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As a part of compliance requirements, companies often need to verify which computers in the organization are encrypted. And in the case of lost or stolen laptops, they must provide proof these missing devices are encrypted. Central Device Encryption makes it easy to verify encryption status and demonstrate compliance. Aug 04,  · Finally, because free online PDF editors are used on-the-fly, they generally have much simpler, more-intuitive interfaces and tools than paid editors do. mentioned in this article Adobe Acrobat Pro DC. Aug 03,  · Read expert tips on how to build a customer-first organization and encryption. If you create PDFs regularly for your job and need a way to collaborate on the same file, Foxit would be a good option. 2. Adobe Acrobat Reader DC. Image Source. Adobe’s free PDF reader, Adobe Acrobat Reader DC, connects to the Adobe Document cloud and other.
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This new methodology also is briefly described below, as it will likely be of interest to all users of data tabulated by ZIP code. The Census Bureau will not be producing data files containing U.

Zip codes can cross State, place, county, census tract, block group, and census block boundaries. The geographic designations the Census Bureau uses to tabulate data are relatively stable over time. For instance, census tracts are only defined every ten years. In contrast, ZIP codes can change more frequently. Postal Service ZIP codes.

ZCTAs are generalized area representations of U. The Bureau of the Census provides information regarding population density in the United States. Covered entities are expected to rely on the most current publicly available Bureau of Census data regarding ZIP codes. The information is derived from the Decennial Census and was last updated in It is expected that the Census Bureau will make data available from the Decennial Census in the near future. This guidance will be updated when the Census makes new information available.

For example, a data set that contained patient initials, or the last four digits of a Social Security number, would not meet the requirement of the Safe Harbor method for de-identification. Elements of dates that are not permitted for disclosure include the day, month, and any other information that is more specific than the year of an event.

Many records contain dates of service or other events that imply age. Ages that are explicitly stated, or implied, as over 89 years old must be recoded as 90 or above. Dates associated with test measures, such as those derived from a laboratory report, are directly related to a specific individual and relate to the provision of health care. Such dates are protected health information.

As a result, no element of a date except as described in 3. This category corresponds to any unique features that are not explicitly enumerated in the Safe Harbor list A-Q , but could be used to identify a particular individual. Thus, a covered entity must ensure that a data set stripped of the explicitly enumerated identifiers also does not contain any of these unique features.

The following are examples of such features:. Identifying Number There are many potential identifying numbers. Identifying Code A code corresponds to a value that is derived from a non-secure encoding mechanism. For instance, a code derived from a secure hash function without a secret key e. This is because the resulting value would be susceptible to compromise by the recipient of such data.

As another example, an increasing quantity of electronic medical record and electronic prescribing systems assign and embed barcodes into patient records and their medications. See the discussion of re-identification. Identifying Characteristic A characteristic may be anything that distinguishes an individual and allows for identification. Generally, a code or other means of record identification that is derived from PHI would have to be removed from data de-identified following the safe harbor method.

The objective of the paragraph is to permit covered entities to assign certain types of codes or other record identification to the de-identified information so that it may be re-identified by the covered entity at some later date. In the context of the Safe Harbor method, actual knowledge means clear and direct knowledge that the remaining information could be used, either alone or in combination with other information, to identify an individual who is a subject of the information.

This means that a covered entity has actual knowledge if it concludes that the remaining information could be used to identify the individual. The covered entity, in other words, is aware that the information is not actually de-identified information. Example 2: Clear Familial Relation Imagine a covered entity was aware that the anticipated recipient, a researcher who is an employee of the covered entity, had a family member in the data e.

In addition, the covered entity was aware that the data would provide sufficient context for the employee to recognize the relative. In this situation, the risk of identification is of a nature and degree that the covered entity must have concluded that the recipient could clearly and directly identify the individual in the data. Example 3: Publicized Clinical Event Rare clinical events may facilitate identification in a clear and direct manner.

For instance, imagine the information in a patient record revealed that a patient gave birth to an unusually large number of children at the same time. During the year of this event, it is highly possible that this occurred for only one individual in the hospital and perhaps the country.

As a result, the event was reported in the popular media, and the covered entity was aware of this media exposure. In this case, the risk of identification is of a nature and degree that the covered entity must have concluded that the individual subject of the information could be identified by a recipient of the data.

In this situation, the covered entity has actual knowledge because it was informed outright that the recipient can identify a patient, unless it subsequently received information confirming that the recipient does not in fact have a means to identify a patient.

Much has been written about the capabilities of researchers with certain analytic and quantitative capacities to combine information in particular ways to identify health information. OCR does not expect a covered entity to presume such capacities of all potential recipients of de-identified data.

This would not be consistent with the intent of the Safe Harbor method, which was to provide covered entities with a simple method to determine if the information is adequately de-identified. Only names of the individuals associated with the corresponding health information i.

There is no explicit requirement to remove the names of providers or workforce members of the covered entity or business associate. At the same time, there is also no requirement to retain such information in a de-identified data set.

Beyond the removal of names related to the patient, the covered entity would need to consider whether additional personal names contained in the data should be suppressed to meet the actual knowledge specification. Additionally, other laws or confidentiality concerns may support the suppression of this information. However, nothing prevents a covered entity from asking a recipient of de-identified information to enter into a data use agreement, such as is required for release of a limited data set under the Privacy Rule.

This agreement may prohibit re-identification. Of course, the use of a data use agreement does not substitute for any of the specific requirements of the Safe Harbor method. PHI may exist in different types of data in a multitude of forms and formats in a covered entity. This data may reside in highly structured database tables, such as billing records. Yet, it may also be stored in a wide range of documents with less structure and written in natural language, such as discharge summaries, progress notes, and laboratory test interpretations.

