A 13-month-old child was allegedly raped and physically abused by a police offer, according to a press release from the Pennsylvania State Police.

Penn. Police Officer Accused of Raping and Physically Abusing 13-Month-Old Child

Rihanna debuted a new hair color and wispy bangs on Wednesday, April 17, while hosting an event in London to celebrate the release of the latest Fenty x Puma Creeper Phatty colorways.

Rihanna Debuts Blonder Hair and New Bangs at Fenty x Puma Event — See Her Look!

Sydney Sweeney responded to veteran movie producer Carol Baum, and her recent comments that Sweeney &quot;can’t act.&quot;

Sydney Sweeney Responds to Producer Who Said She ‘Can’t Act’

In honor of TIME&#x27;s 100 Most Influential People issue, Mary J. Blige sung the praises of her friend Taraji P. Henson, sharing why she thinks she stands out in Hollywood and as a person.

Mary J. Blige Says 'Beautiful Friend' Taraji P. Henson's 'Courage Really Sets Her Apart': 'She Is Unapologetically Herself'

Samantha Davis, wife of British character actor Warwick Davis, died in March at age 53, according to a statement.

'Harry Potter' Actor Warwick Davis Mourns Death of Wife Samantha at 53: 'I Miss Her Hugs'

Valerie Bertinelli&#x27;s boyfriend Mike Goodnough has proudly confirmed that they’re together.

Valerie Bertinelli's Boyfriend Mike Goodnough Speaks Out: 'I Just Adore Her'

Megan Fox took to Instagram with a candid photo, revealing how she was repairing her 26-inch blue hair extensions after attending weekend one of Coachella.

Megan Fox Snaps Makeup-Free Selfie in Bra, Boxers and 26-Inch Blue Hair Extensions 'Post-Coachella'

Singer Toni Braxton looks back on her struggle to get a diagnosis for the autoimmune disease lupus — and how it negatively impacted her career.

​​Toni Braxton Says She 'Was Told to Hide' That She Had Lupus

Mariska Hargitay was filming one of the final episodes of season 25 of &#x27;Law &amp; Order: SVU&#x27; when a little girl approached her looking for help, thinking she was a real police officer

Mariska Hargitay, Dressed in Her SVU Gear, Mistaken for Real-Life Police Officer By Young Girl Looking for Her Mom

Katie Holmes embraces warm weather in N.Y.C., plus Zendaya, Zoë Kravitz, Jon Bon Jovi and more. From Hollywood to New York and everywhere in between, see what your favorite stars are up to!

Katie Holmes Embraces Warm Weather in N.Y.C., Plus Zendaya, Zoë Kravitz, Jon Bon Jovi and More

Virtual work experience that allows job seekers to gain experience and makes recruitment more effective, inclusive, fair

