his or her own data, whether private, public or professional. Without knowledge of the physical location of the server or of how the processing of personal data is configured, end-users consume cloud services without any information about the processes involved. Data in the cloud are easier to manipulate, but also easier to lose control of. For instance, storing personal data on a server somewhere in cyberspace could pose a major threat to individual privacy. Cloud computing thus raises a number of privacy and security questions. Can cloud providers be trusted? Are cloud servers reliable enough? What happens if data get lost? What about privacy and lock-in? Will switching to another cloud be difficult? Privacy issues are increasingly important in the online world. It is generally accepted that due consideration of privacy issues promotes user confidence and economic development. However, the secure release, management and control of personal information into the cloud represents a huge challenge for all stakeholders, involving pressures both legal and commercial. This report analyses the challenges posed by cloud computing and the standardization work being done by various standards development organizations (SDOs) to mitigate privacy risks in the cloud, including the role of privacy-enhancing technologies.