These documents may vary with respect to the consistency and the format employed by the covered entity. The de-identification standard makes no distinction between data entered into standardized fields and information entered as free text i. Whether additional information must be removed falls under the actual knowledge provision; the extent to which the covered entity has actual knowledge that residual information could be used to individually identify a patient.

In structured documents, it is relatively clear which fields contain the identifiers that must be removed following the Safe Harbor method. For instance, it is simple to discern when a feature is a name or a Social Security Number, provided that the fields are appropriately labeled. However, many researchers have observed that identifiers in medical information are not always clearly labeled. It also is important to document when fields are derived from the Safe Harbor listed identifiers.

For instance, if a field corresponds to the first initials of names, then this derivation should be noted. De-identification is more efficient and effective when data managers explicitly document when a feature or value pertains to identifiers. Health Level 7 HL7 and the International Standards Organization ISO publish best practices in documentation and standards that covered entities may consult in this process. The covered entity must remove this information. The phrase may be retained in the data.

Note: some of these terms are paraphrased from the regulatory text; please see the HIPAA Rules for actual definitions. Information that is a subset of health information, including demographic information collected from an individual, and: 1 Is created or received by a health care provider, health plan, employer, or health care clearinghouse; and 2 Relates to the past, present, or future physical or mental health or condition of an individual; the provision of health care to an individual; or the past, present, or future payment for the provision of health care to the individual; and i That identifies the individual; or ii With respect to which there is a reasonable basis to believe the information can be used to identify the individual.

In an effort to make this guidance a useful tool for HIPAA covered entities and business associates, we welcome and appreciate your sending us any feedback or suggestions to improve this guidance. You may submit a comment by sending an e-mail to ocrprivacy hhs. OCR gratefully acknowledges the significant contributions made by Bradley Malin, PhD, to the development of this guidance, through both organizing the workshop and synthesizing the concepts and perspectives in the document itself.

OCR also thanks the workshop panelists for generously providing their expertise and recommendations to the Department. To sign up for updates or to access your subscriber preferences, please enter your contact information below.

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Affiliate marketing is a popular component of marketing as it helps in driving sales and produces significant online revenues. There are three different types of affiliate marketing. Unattached: In this business model, the affiliates have no relation to the products or the services they are selling. They do not have any standing in that particular subject, and neither can they make any claims on the use of the products. The unattached affiliate marketing is based on a pay per click campaign.

The affiliates use the affiliate link to get the customers to visit the link and purchase some products. It is a popular type of affiliate marketing due to its lack of responsibility and is generally suitable for those who are looking for a passive income. Related: The related business model strikes a balance between unattached and involved business models. In this day and age, waiting on a document to return means missing deadlines, delaying production, or turning potential customers away altogether.

The solution, of course, is sending that same document as a fillable PDF. Fillable PDFs are online documents that have editable fields but do not require recipients to use PDF editing software. On the whole, fillable PDFs have enormous benefits.

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In response to widespread Internet postings of the key, the AACS LA issued various press statements, praising those websites that complied with their requests for acting in a “responsible manner” and warning that “legal and technical tools” were adapting to the situation. The controversy was further escalated in early May , when aggregate news site Digg received a DMCA cease and desist notice and then removed numerous articles on the matter and banned users reposting the information.

Hexadecimal is a base numeral system used in the fields of computer programming and mathematics. Because the encryption key may be used as part of circumvention technology forbidden by the DMCA , its possession and distribution has been viewed as illegal by the AACS , as well as by some legal professionals. There are several interlocking encryption mechanisms, such that cracking one part of the system does not necessarily crack other parts. Therefore, the “09 F9” key is only one of many parts that are needed to play a disc on an unlicensed player.

If other players are then cracked, further revocation would lead to legitimate users of compromised players being forced to upgrade or replace their player software or firmware in order to view new discs. Each playback device comes with a binary tree of secret device and processing keys.

The processing key in this tree, a requirement to play the AACS encrypted discs, is selected based on the device key and the information on the disc to be played. As such, a processing key such as the “09 F9” key is not revoked, but newly produced discs cause the playback devices to select a different valid processing key to decrypt the discs.

On January 1, , muslix64 published a new version of the program, with volume key support. On or about January 13, a title key was posted on pastebin. By converting these results to hexadecimal, a correct key could be formed. Nothing was hacked, cracked or even reverse-engineered btw: I only had to watch the “show” in my own memory. No debugger was used, no binaries changed. This key is not specific to any playback device or DVD title. On May 17, one week before any discs with the updated processing key had reached retail, claims were reported of the new keys having been retrieved from a preview disc of The Matrix Trilogy.

Sims of Proskauer Rose. On May 1, , in response to a DMCA demand letter, technology news site Digg began closing accounts and removing posts containing or alluding to the key. The Digg community reacted by creating a flood of posts containing the key, many using creative ways of disguising the key, [41] by semi-directly or indirectly inserting the number, such as in song or images either representing the digits pictorially or directly representing bytes from the key as colors or on merchandise.

But now, after seeing hundreds of stories and reading thousands of comments, you’ve made it clear. You’d rather see Digg go down fighting than bow down to a bigger company. We hear you, and effective immediately we won’t delete stories or comments containing the code and will deal with whatever the consequences might be. Lawyers and other representatives of the entertainment industry, including Michael Ayers, an attorney for Toshiba Corporation, expressed surprise at Digg’s decision, but suggested that a suit aimed at Digg might merely spread the information more widely.

If you try to stick up for what you have a legal right to do, and you’re somewhat worse off because of it, that’s an interesting concept.