Propl

Honey Moons and All Things Come to an End

by Richard Kallos is an Erlang library I wrote for concurrently executing task dependency graphs. It’s intended purpose is to run a set of pre-defined tasks that have a partial ordering between them. In this post, I explain why I wrote wrek, what it can be used for, and how to use it. Wrek Motivation Wrek emerged as the result of two distinct forces. First, my amateurish enjoyment of graph theory made me try to see graphs wherever I could, laying the conceptual foundation for this library. Second, I realized that a project I was working on at Adgear would benefit from such a library, causing me to finally start writing Wrek. Conceptual The graph is a pervasive data structure in computing. When I learned about graph algorithms in school, I was amazed by their broad applications. Graphs play essential roles in compilers and build systems. Various graph algorithms form the backbone of how we communicate with each other over the internet. Our everyday lives tend to be filled with lists. We have to-do lists, shopping lists, recipes, checklists, instructions, and much, much more. One day, I realized that some of these lists are deceiving. Some of these lists are actually graphs hiding in list’s clothing; these lists are of . Two of the more obvious cases of this are to-do lists and recipes. You can’t send a letter that you haven’t written yet, nor can you cook spaghetti if you haven’t boiled a pot of water. topological orderings directed acyclic graphs Once the sneaky graphs were discovered, I spent some time thinking about how to benefit from treating various lists like the DAGs that they secretly are. The clearest analogies between these lists and DAGs were to-do lists and recipes. These very closely resembled . Unlike in their list representation, these dependency graphs show which vertices (individual tasks) can be executed concurrently. Sometimes this is obvious (e.g: I can chop vegetables while I wait for the pot of water to boil! I can begin preparing a second baking sheet of cookies while the first batch is in the oven!), but I had my hopes that the act of reformulating lists as dependency graphs could expose more opportunities for concurrency. dependency graphs Boil water -- Add pasta -- Cook pasta --.  
                                                     \\ Purée tomatoes --.                                      \\                                      \Chop vegetables -- Combine in saucepan -- Simmer sauce -- Combine pasta and sauce -- Serve/Add spices --' Edges between vertices in the above graph express a partial ordering. Vertices with no path between them can be executed concurrently. The relationship between vertices in the graph reflects the truth in the kitchen. We can cook the pasta while our sauce is simmering. It doesn’t matter whether we chop vegetables or purée tomatoes first; they both need to be done if we’re going to make any sauce. Despite my best efforts, I am still a disaster in the kitchen. As a means of changing this inconvenient fact, I thought it would be fun to try representing recipes as directed graphs, with extra data like how long each step can be expected to take. This sat in my list of ‘someday projects’ for a long time, and I was only reminded of it when I begin to think about a project I was working on at $JOB. Practical One of the projects I accomplished last year at Adgear was removing an expensive computation that was taking place on each of our already maxed-out edge servers, and replaced it with a system that performed the expensive computation on a single machine, then distributed the result. The system worked when nobody touched it, but it was the programming equivalent of twigs and duct tape; cron jobs and shell scripts. This system continued to be painful to use, and more examples of expensive computations being done on CPU-starved machines were cropping up. At this point, it made sense start writing a more robust system. These expensive computations decomposed nicely into lists of steps to be performed. Fetch this data, transform it, transform it some more, send some of the data to this group of servers, send this other data to some other group of servers. Shell scripts are pretty good at encoding these pipelines, so it was an acceptable choice at the time of implementation. After a while, it dawned on me that these lists of steps were not really lists; they were dependency graphs. I tried to expose the latent concurrency in the shell scripts by spicing them up with some background jobs and waitpid , but it was decided that it would make more sense to switch to Erlang and benefit from all that OTP has to offer. Let’s Get ‘Wrek’ ed (I’m sorry. I couldn’t resist.) Wrek accepts dependency graphs like the above spaghetti recipe as input, and executes each vertex. The nature of concurrently executing actions as soon as they are able to execute is to any problem that can be represented by a dependency graph. The structure of a dependency graph, as well as the tasks involved in each of the graph’s vertices are to the user’s wishes. Following the same generic/specific split as OTP; the generic portion of this class of problems is solved by and modules. The specific portion is provided by the user in the form of an Erlang map describing each vertex in the graph, and a set of callback modules that implement the behaviour. generic specific wrek wrek_vert wrek_vert The behaviour consists of a single callback , where the first argument is a list of arguments to be sent to the callback function, and the second argument is the ID of a process which can provide information generated by other vertices. The expected result of this callback function is either wrek_vert run/2 or . If the callback function succeeds, will be taken by wrek and made available to other processes. If the callback function crashes or returns an error, the entire graph will be shut down. {ok, Any :: any()} {error, Reason :: any()} Any wrek_vert Making Erlang Pasta Following the contrived example above, let’s set about using wrek to make pasta. Of course, our program won’t really make pasta, but it’s output ought to fool somebody. Looking at the above graph, each step seems to do one of three things: Add an ingredient Combine ingredients in a vessel Do something to ingredients in a vessel Let’s go ahead write some s for each of those actions. If you don’t feel like following along in a text editor, the full code can be found . wrek_vert here -module(cook_add). -behaviour(wrek_vert).-export([run/2]). run([Ingredient, Quantity], _Pid) ->io:format(“adding ~s. amount: ~s.~n”, [Ingredient, Quantity]),{ok, #{added => [{Ingredient, Quantity}]}}. That’s all for . It prints a message, then produces a map with a key added whose value is a proplist with a single pair. cook_add -module(cook_heat). -behaviour(wrek_vert).-export([run/2]). run([Verb, Noun], _Pid) ->io:format("~ping ~p.~n", [Verb, Noun]),{ok, #{}}. is also pretty short. It’s also very abstract. It could be used to print a message about ing any , not just cooking ingredients! cook_heat Verb Noun Our final callback module is a little longer, because it does a little bit more than printing a message. -module(cook_combine). -behaviour(wrek_vert).-export([run/2]). run([Ingredients, Vessel], Pid) ->Fun = fun(Step, Acc) ->Stuff = wrek_vert:get(Pid, Step, added),io:format("combining ~p with ~p in ~p.~n", [Stuff, Acc, Vessel]),Stuff ++ Accend,Stuff = lists:foldl(Fun, [], Ingredients),io:format("~p now contains: ~p.~n", [Vessel, Stuff]),{ok, #{added => Stuff}}. is expected to be a list of vertex names. We finally use our parent process’s Pid as an argument to . This lets us consume the data produced by the callback module. After combining everything, we returns a new collection of ingredients. Ingredients wrek_vert:get/3 cook_add Alright! We’re nearly done describing the specific portion of our problem! The last step is to represent our dependency graph in terms of these callback modules and the arguments we want to pass to them. -module(wrek_example). -export([make_pasta/0]). make_pasta() ->application:ensure_all_started(wrek),Graph = #{tomatoes => #{module => cook_add,args => ["pureed tomatoes", "1 can"],deps => []},vegetables => #{module => cook_add,args => ["chopped vegetables", "lots"],deps => []},spices => #{module => cook_add,args => ["spices", "to taste"],deps => []},saucepan => #{module => cook_combine,args => [[tomatoes, vegetables, spices], saucepan],deps => [tomatoes, vegetables, spices]},simmer_sauce => #{module => cook_heat,args => [simmer, sauce],deps => [saucepan]},boil_water => #{module => cook_heat,args => [boil, water],deps => []},add_pasta => #{module => cook_add,args => ["pasta", "1 handful"],deps => [boil_water]},cook_pasta => #{module => cook_heat,args => [cook, pasta],deps => [add_pasta]},mix_pasta_with_sauce => #{module => cook_combine,args => [[saucepan, add_pasta], saucepan],deps => [simmer_sauce, cook_pasta]}},wrek:start(Graph). That’s an eyeful! What we’ve done here is created an Erlang map whose keys represent the names of vertices in our original dependency graph, and whose values are maps that specify a callback module, arguments to pass to the callback module, as well as any dependencies the vertex may have. I congratulate those of you who noticed that we are never straining the pasta; I did confess to being a disaster in the kitchen. I promise I learned my lesson. Alright, we’re done coding! Let’s start up a shell and make some pasta! Read the rest of this blog post on codesync.global Code BEAM SF 2018: 15–16 March 2018 Join Richard Kallos, developer at AdGear, at CodeBEAM SF where he will be giving a talk on . wrek Originally published at codesync.global .

Introducing Wrek — A Miniature Erlang Graph Engine

10 LeetCode Patterns to Solve 1000 LeetCode Problems

Software development is mostly not actually writing software. Sometimes, it’s debugging a critical issue that cannot wait and is beyond the abilities of first-line support. Keep reading to learn what tools you can and should employ when dealing with long-running hard-to-fix problems. You may be guarded by countless levels of the corporate hierarchy, but eventually, you will either be asked to debug a production issue or you will be in a job that will require it. This article is aimed primarily at software engineers but also QAs, managers, leads, and solution engineers. How Does an Issue Reach You? You get an invite to a call, and you’re tagged in a Jira ticket, on Slack, or DM’ed. Ok, cool. Someone is asking you to drop a feature you’ve been working on, switch context, and help. Annoying, I know. Give yourself 90 seconds to grieve and move on. If someone is asking you for urgent help with a production issue, they mean it. Before you start, make sure your direct superior/manager/leas knows you are switching priorities. And if you start investigating, make sure everyone knows it, so other people are not wasting time doing the same. As you’ll see, comms are the key. Communication Before we get to any technical tips, let’s start with communication. I’ll mention some tools, some should be a part of the system already in place, automatic procedures. If they’re not, you should introduce them. Incident Slack Channel If you’re reading this in the early XXI century, you have a company chat app. Make sure there is a channel where all the people who can help with the problem or need information about it have a place to talk. Invite people, and ask them to add anyone interested. Spam this channel with progress updates. Example name: inc-2023-01-04-sign-up-down . It can also include a ticket number instead of a date. Cadency Depending on the criticality of the issue, post summaries of what’s going on. If it’s an urgent issue that is classified as P1 (priority 1, critical system down, significant financial impact), you’re likely to post summaries each hour or two.


If it’s a long-running issue with lower priority, begin the day with a plan for what’s next and close the day with a progress summary. Message Template Here’s what I use: Summary of [name/ticket] incident investigation as of 4PM, Jan 18th
Resolved: yes/no/partially
∑ Brief summary

we know that the cause of the issue is: …
fix by … didn’t work, we’re trying …., estimated test at …
replication is hard, streamlining it

⏭️ Next steps

[…]

🧠 Other notes

[ideas and resources] These updates may not get reactions but many people will read them and quietly thank you for your thoroughness. If you are a recipient of those, like them, react with 👀 emoji, or whatever. Feedback is always good. Forward daily updates on the main channel for issue discussions or on the team channel, so people less involved but still interested or able to help can see them. Escalation Whenever you are stuck - flag it and ask for help. You have an important task, it’s not worth being quiet. If your direct manager isn’t listening - try their manager. When asking people for help, state how urgent is the question and when you need it done. Don’t sit alone on an unresolved issue. You work with other specialists, present your idea to someone, and get feedback. Getting Essential Information There are a few types of information you are going to need. Apart from what comes with your programming experience. How to reproduce the issue? Steps taken, environment details.


Input and output data - input that is causing the issue, the erroneous output, the right output.


Logs with real-world examples of the issue in the wild.


System knowledge - think knowing the part of the product in question, documentation.


The initial estimate of the impact on customers. If you lack any of these at the start, work hard to get them first. I’ve been asked to work on a bug that no one could reproduce a few times. Customers that encountered it, didn’t have time to jump on a call. Imagine how hard it was to work on such an elusive problem. You are OK to push back in these situations. Make sure to be collaborative with your customer-facing colleagues who will help gather this information. If you can, tell them exactly what you need. You can use the list above. Regarding point 5, estimating impact, it will need to be done properly either by you or someone else in the end. It will be needed for proper customer communication. Working on the Issue Finding and fixing a bug is a little bit like doing science. You are likely going to follow a process like this: Construct a hypothesis