The American Bar Association ‘s eReport published a discussion of the controversy, [48] in which Eric Goldman at Santa Clara University ‘s High Tech Law Institute noted that the illegality of putting the code up is questionable that Section of the Communications Decency Act may protect the provider when the material itself is not copyrighted , although continuing to allow posting of the key may be “risky”, and entertainment lawyer Carole Handler noted that even if the material is illegal, laws such as the DMCA may prove ineffective in a practical sense.

In a response to the events occurring on Digg and the call to “Spread this number”, the key was rapidly posted to thousands of pages, blogs and wikis across the Internet. Intellectual property lawyer Douglas J. Sorocco noted, “People are getting creative. It shows the futility of trying to stop this. Once the information is out there, cease-and-desist letters are going to infuriate this community more. On Tuesday afternoon, May 1, , a Google search for the key returned 9, results, [55] while the same search the next morning returned nearly , results.

Widespread news coverage [43] [58] [45] [59] [60] included speculation on the development of user-driven websites, [61] the legal liability of running a user-driven website, [62] the perception of acceptance of DRM , [63] the failure as a business model of “secrecy based businesses In an opposing move, Carter Wood of the National Association of Manufacturers said they had removed the “Digg It”-link from their weblog.

Until the Digg community shows as much fervor in attacking intellectual piracy as attacking the companies that are legitimately defending their property, well, we do not want to be promoting the site by using the “Digg It” feature.

Media coverage initially avoided quoting the key itself. However, several US-based news sources have run stories containing the key, quoting its use on Digg, [67] [68] [69] [70] [71] [72] though none are known to have received DMCA notices as a result. Later reports have discussed this, quoting the key. Wikipedia , on May 1, , locked out the page named for the number “to prevent the former secret from being posted again. On May 7, , the AACS LA announced on its website that it had “requested the removal solely of illegal circumvention tools, including encryption keys, from a number of web sites”, and that it had “not requested the removal or deletion of any The statement continued, “AACS LA is encouraged by the cooperation it has received thus far from the numerous web sites that have chosen to address their legal obligations in a responsible manner.

From Wikipedia, the free encyclopedia. Controversy regarding copyright. Wikinews has related news: Digg. Retrieved May 3, Brisbane Times. Retrieved September 24, Archived from the original on March 10, Jeff Thompson. Archived from the original on September 24, An example of this is the so-called ‘Free Speech Flag’, seen above. Crypto Anarchy.

ISBN Conyers Cyberwarfare Sourcebook. Chilling Effects. Retrieved May 4, ZDNet UK. Archived from the original on June 12, Retrieved May 18, The Inquirer. Archived from the original on October 29, Sci-Tech Today. Archived from the original on May 6, May 2, Archived from the original on July 3, Retrieved May 20, Malone May 3, Patents in Web 2.

Archived from the original on May 5, Archived from the original on May 7, The New York Times. ISSN Archived from the original on August 8, Retrieved May 8, Based on our scan system, we have determined that these flags are possibly false positives. It means a benign program is wrongfully flagged as malicious due to an overly broad detection signature or algorithm used in an antivirus program. What do you think about PDF Eraser? Do you recommend it?

PDF Eraser for Windows. PDF Rider 0. PDF Splitter 1. PDFedit 1. PDFTK 2. Property Management Database Software. Your review for PDF Eraser. Leave a review.

This free tool allows you to remove unwanted text and images from your PDF document. You don’t need to worry about compatibility, as this app will work on all PDF files. Have you tried PDF Eraser? Be the first to leave your opinion! Laws concerning the use of this software vary from country to country. We do not encourage or condone the use of this program if it is in violation of these laws.

In Softonic we scan all the files hosted on our platform to assess and avoid any potential harm for your device. Our team performs checks each time a new file is uploaded and periodically reviews files to confirm or update their status.

This comprehensive process allows us to set a status for any downloadable file as follows:. We have scanned the file and URLs associated with this software program in more than 50 of the world’s leading antivirus services; no possible threat has been detected. Based on our scan system, we have determined that these flags are possibly false positives. It means a benign program is wrongfully flagged as malicious due to an overly broad detection signature or algorithm used in an antivirus program.

What do you think about PDF Eraser? Do you recommend it? PDF Eraser for Windows. PDF Rider 0. PDF Splitter 1. PDFedit 1. PDFTK 2.

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In cryptography, key size, key length, or key space refer to the number of bits in a key used by a cryptographic algorithm (such as a cipher).. Key length defines the upper-bound on an algorithm’s security (i.e. a logarithmic measure of the fastest known attack against an algorithm), since the security of all algorithms can be violated by brute-force attacks. Jul 28,  · It comes with a complete set of free PDF editing tools; Cons: With heavy PDF, OCR is ineffective; Top 9. Expert PDF Viewer – Versatile PDF Viewer and Editor for Windows. Expert PDF Viewer is a free PDF viewer for Windows, which allows you to open and print PDFs. You can also use it to make simple changes to existing PDF documents. Aug 03,  · Read expert tips on how to build a customer-first organization and encryption. If you create PDFs regularly for your job and need a way to collaborate on the same file, Foxit would be a good option. 2. Adobe Acrobat Reader DC. Image Source. Adobe’s free PDF reader, Adobe Acrobat Reader DC, connects to the Adobe Document cloud and other. Customers can control encryption in transit with TLS across AWS services. • Connectivity options that enable private, or dedicated, connections from your office or on-premises AWS Trusted Advisor is an online tool that acts like a customized cloud expert, helping you to configure This free tool is available in the AWS Management.

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By using our site, you agree to our collection of information through the use of cookies. To learn more, view our Privacy Policy. To browse Academia. Log in with Facebook Log in with Google. Remember me on this computer. Enter the email address you signed up with and we’ll email you a reset link. Need an account? Click here to sign up. Download Free PDF. Vincenzo D Crawford. Vincenzo Crawford. A short summary of this paper. PDF Pack. People also downloaded these PDFs.