Test it by doing experiments


Analyze your data and draw a conclusion


Come up with a fix


Test the fix


If it doesn’t work → repeat Make sure to write down your current hypothesis and log any additional ideas. Keep track of what you checked and what you didn’t. If the work will end up taking a long time or you’ll be forced to hand it over to someone else, these notes will be extremely useful. In general, maintain a log of what you experimented with. This will help you avoid running in circles and provide good updates for the team. Create Tools! Whenever an experiment requires manual labor and you have to do it multiple times, create small tools to help you do it. As an example, if experimenting requires decrypting some values stored in your system, create a piece of code that will do that en masse instead of using online tools and console programs all the time. If you need to parse some files and you are opening tens of them and looking for clues - create a small JS website that will help you extract the right information. Mini-tools will help you move faster and you won’t need to repeat the same work. Of course, make them only when it is necessary. At many projects of mine, these tools later became a part of regular testing and development processes. After the Incident Your company, likely, will have a process, usually, it is called RCA - Root Cause Analysis. Someone should schedule a meeting with all of the people involved in the work and prepare a document, later distributed to everyone interested. On top of this note, relevant work preventing such incidents in the future should be scheduled. The point of the whole exercise is to learn from mistakes. This meeting should not be geared towards blaming individuals. It should point out where the processes failed. When everything is fixed, make sure everyone knows it is the case. If you spent some extra hours working on it, ask to be compensated or to be able to work less in the coming days. Make sure to note down what you did and how it helped the company and use it in your next evaluation meeting. Summary If you have dealt with production issues at your job, this guide probably sounds familiar. If you are yet to be asked to fix something, this article gives you the proper frame of mind. Remember: communication is the key, don’t neglect it


fixing a bug is like doing scientific research: form and test hypotheses, note everything down


create tools that will help you with manual work


take and give credit, forget about the blame What are your experiences with troubleshooting live issues? Subscribe to my profile by filling in your email address on the left, and be up-to-date with my articles! Don't forget to follow me on Twitter @ horosin, and subscribe to my blog’s newsletterfor more tips and insights! If you don't have Twitter, you can also follow me on LinkedIn. Software development is mostly not actually writing software. Sometimes, it’s debugging a critical issue that cannot wait and is beyond the abilities of first-line support. Keep reading to learn what tools you can and should employ when dealing with long-running hard-to-fix problems. You may be guarded by countless levels of the corporate hierarchy, but eventually, you will either be asked to debug a production issue or you will be in a job that will require it. This article is aimed primarily at software engineers but also QAs, managers, leads, and solution engineers. How Does an Issue Reach You? You get an invite to a call, and you’re tagged in a Jira ticket, on Slack, or DM’ed. Ok, cool. Someone is asking you to drop a feature you’ve been working on, switch context, and help. Annoying, I know. Give yourself 90 seconds to grieve and move on. If someone is asking you for urgent help with a production issue, they mean it. Before you start, make sure your direct superior/manager/leas knows you are switching priorities. And if you start investigating, make sure everyone knows it, so other people are not wasting time doing the same. As you’ll see, comms are the key. Communication Before we get to any technical tips, let’s start with communication. I’ll mention some tools, some should be a part of the system already in place, automatic procedures. If they’re not, you should introduce them. Incident Slack Channel If you’re reading this in the early XXI century, you have a company chat app. Make sure there is a channel where all the people who can help with the problem or need information about it have a place to talk. Invite people, and ask them to add anyone interested. Spam this channel with progress updates. Example name: inc-2023-01-04-sign-up-down . It can also include a ticket number instead of a date. inc-2023-01-04-sign-up-down Cadency Depending on the criticality of the issue, post summaries of what’s going on. If it’s an urgent issue that is classified as P1 (priority 1, critical system down, significant financial impact), you’re likely to post summaries each hour or two. If it’s a long-running issue with lower priority, begin the day with a plan for what’s next and close the day with a progress summary. If it’s an urgent issue that is classified as P1 (priority 1, critical system down, significant financial impact), you’re likely to post summaries each hour or two. If it’s an urgent issue that is classified as P1 (priority 1, critical system down, significant financial impact), you’re likely to post summaries each hour or two. If it’s a long-running issue with lower priority, begin the day with a plan for what’s next and close the day with a progress summary. If it’s a long-running issue with lower priority, begin the day with a plan for what’s next and close the day with a progress summary. Message Template Here’s what I use: Summary of [name/ticket] incident investigation as of 4PM, Jan 18th Resolved: yes/no/partially ∑ Brief summary we know that the cause of the issue is: …
fix by … didn’t work, we’re trying …., estimated test at …
replication is hard, streamlining it ⏭️ Next steps […] 🧠 Other notes [ideas and resources] Summary of [name/ticket] incident investigation as of 4PM, Jan 18th Summary of [name/ticket] incident investigation as of 4PM, Jan 18th Summary of [name/ticket] incident investigation as of 4PM, Jan 18th Resolved: yes/no/partially Resolved: yes/no/partially ∑ Brief summary ∑ Brief summary ∑ Brief summary we know that the cause of the issue is: … fix by … didn’t work, we’re trying …., estimated test at … replication is hard, streamlining it we know that the cause of the issue is: … we know that the cause of the issue is: … fix by … didn’t work, we’re trying …., estimated test at … fix by … didn’t work, we’re trying …., estimated test at … replication is hard, streamlining it replication is hard, streamlining it ⏭️ Next steps ⏭️ Next steps Next steps […] […] […] 🧠 Other notes 🧠 Other notes Other notes [ideas and resources] [ideas and resources] [ideas and resources] These updates may not get reactions but many people will read them and quietly thank you for your thoroughness. If you are a recipient of those, like them, react with 👀 emoji, or whatever. Feedback is always good. Forward daily updates on the main channel for issue discussions or on the team channel, so people less involved but still interested or able to help can see them. Escalation Whenever you are stuck - flag it and ask for help. You have an important task, it’s not worth being quiet. If your direct manager isn’t listening - try their manager. When asking people for help, state how urgent is the question and when you need it done. Don’t sit alone on an unresolved issue. You work with other specialists, present your idea to someone, and get feedback. Getting Essential Information There are a few types of information you are going to need. Apart from what comes with your programming experience. How to reproduce the issue? Steps taken, environment details. Input and output data - input that is causing the issue, the erroneous output, the right output. Logs with real-world examples of the issue in the wild. System knowledge - think knowing the part of the product in question, documentation. The initial estimate of the impact on customers. How to reproduce the issue? Steps taken, environment details. How to reproduce the issue? Steps taken, environment details. Input and output data - input that is causing the issue, the erroneous output, the right output. Input and output data - input that is causing the issue, the erroneous output, the right output. Logs with real-world examples of the issue in the wild. Logs with real-world examples of the issue in the wild. System knowledge - think knowing the part of the product in question, documentation. System knowledge - think knowing the part of the product in question, documentation. The initial estimate of the impact on customers. The initial estimate of the impact on customers. If you lack any of these at the start, work hard to get them first. I’ve been asked to work on a bug that no one could reproduce a few times. Customers that encountered it, didn’t have time to jump on a call. Imagine how hard it was to work on such an elusive problem. You are OK to push back in these situations. Make sure to be collaborative with your customer-facing colleagues who will help gather this information. If you can, tell them exactly what you need. You can use the list above. Regarding point 5, estimating impact, it will need to be done properly either by you or someone else in the end. It will be needed for proper customer communication. Working on the Issue Finding and fixing a bug is a little bit like doing science. You are likely going to follow a process like this: Construct a hypothesis Test it by doing experiments Analyze your data and draw a conclusion Come up with a fix Test the fix If it doesn’t work → repeat Construct a hypothesis Construct a hypothesis Test it by doing experiments Test it by doing experiments Analyze your data and draw a conclusion Analyze your data and draw a conclusion Come up with a fix Come up with a fix Test the fix Test the fix If it doesn’t work → repeat If it doesn’t work → repeat Make sure to write down your current hypothesis and log any additional ideas. Keep track of what you checked and what you didn’t. If the work will end up taking a long time or you’ll be forced to hand it over to someone else, these notes will be extremely useful. In general, maintain a log of what you experimented with. This will help you avoid running in circles and provide good updates for the team. Create Tools! Whenever an experiment requires manual labor and you have to do it multiple times, create small tools to help you do it. As an example, if experimenting requires decrypting some values stored in your system, create a piece of code that will do that en masse instead of using online tools and console programs all the time. If you need to parse some files and you are opening tens of them and looking for clues - create a small JS website that will help you extract the right information. Mini-tools will help you move faster and you won’t need to repeat the same work. Of course, make them only when it is necessary. At many projects of mine, these tools later became a part of regular testing and development processes. After the Incident Your company, likely, will have a process, usually, it is called RCA - Root Cause Analysis. Someone should schedule a meeting with all of the people involved in the work and prepare a document, later distributed to everyone interested. On top of this note, relevant work preventing such incidents in the future should be scheduled. The point of the whole exercise is to learn from mistakes. This meeting should not be geared towards blaming individuals. It should point out where the processes failed. When everything is fixed, make sure everyone knows it is the case. If you spent some extra hours working on it, ask to be compensated or to be able to work less in the coming days. Make sure to note down what you did and how it helped the company and use it in your next evaluation meeting. Summary If you have dealt with production issues at your job, this guide probably sounds familiar. If you are yet to be asked to fix something, this article gives you the proper frame of mind. Remember: communication is the key, don’t neglect it fixing a bug is like doing scientific research: form and test hypotheses, note everything down create tools that will help you with manual work take and give credit, forget about the blame communication is the key, don’t neglect it communication is the key, don’t neglect it fixing a bug is like doing scientific research: form and test hypotheses, note everything down fixing a bug is like doing scientific research: form and test hypotheses, note everything down create tools that will help you with manual work create tools that will help you with manual work take and give credit, forget about the blame take and give credit, forget about the blame What are your experiences with troubleshooting live issues? Subscribe to my profile by filling in your email address on the left, and be up-to-date with my articles! Don't forget to follow me on Twitter @ horosin , and subscribe to my blog’s newsletter for more tips and insights! @ horosin newsletter If you don't have Twitter, you can also follow me on LinkedIn . LinkedIn