People also downloaded these free PDFs. The impact of full disk encryption on digital forensics by Eoghan Casey. Bringing science to digital forensics with standardized forensic corpora by George Dinolt. Observations on dental structures and restorative materials subjected to high temperatures in an animal model. Experimental preliminary studies by Giuseppe Merlati. Download Download PDF. Translate PDF. Crawford Bs. Forensic Science Background to the Case Therese Brain child, a master accountant hired by Safe Data Associates was suspected of being engaged in cyber crimes, industrial espionage, embezzlement and terrorism.

Brainchild opted to delete files from her thumb drive kept at her workstation before being escorted from the building and her administrative duties. To conduct an effective and efficient investigation, I employed the use of the Forensic Tool Kit Imager software FTK Imager in order to recover the files deleted from the thumb drive said to be that of Brainchild’s; Based on my expert knowledge of digital forensics, these deleted files will still be lingering in what is called the ‘unallocated space’ of the thumb drive.

She was questioned in order to acquire legitimacy for data acquisition. The following questions were brought forward: Questions 1. Is the computer system, thumb drive and other devices personal or were they assigned to Brainchild by the company? If these devices were assigned by the company, were they being used before, during and or shortly after they were assigned to the accused Therese Brainchild? Search and seizer and transport of evidence A request was filed for legal authorities to enter the dwelling of Theresa Brainchild.

The warrant was issued for the search and seizer of devices which may be analyzed and serve as digital evidence, in order to convict or exonerate her. Upon the search and seizer of the necessary devices which may provide digital evidence, the acquired materials were carefully package and a chain of custody was efficiently established; so to ensure the integrity of the evidence.

Burgundy Wi-Fi Mobile Cellphone 2. Nokia Mobile Phone 3. Black Dapeng cellphone 3 Vincenzo D. Were the three 3 cell phones; exhibits 1, 2 and 4 [serial- , and , respectively] used to call individuals, or browse for information which may be deemed as incriminating and of relevance to the investigation?

Did anyone else other than the accused have access to the thumb drive; exhibit 3 [serial- FYY ] before, during and or after Brainchild’s possession of it? Evidence to Search For Based on the nature of the case and all that which have been made against the accused Therese Brainchild , to begin analysis of the obtained evidence, the search for data of probative value to the investigation will be in the area of; A acquiring the browsing data from the laptop and cell phones’ browsers, B investigate the previous locations and calls made to and from the cell phones, C The acquisition of files deleted from the laptop, phone memories and most importantly files deleted from the thumb drive.

Deleted files of evidentiary value to the case 5. These documents contained; code clues, encrypted and steganographic files, erroneous documents, stolen credit cards information, cheque details, information on lottery winners. The five 5 txt files recovered contained names, address, phone numbers and credit card information of individuals.

Among these files, were steganographic clues to encrypted data. However, only 4 of these documents were relevant to the investigation as they contained, lottery leads, bank cheque, stolen credit cards information and a terrorist map. Forensic Science 6. Corporate Breach Theresa Brainchild, deemed to have committed corporate breaches such as; the breach of contract to maintain data integrity and company confidentiality, falsification of data, Embezzlement and industrial espionage.

The sha1 hash value e2abcf6fe70bd9eefdd and MD5 hash value 3b50d4fde5c5c29ef7fdbc1d were obtained in order to aid in proving the legitimacy of the files recovered. Among the files recovered, there was a database document named ‘Snowden Employee. Deleted, Encrypted and Steganographic files Approximately forty-one 41 files of different formats were deleted.

Of all the files retrieved, two 2 files and one 1 folder was encrypted. The encrypted files were cracked as a result of steganograpic files which contained clues and passwords to break the encryption. The encrypted files and passwords are as follows;.

Rar file entitled ‘x’ containing; 1 Database documents of customer and employees’ detailed information names, positions, ID numbers, bill payments and account numbers, accounts 5 Vincenzo D. Forensic Science above dollars. The steganographic files obtained were hidden in various forms. The Personal and Swiss bank account numbers of Therese Brainchild recovered from encryption is; [ and respectively]. Forensic Science 9. Analysis Results From the above exhibits; The cell phones confiscated for analysis, ‘Burgundy Wi-Fi Mobile Cellphone’, ‘Nokia Mobile Phone’ and ‘Black Dapeng cellphone’, exhibits 1, 2 and 5 [serial- , and , respectively], were analyzed and I calculated their check digit in order to verify the IMEIs which intern reveals the make, model, date and country of origin of all three exhibits.

The check digits calculated are as follows: Exhibit 1, Wi-Fi Mobile Cellphone, [serial – , corrected was found to be ‘6’]. Exhibit 2, Nokia Mobile Phone, [serial – , correct check digit found to be ‘4’].

Exhibit 5, Black Dapeng cellphone, [serial – , [check digit remains unchanged ‘0’] Further analysis brought to the forefront, identified metadata information which proved to be vital to this investigation. Password clue to the binary digits password [] required to open the ‘rar’ file entitled ‘x’ containing fraudulent activities of Therese Brainchild. Passwords were also hidden in Steganography files which lead to brainchild’s Personal bank account and Swiss bank account.

Conclusion and I managed to maintain the integrity of all the deleted data during its recovery as all the exhibits were protected and verified by checking hash values and recalculating check digits during the examination. Forensic methods for detection of deniable encryption in mobile networks by Angela Irwin. Use of computer forensics in the digital curation of removable media by William Glisson.