How to Debug and Solve a Big Production Problem With SaaS

SHERIDAN, United States, July 24th, 2024/Chainwire/--Proptokenmarket, a dynamic newcomer to the real estate and blockchain landscape, proudly unveils its global Real Estate Token Directory. This groundbreaking platform is the first to provide a third-party directory for Real Estate Tokens, offering a fresh, user-friendly approach to discovering and engaging with tokenized real estate assets from various issuers worldwide. Key Features of Proptokenmarket's Real Estate Token Directory: 1.      Global Tokenized Real Estate Assets: Exploring a curated selection of tokenized real estate assets, from single-family gems to luxury apartments on exotic islands and commercial opportunities worldwide. 2.      Data-Driven Decision-Making: Accessing comprehensive property information, token metrics, historical performance data, and market analytics to make informed investment decisions. 3.      Extensive Learning Opportunities: Proptokenmarket offers a wealth of resources for both beginners and seasoned investors to learn about real estate tokens. Users can access educational articles, tutorials, and guides that cover everything from the basics of real estate tokenization to advanced blockchain knowledge. A dedicated news feed summarizes the latest developments and trends in the real estate token market, ensuring users stay informed and educated. 4.      User-Centric Design: Navigating with ease through an intuitive and visually appealing interface, designed for both seasoned investors and newcomers. 5.      Responsive Support: Proptokenmarket is committed to providing exceptional customer support, guiding users through their investment journey and promptly addressing inquiries. Florian Schick, founder of Proptokenmarket, commented, "At Proptokenmarket, we're thrilled to introduce our Real Estate Token Directory. Our platform is designed to democratize real estate investment, allowing users to easily explore real estate tokens globally and find related platforms and issuers. Additionally, Proptokenmarket offers valuable information on real estate tokenization, catering to all knowledge levels.A dedicated news feed summarizing exciting and relevant news topics completes our platform." Users can discover the future of real estate investment by visiting https://proptokenmarket.com. About Proptokenmarket Proptokenmarket is a forward-thinking startup dedicated to reshaping the real estate token investment landscape by providing excellent transparency, accessibility and innovative solutions through a comprehensive global perspective on the real estate token market. Their mission is to provide transparency, security, and accessibility to investors worldwide. LinkedIn Contact Founder Florian Schick Proptokenmarket LLC florian@proptokenmarket.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. SHERIDAN, United States, July 24th, 2024/Chainwire/--Proptokenmarket, a dynamic newcomer to the real estate and blockchain landscape, proudly unveils its global Real Estate Token Directory. This groundbreaking platform is the first to provide a third-party directory for Real Estate Tokens, offering a fresh, user-friendly approach to discovering and engaging with tokenized real estate assets from various issuers worldwide. Key Features of Proptokenmarket's Real Estate Token Directory: 1.      Global Tokenized Real Estate Assets: Exploring a curated selection of tokenized real estate assets, from single-family gems to luxury apartments on exotic islands and commercial opportunities worldwide. 2.      Data-Driven Decision-Making: Accessing comprehensive property information, token metrics, historical performance data, and market analytics to make informed investment decisions. 3.      Extensive Learning Opportunities: Proptokenmarket offers a wealth of resources for both beginners and seasoned investors to learn about real estate tokens. Users can access educational articles, tutorials, and guides that cover everything from the basics of real estate tokenization to advanced blockchain knowledge. A dedicated news feed summarizes the latest developments and trends in the real estate token market, ensuring users stay informed and educated. 4.      User-Centric Design: Navigating with ease through an intuitive and visually appealing interface, designed for both seasoned investors and newcomers. 5.      Responsive Support: Proptokenmarket is committed to providing exceptional customer support, guiding users through their investment journey and promptly addressing inquiries. Florian Schick, founder of Proptokenmarket, commented, "At Proptokenmarket, we're thrilled to introduce our Real Estate Token Directory. Our platform is designed to democratize real estate investment, allowing users to easily explore real estate tokens globally and find related platforms and issuers. Additionally, Proptokenmarket offers valuable information on real estate tokenization, catering to all knowledge levels. A dedicated news feed summarizing exciting and relevant news topics completes our platform." Florian Schick, founder of Proptokenmarket, commented, "At Proptokenmarket, we're thrilled to introduce our Real Estate Token Directory. Our platform is designed to democratize real estate investment, allowing users to easily explore real estate tokens globally and find related platforms and issuers. Additionally, Proptokenmarket offers valuable information on real estate tokenization, catering to all knowledge levels. A dedicated news feed summarizing exciting and relevant news topics completes our platform." Users can discover the future of real estate investment by visiting https://proptokenmarket.com . https://proptokenmarket.com https://proptokenmarket.com About Proptokenmarket Proptokenmarket is a forward-thinking startup dedicated to reshaping the real estate token investment landscape by providing excellent transparency, accessibility and innovative solutions through a comprehensive global perspective on the real estate token market. Their mission is to provide transparency, security, and accessibility to investors worldwide. Proptokenmarket Proptokenmarket LinkedIn LinkedIn LinkedIn Contact Founder Florian Schick Proptokenmarket LLC florian@proptokenmarket.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Introducing Proptokenmarket: Pioneering the Future with the “First Real Estate Token Directory”

Authors:
(1) Xiaofan Yu, University of California San Diego, La Jolla, California, USA (x1yu@ucsd.edu);
(2) Anthony Thomas, University of California San Diego, La Jolla, California, USA (ahthomas@ucsd.edu);
(3) Ivannia Gomez Moreno, CETYS University, Campus Tijuana, Tijuana, Mexico (ivannia.gomez@cetys.edu.mx);
(4) Louis Gutierrez, University of California San Diego, La Jolla, California, USA (l8gutierrez@ucsd.edu);
(5) Tajana Šimunić Rosing, University of California San Diego, La Jolla, USA (tajana@ucsd.edu). Table of Links Abstract and 1. Introduction 2 Related Work 3 Background on HDC 4 Problem Definition 5 LifeDH 6 Variants of LifeHD 7 Evaluation of LifeHD 8 Evaluation of LifeHD semi and LifeHDa 9 Discussions and Future Works 10 Conclusion, Acknowledgments, and References 4 PROBLEM DEFINITION Before diving into our method, we first rigorously formulate the unsupervised lifelong learning problem using streaming sources, driven by real-world IoT applications. Streaming Data. To represent continuously changing environment, we assume a well-known class-incremental model in lifelong learning, in which new classes emerge in a sequential manner [46]. We also allow data distribution shift within one class. This setting models a scenario in which a device is continuously sampling data while the surrounding environment may change implicitly over time, e.g., the self-driving vehicle as shown in Fig. 1. We require that all samples appear only once (i.e., single-pass streams). Learning Protocol. Our goal is to build a classification algorithm that maps X → Y. For evaluation, we use the common evaluation protocol in state-of-the-art lifelong learning works [13, 14, 54], in which we construct an iid dataset E = {(𝑋𝑘 , 𝑦𝑘 )} for periodic testing, by sampling labeled examples from each class in a manner that preserves the overall (im)balance between the classes. Note, that even when one class has not appeared in the training data stream, it is always included in E. Hence E is a global view of all classes that can potentially exist in the environment. Unsupervised Clustering Accuracy. Since we do not give class labels or the total number of classes during training, the predicted label can be different from the ground-truth label. Therefore, for evaluation metric, we cannot adopt the simple prediction accuracy that requires exact label matching. Instead, we employ a widely used clustering metric known as unsupervised clustering accuracy (ACC) [63], which mirrors the conventional accuracy evaluation but within an unsupervised context. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) Xiaofan Yu, University of California San Diego, La Jolla, California, USA (x1yu@ucsd.edu); (2) Anthony Thomas, University of California San Diego, La Jolla, California, USA (ahthomas@ucsd.edu); (3) Ivannia Gomez Moreno, CETYS University, Campus Tijuana, Tijuana, Mexico (ivannia.gomez@cetys.edu.mx); (4) Louis Gutierrez, University of California San Diego, La Jolla, California, USA (l8gutierrez@ucsd.edu); (5) Tajana Šimunić Rosing, University of California San Diego, La Jolla, USA (tajana@ucsd.edu). Authors: Authors: (1) Xiaofan Yu, University of California San Diego, La Jolla, California, USA (x1yu@ucsd.edu); (2) Anthony Thomas, University of California San Diego, La Jolla, California, USA (ahthomas@ucsd.edu); (3) Ivannia Gomez Moreno, CETYS University, Campus Tijuana, Tijuana, Mexico (ivannia.gomez@cetys.edu.mx); (4) Louis Gutierrez, University of California San Diego, La Jolla, California, USA (l8gutierrez@ucsd.edu); (5) Tajana Šimunić Rosing, University of California San Diego, La Jolla, USA (tajana@ucsd.edu). Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2 Related Work 2 Related Work 3 Background on HDC 3 Background on HDC 4 Problem Definition 4 Problem Definition 5 LifeDH 5 LifeDH 6 Variants of LifeHD 6 Variants of LifeHD 7 Evaluation of LifeHD 7 Evaluation of LifeHD 8 Evaluation of LifeHD semi and LifeHDa 8 Evaluation of LifeHD semi and LifeHDa 9 Discussions and Future Works 9 Discussions and Future Works 10 Conclusion, Acknowledgments, and References 10 Conclusion, Acknowledgments, and References 4 PROBLEM DEFINITION Before diving into our method, we first rigorously formulate the unsupervised lifelong learning problem using streaming sources, driven by real-world IoT applications. Streaming Data. To represent continuously changing environment, we assume a well-known class-incremental model in lifelong learning, in which new classes emerge in a sequential manner [46]. We also allow data distribution shift within one class. This setting models a scenario in which a device is continuously sampling data while the surrounding environment may change implicitly over time, e.g., the self-driving vehicle as shown in Fig. 1. We require that all samples appear only once (i.e., single-pass streams). Streaming Data. Learning Protocol. Our goal is to build a classification algorithm that maps X → Y. For evaluation, we use the common evaluation protocol in state-of-the-art lifelong learning works [13, 14, 54], in which we construct an iid dataset E = {(𝑋𝑘 , 𝑦𝑘 )} for periodic testing, by sampling labeled examples from each class in a manner that preserves the overall (im)balance between the classes. Note, that even when one class has not appeared in the training data stream, it is always included in E. Hence E is a global view of all classes that can potentially exist in the environment. Learning Protocol. Unsupervised Clustering Accuracy. Since we do not give class labels or the total number of classes during training, the predicted label can be different from the ground-truth label. Therefore, for evaluation metric, we cannot adopt the simple prediction accuracy that requires exact label matching. Instead, we employ a widely used clustering metric known as unsupervised clustering accuracy (ACC) [63], which mirrors the conventional accuracy evaluation but within an unsupervised context. Unsupervised Clustering Accuracy. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. available on arxiv

Lifelong Intelligence Beyond the Edge using Hyperdimensional Computing: Problem Definition