Customers can control encryption in transit with TLS across AWS services. • Connectivity options that enable private, or dedicated, connections from your office or on-premises AWS Trusted Advisor is an online tool that acts like a customized cloud expert, helping you to configure This free tool is available in the AWS Management. Aug 04,  · Finally, because free online PDF editors are used on-the-fly, they generally have much simpler, more-intuitive interfaces and tools than paid editors do. mentioned in this article Adobe Acrobat Pro DC. Vince Cate put up a web page that invited anyone to become an international arms trafficker; every time someone clicked on the form, an export-restricted item — originally PGP, later a copy of Back’s program — would be mailed from a US server to one in Anguilla.. Cypherpunk fiction. In Neal Stephenson’s novel Cryptonomicon many characters are on the “Secret Admirers” . PDF file manager and image and text extractor. PDF Explorer is a nice, free Windows program, that belongs to the category Business software with subcategory PDF.. More about PDF Explorer. About the download, PDF Explorer is a slick software that will require less storage space than many software in the section Business software. Manage encryption keys on Google Cloud. Start building right away on our secure, intelligent platform. New customers get $ in free credits to use toward Google Cloud products and services. Get answers to technical questions from expert communities, including Stack Overflow, Server Fault, and Google Groups.

There are several software tools available that make editing a PDF a straightforward process. Apple provides every Mac with Preview, a free program that allows you to view and edit a PDF and other file types. With Preview, you can highlight text, include a signature, or add text and comments. You probably have a copy of Microsoft Word already. You can then edit the document as needed. When finished, save the document as a PDF. There are dozens of tools that allow you to edit a PDF on Windows; however, most of these come with a price.

Go to the Comment menu and choose from the following buttons:. A dedicated PDF reader usually comes with more functionality, such as converting PDFs , adding signatures, annotating, and combining pages. We combed the internet, tried a bunch of editors, and found the best free ones for you to try. If you have offices in different parts of the country or world and need to collaborate on documents, it can be very difficult to exchange documents constantly through email and work on the most updated draft.

Even people who work on the same floor, or in the same building, can run into this same issue. Google Docs and Sheets allows you to collaborate in real time, provides you with a document-authoring tool, and stores your files online. This makes it easy for multiple users to edit a document at the same time, and see any changes instantaneously. To export the document to a PDF file, follow these steps:. Reducing the size is not a problem with a robust PDF editing tool.

If you need it really small, you can set it to a later version of Adobe Acrobat. Rename the file, if you want to create a new, smaller version of your original file. This will keep your original, large file. Acrobat will ask if you really want to overwrite your original file. Drop all the files you want to reduce into that box and a batch of smaller PDFs will appear.

Having trouble with deleting pages from your PDF? In most cases, the entire process can be done in just a few quick steps — and we have plenty of pictures that you can reference along the way. Need to merge several PDF files together to create a cohesive document? Have a large document that you want to split into smaller sections? Or, do you just need a few pages and want to extract them from a larger document? They make the process of sharing important, print-ready files a breeze.

Oftentimes, companies are faced with lengthy Microsoft Excel sheets that contain troves of data to sift through and organize. Collecting data is just the first step, though. Once you have the information, you need to figure out how to present it to your audience in a way that makes sense. You need to be cognizant of where to insert text, images, and graphics so the end product is easy to understand and looks professional.

Be careful when putting a PDF together because there are many ways for things to go wrong. There are a few issues that plague even the most seasoned PDF professionals. One big problem is getting an image in a PDF to look just right. Another major flub is not setting up the bleed, or margin, correctly. A survey conducted by Ghent Workgroup, an international graphic arts think tank, found that errors in PDF files are, perhaps, more common than we may think, even among experts.

According to Prepressure. Another 25 percent of survey respondents — or people — reported finding errors in 10 to 50 percent of the PDF files that came across their desk. That may sound like a lot of PDF errors floating around, but close to 52 percent of those professionals who were surveyed — or people — reported finding errors in less than 10 percent of PDF files, if any at all.

The fact is that a wide range of things can go wrong at any given time. When edits must be made, people need to use software, which can be either robust and pricey, or basic and free. Regardless of which software you choose to use, it will take time to edit any errors or information. Problems with editing PDF files manually tend to vary with each case, although there are a few commonalities.

There always seems to be a problem with matching font type and size when editing a PDF manually, so be careful when injecting new fonts into your PDF. You can use free tools, such as WhatTheFont , to see what type of font was used in the original PDF and then match it accordingly while editing.

Some software will allow you to shift PDF content around with ease, while some software will require more of a design eye to make everything look just right. We have the rundown on what to do in the subsections below. But the problem with gathering a lot of information is figuring out ways to organize and manage it.

There are many tools out there that range from free to pricey, depending on your needs. Choosing a strong tool is the first order of business before embarking on your information collection journey because it will help you gather information efficiently and effectively. A big information collection issue is not having a big-picture mindset about what information to collect and what should be understood from the data.

This will vary depending on the tool you choose, answers to your questions, and your goals. Having a plan is important because it will help you achieve your goals and stay on the path to success. Once you have everything in place, you can start collecting information. Before taking on the task of turning your data into a document, revisit your answers to the key questions outlined at the start of your project: Why are you collecting information?

What is its purpose? What do you want to do with the information? It can take extra time, energy, and attention to detail to get your data into a document and have it look just right. Healthcare companies are a great example of this.

They receive mass amounts of patient data every single day, including general information, current state of health, health records, medication usage, and family health history. But healthcare organizations must find a way to consolidate this data into one document so they can share it easily with medical staff, referral doctors, and patients. Small and large businesses; nonprofits; and educational institutions struggle with turning valuable information into documents.

You also can face similar hardships while creating a custom design for your PDF. PDF files come in all shapes and sizes.

Most organizations are plagued with the need for a well-designed PDF. Nonprofits, for instance, need custom PDFs designed for event invitations. They funnel this data into a Microsoft Excel sheet, which is great, but how will that information be used to create invitations? The nonprofit needs to transfer the data into a professional-looking document so they can mail out formal invitations. Usually, the easiest way to do this is to extract information manually from an Excel spreadsheet, place it into a PDF, and figure out a way to design it.

Designing a PDF this way is unproductive, especially when there are automated ways to streamline the process. There are many other examples in which organizations or individuals must turn information into documents. This is a common situation for contractual agreements, including instances when a real estate agent, financial professional, or advertising agent must turn information about a deal into a document.

For example, if a financial planner wants to close a deal on an investment opportunity and must transfer client information into a PDF, he or she will want a seamless way to get it done. Simply turning information into documents will save time and increase productivity.

Turning information into documents also allows for easy sharing, which can be implemented by companies — large and small. Oftentimes, design software has a lot of bells and whistles that can feel overwhelming to people with non-design backgrounds. Moreover, the surplus of features can have an adverse effect and encourage people to add more colors, fonts, and images unnecessarily. Before getting started, think about what you want your PDF to achieve.

What point are you trying to make? What do you want people to glean from it? Luckily, there are ways to automate this process.

Read on to learn more! It sucks your valuable time and adds tedious work to your day. So the question remains: how do you automate this process.

More importantly, a lot of forms you encounter today are easy to fill out from mobile and tablet devices, meaning higher completion rates and more accurate information. Using online forms, you can collect signatures, dates, long text fields, images, and just about anything else you can imagine.

Need a way to design customized documents seamlessly using data from completed forms that you make and send out? It connects to any online form you have with the platform, and responses that you receive through your form automatically populate sections of the PDF with the information you need.

So, that one PDF template you create automatically turns into dozens, hundreds, or even thousands of unique PDFs as people fill out your form and submit it to you. Regardless of whether you use PDFs internally or want it sent out to clients as a professional-looking document, you need a fast way to automate the process.

Jotform forms and this product solves this problem by turning form responses into designed PDFs. It requires a minimal amount of time up front but saves hours of time and allows you to become more productive. The features of the tool comes to serve the common problems of everyday PDF users since it came as an idea from listening to our users and their problems in many different industries. Automation, design, communication and durability were 4 main pillars that came out from all that we have build our product on.

Jotform users across a diverse range of industries — from a paint distributor in Calgary, Canada, to an event management company in Metro Vancouver, Canada — have tried PDF Editor and incorporated it into their workflows.

With Jotform PDF Editor, you can not only turn submission data into polished PDF documents that can be shared with clients but also create a plain copy for your records. Many of these new features were directly inspired by our users, who felt there was a better way to turn bland, clunky PDFs into professional-looking documents. Anyone who works in the field needs to have an airtight system for not only collecting information, but also for sending it back to the office.

If the final assessment of field data is supposed to be shown as a polished, professional PDF, then how on earth do you simplify that?

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Ambush marketing, a term first coined by marketing guru Jerry Welsh, has not really been rigorously defined. However, it broadly refers to a situation in which a company or product seeks to ride on the publicity value of a major event without having contributed to the financing of the event through sponsorship. It is typically targeted at major sporting events – like the Olympic Games or the world.

Behavioral segmentation is a more focused form of market segmentation that groups different consumers based on specific behavioral patterns they display when making buying a product. Description: Behavioral segmentation classifies organizations and individuals into different categories based on how they act or behave towards products.

It involves classifying consumers or grouping them based on. This strategy revolves around searching for a business in which very few firms operate and where there is no pricing pressure. Description: Blue Ocean Strategy can be applied across sectors or businesses. It is not limited to just one business. But, let’s first understand what is B. A brand tribe could be regarded as a group of people who collectively identify themselves with the product and share similar views and notions about the brand.

They are not just consumers of the product, but play a major role in its promotion. Description: A product is successful when it becomes a cult. Companies are not just selling consumers their products nowadays, but an idea, a vision as h. Brand valuation is the process used to calculate the value of a brand or the amount of money another party is prepared to pay for it. Description: A brand comprises tangible as well as intangible elements relating to the company’s style, culture, positioning, messages, promises and value proposition.

Brand Valuation, subsequently, is an estimate of the financial value of a brand. There is no un. Nifty 17, JSW Energy Market Watch. Mutual Funds. ET NOW. Suggest a new Definition Proposed definitions will be considered for inclusion in the Economictimes.

Ambient Advertising. Have you observed the tags ‘affiliate links’ or ‘sponsored posts’ on websites before? What is affiliate marketing? Affiliate marketing definition includes an affiliate promoting other people’s products and receiving a small commission whenever a sale is made.

The affiliate shares the ad or link of the product on their platform, and when a customer clicks on the links and purchases the products, the conversion gets tracked, and the affiliate is provided with a commission. Affiliate marketing is a popular component of marketing as it helps in driving sales and produces significant online revenues. There are three different types of affiliate marketing. Unattached: In this business model, the affiliates have no relation to the products or the services they are selling.

Patents in Web 2. Archived from the original on May 5, Archived from the original on May 7, The New York Times.

ISSN Archived from the original on August 8, Retrieved May 8, Freedom to Tinker. Archived from the original on September 23, Retrieved January 8, Ars Technica. Archived from the original on May 10, Retrieved May 2, Doom9’s Forum. Archived from the original on March 22, Retrieved April 9, July 25, Archived from the original PDF on February 9, December 28, Retrieved January 2, January 26, Archived from the original on February 3, Retrieved January 26, Archived from the original on May 4, Doom9’s Forums.

April 16, Retrieved November 11, Archived from the original on May 19, Retrieved May 17, Retrieved December 12, MKB v3 is now open “. Archived from the original on June 1, Retrieved May 30, April 17, May 1, Darknet Diaries. Jack Rhysider. Retrieved May 11, Digg the Blog. Digg Inc. Archived from the original on May 16, Archived from the original on October 6, Retrieved October 29, Los Angeles Times latimes. ABA Journal. Archived from the original on June 23, April 30, Archived from the original on May 2, WikiEN-L mailing list.

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This guidance is intended to assist covered entities to understand what is de-identification, здесь general process by which de-identified information is created, and the options available for performing de-identification. In developing this guidance, the Office for Civil Rights OCR solicited input from stakeholders with rree, technical and policy experience in de-identification. OCR convened stakeholders at a workshop consisting of multiple panel sessions held March, in Washington, DC.

The workshop was open to the public and each panel was followed enfryption a question and answer period. Read the Full Guidance. Protected health information is information, including demographic information, which relates to:.

By contrast, a health plan report that only noted the average age of health plan members was 45 years would not be PHI because that information, although developed by pdf expert encryption free information from individual plan member records, does not identify any individual plan members and there is no reasonable basis to believe that it could be used to identify an individual.

The relationship with health information is fundamental. Identifying information alone, such as personal names, residential addresses, or phone numbers, would not necessarily be designated as PHI. For instance, if such information was reported as part of a publicly accessible data нра) cdw windows server 2016 standard free download очень, such as a phone book, then this information would not be PHI because it is not related to heath data see above.

If such information was listed with health condition, health care provision or payment data, such as an indication that the individual was treated at http://replace.me/24087.txt certain clinic, then this information would be PHI.

In general, the protections of the Privacy Rule apply to information held by covered entities and their business associates. HIPAA defines a covered entity as 1 a health care provider that conducts certain encrryption administrative and financial transactions in electronic form; 2 a health care clearinghouse; or 3 a health plan. A covered entity may use a business associate experh de-identify PHI on its behalf only to the extent such читать полностью is authorized by their business associate agreement.

The increasing adoption of health information technologies in the United States accelerates their potential to facilitate beneficial studies that combine large, complex data sets from multiple sources. The process of de-identification, by which identifiers are removed from the pdf expert encryption free information, mitigates privacy risks to individuals and thereby supports the secondary use of data for comparative effectiveness studies, policy assessment, life sciences research, and other endeavors.

The Privacy Rule was designed to protect individually identifiable health information through permitting only certain uses and disclosures of PHI provided by the Rule, or as authorized by the individual subject of the information. These provisions allow the entity to use and disclose information that neither identifies nor provides a reasonable basis to identify an individual.

Both methods, even when properly frew, yield de-identified data that retains encryptiom risk of identification. Although the risk is very small, it is not pdf expert encryption free, and there is a possibility that de-identified data could be linked back to the identity of the patient to which it corresponds. Regardless pddf the method by which de-identification is achieved, the Privacy Rule does not restrict the use or disclosure of de-identified health information, as it is no longer considered protected health information.

Section Under this standard, health information is not individually identifiable if it does not identify an individual and if the covered entity has no reasonable basis to believe it can be used to identify an individual. Health information that does not identify an individual and with respect to which there is no reasonable basis to believe that the information can be used to identify an individual is not individually identifiable health information. Sections As summarized in Figure 1, the Privacy Rule provides two methods by which health information can be designated as de-identified.

Figure 1. A covered entity may determine that health information is not individually identifiable health information only if: 1 A person with appropriate knowledge of and experience with generally accepted statistical and scientific principles and methods for rendering information not individually identifiable: i Applying such principles and methods, determines that pdf expert encryption free risk is very small that the information could be used, alone or in combination with other reasonably available information, by an anticipated recipient to identify an individual who is a subject of the information; and ii Documents the methods and results of the analysis that justify such determination; or.

B All geographic subdivisions smaller than a state, including street address, city, county, precinct, ZIP code, and their equivalent geocodes, except pdg the initial three digits of the ZIP code pdf expert encryption free, according to the current publicly available data from the Bureau of the Census: 1 The geographic unit formed by combining all ZIP codes with the same three initial digits contains more than 20, people; and 2 The initial three digits frer a Pdf expert encryption free code for all such geographic units containing 20, or fewer people is changed to C All elements of dates except year for dates that are pdf expert encryption free related to an individual, including birth date, admission date, discharge date, death date, and all ages over 89 and all elements of dates including year indicative of such age, except that such ages and elements may be aggregated into a single pdf expert encryption free of age 90 or older.

De-identified health information created following these methods is no longer protected by the Privacy Rule because it does not fall within the definition of PHI. Of course, de-identification leads to information loss which may limit the usefulness of wxpert resulting http://replace.me/4163.txt information in certain encrgption. As described in the forthcoming pdf expert encryption free, covered entities may wish to select de-identification strategies that minimize such loss.

The implementation specifications further provide direction with respect to re-identificationspecifically the assignment of a unique code pdf expert encryption free the set of de-identified health information to permit re-identification by the covered entity. If a covered entity or business associate successfully undertook enccryption effort to identify the subject of de-identified information it maintained, the health information now related to a specific individual would again be protected by the Privacy Rule, as it would meet the definition of PHI.

Disclosure of a code encrypgion other means of record identification designed to enable coded or otherwise de-identified information to be re-identified is also considered a disclosure of PHI. A covered entity may assign a code or other means of record identification to allow information de-identified under this section to be re-identified by the covered entity, provided that: 1 Derivation.

The code or other means of record identification is not derived from or related to information about the individual and is not otherwise capable of being translated so as to identify the individual; and 2 Security. The covered entity does not use or disclose the code or other means of record identification for any other purpose, and does not disclose the mechanism for re-identification.

The importance of documentation for which values in health data correspond to PHI, as well as the systems that encfyption PHI, for the expeert process cannot be overstated. Esoteric notation, such as acronyms whose meaning are known to only a select few employees of a covered entity, and incomplete description may lead those overseeing a de-identification procedure to unnecessarily redact information or to fail to redact when necessary.

When sufficient documentation is provided, it is straightforward to redact the appropriate fields. See section 3. In the following two sections, we address questions regarding the Expert Determination method Section 2 and the Safe Harbor method Section 3. Pdf expert encryption free notion of expert certification is not unique to the health care field. Professional scientists and statisticians in various fields routinely determine and accordingly mitigate risk prior to sharing data.

The field of statistical disclosure pdf expert encryption free, for instance, has been developed читать больше government statistical agencies, such as the Bureau of the Census, and applied to protect numerous types of data.

There is no specific professional degree or certification program for designating who is an expert at rendering health information посетить страницу источник. Relevant expertise may be gained through various routes of education and experience. Experts may be found in the statistical, mathematical, or other scientific domains. From an enforcement perspective, OCR would review the relevant professional experience and academic or other training of the expert used by the covered entity, as well as actual experience of the expert using health information de-identification methodologies.

The ability of a recipient of information pdf expert encryption free identify an individual i. This is because the risk of identification that has been determined for one particular data set in the context of a specific environment may not be appropriate for the same data set in a different freee or a different data set in the same environment.

This issue is addressed in further depth in Section 2. The Privacy Rule does not explicitly require that an expiration date be attached to the determination that a data set, or the method that generated such a data set, is de-identified information.

However, experts have recognized that technology, social conditions, and the availability of information changes over time. Consequently, certain de-identification practitioners use the approach of time-limited certifications.

In this sense, the expert will assess the expected change of computational capability, as well as access to various data sources, and then determine an appropriate timeframe within which the health information will be considered reasonably protected from identification of an individual.

Information that had previously been de-identified may still be adequately de-identified when the certification limit has been reached. When the certification timeframe reaches its conclusion, it does not imply that the data which has already been disseminated is no longer sufficiently protected in accordance with the de-identification standard.

Covered entities will need to have an expert examine whether future releases of the data to the same recipient e. In such cases, the expert must take care to ensure that the data sets cannot be combined to pdf expert encryption free the protections set in place through pdf expert encryption free mitigation strategy. Of course, the expert must also reduce the risk that the data sets could be combined with prior versions of the de-identified dataset or with other publically available datasets to identify an individual.

For instance, an expert may derive one data set that contains detailed geocodes and generalized aged values e. The expert may certify a covered entity to share both по этой ссылке sets after determining that the two data sets could not be merged to individually identify a patient. This certification may be based on a technical proof regarding the inability to merge such data sets.

Alternatively, the expert also could require additional safeguards through a data use agreement. No single universal solution addresses all privacy and identifiability issues. Rather, a combination of technical and policy procedures are pff applied to the de-identification task. OCR does not encryptioon a particular process for an expert to use to reach a determination that the risk of identification is very small.

However, the Rule does require that the methods and pdf expert encryption free of the analysis that justify the determination be documented and made available to OCR upon request. The following information is meant to provide covered entities with a general understanding of the de-identification process applied by an expert. It does not provide sufficient detail in statistical or scientific methods to serve as a substitute for working with an expert in de-identification.

A general workflow for expert determination is depicted in Figure 2. Stakeholder input suggests that the determination of identification risk can be a process pulpit zdalny w windows 10 home free consists of a series of steps.

First, the expert will evaluate the extent to which the health information can or cannot be identified by the anticipated recipients. Second, the expert often will provide guidance to the covered entity or business associate on which statistical or scientific methods can be applied to the health information to mitigate the anticipated risk.

The expert will then execute such methods as deemed acceptable by the covered entity or business associate data managers, i. Finally, the expert will evaluate the identifiability of the resulting health information to confirm that узнать больше здесь risk is no more than very small when pvf to the anticipated recipients.

Stakeholder input suggests that a process may require several iterations until the expert and data managers agree upon an acceptable solution. Regardless of the process or methods employed, the information must pdf expert encryption free the pdf expert encryption free small risk specification requirement. Figure 2.

Pdf expert encryption free for expert determination of de-Identification. Data managers encry;tion administrators working with an expert to consider the risk of identification of a нажмите для деталей set of health information can look to the principles summarized in Table 1 for assistance.

По ссылке principles should serve as a starting point for reasoning and are pdf expert encryption free meant to serve as a definitive list. In the process, experts are advised to consider how data encrypgion that are available to a recipient of health information e. Linkage is a process that requires the satisfaction of certain conditions. This is because of a second condition, which is the need for a naming pdf expert encryption free source, such as a publicly available voter fere database see Section 2.

Without such a data source, pdf expert encryption free is encrypiton way to definitively pdf expert encryption free the de-identified health information to the corresponding patient.

Finally, for the third condition, we need a mechanism to relate the de-identified and identified data sources. The pdf expert encryption free of a readily available naming data source does not imply that data are sufficiently protected from future identification, but it does indicate that it is harder to re-identify an individual, or group of individuals, given the data sources at hand.

Example Scenario Imagine that a covered entity is considering sharing the information in the table to the left in Figure 3. This table is devoid of frse identifiers, such as personal names and Social Продолжить чтение Numbers. The information in this table is distinguishing, such that each row pdf expert encryption free unique on the combination of demographics i.

Beyond this data, there exists a voter registration data source, which contains personal names, as well as demographics i. Linkage between the records in the tables is possible through the demographics.

Figure 3. Linking two data sources to identity diagnoses. Thus, an important aspect of identification risk assessment is the route by which health information can be linked to naming sources or sensitive knowledge can be inferred.