Looks Like Craig Wright’s Dissertation Proposal Took a Time Machine to 2019

DUBAI, 22 July 2024 - Propchain has announced a strategic advancement in the tokenized real estate sector with the launch of Propchain DAO, marking the first Real World Assets (RWA) project to launch a DAO in the tokenized real estate sector. This initiative sets a new benchmark for transparency, inclusivity, and community-driven governance not only for Propchain, but within the rapidly growing RWA industry as well. Propchain DAO: Guiding the Future of Tokenized Real Estate Propchain DAO plays a crucial role in steering the decision-making processes of the Propchain Foundation. Key areas of focus include: Utility Token Management: Ensuring effective use and integration of the $PROPC token within the ecosystem.
Ecosystem Development: Enabling growth and innovation within the Propchain network.
Treasury Oversight: Managing funds to support various initiatives and maintain financial stability.
Strategic Partnerships: Forming collaborations to expand Propchain’s reach and capabilities globally.
Grant Support: Providing financial backing for projects aligned with Propchain's mission.
Global Initiatives: Leading efforts to promote Propchain's vision on an international scale. Empowering the Community through Governance The DAO's Governance Protocol empowers community engagement through a token-based voting system, ensuring that decisions are decentralized and reflect collective preferences. This approach promotes transparency and inclusivity within Propchain's RWA-focused ecosystem. Key components include: Token-Based Voting: Allowing $PROPC holders to participate in governance decisions.
Proposal Vetting: Initial review by the Foundation's core contributors to ensure relevance and feasibility.
Secure Voting Mechanism: Voting power proportional to token holdings. Commitment to Inclusivity The governance participation in Propchain DAO is exclusively for $PROPC holders, reinforcing Propchain's commitment to building a global, permissionless, and inclusive community. This ensures that community members have a direct influence on the development and future direction of the Propchain ecosystem. Till date, the Propchain DAO has successfully witnessed the full-cycle completion of 2 proposals, demonstrating the community's active involvement in governance. This further drives Propchain a step ahead in leading the digitization of the global real estate industry. About Propchain Propchain leads the way in real estate investment platforms, placing consumer needs at the forefront by providing effortless access to tokenized assets and a user-friendly digital interface for asset management. It aims to revolutionize the real estate industry through the widespread adoption of blockchain technology, facilitating improved market dynamics, transparency, and long-term sustainability. Propchain's journey is marked by significant milestones, strategic focus, and innovative real estate strategies. With its dedication to digitally empowering the real estate value chain through investing and strategic positioning in the global market, Propchain is set to redefine the real estate investment landscape and continue its path of success. This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here. DUBAI, 22 July 2024 - Propchain has announced a strategic advancement in the tokenized real estate sector with the launch of Propchain DAO, marking the first Real World Assets (RWA) project to launch a DAO in the tokenized real estate sector. This initiative sets a new benchmark for transparency, inclusivity, and community-driven governance not only for Propchain, but within the rapidly growing RWA industry as well. Propchain DAO: Guiding the Future of Tokenized Real Estate Propchain DAO plays a crucial role in steering the decision-making processes of the Propchain Foundation. Key areas of focus include: Utility Token Management: Ensuring effective use and integration of the $PROPC token within the ecosystem. Ecosystem Development: Enabling growth and innovation within the Propchain network. Treasury Oversight: Managing funds to support various initiatives and maintain financial stability. Strategic Partnerships: Forming collaborations to expand Propchain’s reach and capabilities globally. Grant Support: Providing financial backing for projects aligned with Propchain's mission. Global Initiatives: Leading efforts to promote Propchain's vision on an international scale. Utility Token Management: Ensuring effective use and integration of the $PROPC token within the ecosystem. Ecosystem Development: Enabling growth and innovation within the Propchain network. Treasury Oversight: Managing funds to support various initiatives and maintain financial stability. Strategic Partnerships: Forming collaborations to expand Propchain’s reach and capabilities globally. Grant Support: Providing financial backing for projects aligned with Propchain's mission. Global Initiatives: Leading efforts to promote Propchain's vision on an international scale. Empowering the Community through Governance The DAO's Governance Protocol empowers community engagement through a token-based voting system, ensuring that decisions are decentralized and reflect collective preferences. This approach promotes transparency and inclusivity within Propchain's RWA-focused ecosystem. Key components include: Token-Based Voting: Allowing $PROPC holders to participate in governance decisions. Proposal Vetting: Initial review by the Foundation's core contributors to ensure relevance and feasibility. Secure Voting Mechanism: Voting power proportional to token holdings. Token-Based Voting: Allowing $PROPC holders to participate in governance decisions. Proposal Vetting: Initial review by the Foundation's core contributors to ensure relevance and feasibility. Secure Voting Mechanism: Voting power proportional to token holdings. Commitment to Inclusivity The governance participation in Propchain DAO is exclusively for $PROPC holders, reinforcing Propchain's commitment to building a global, permissionless, and inclusive community. This ensures that community members have a direct influence on the development and future direction of the Propchain ecosystem. Till date, the Propchain DAO has successfully witnessed the full-cycle completion of 2 proposals, demonstrating the community's active involvement in governance. This further drives Propchain a step ahead in leading the digitization of the global real estate industry. About Propchain Propchain leads the way in real estate investment platforms, placing consumer needs at the forefront by providing effortless access to tokenized assets and a user-friendly digital interface for asset management. Propchain Propchain It aims to revolutionize the real estate industry through the widespread adoption of blockchain technology, facilitating improved market dynamics, transparency, and long-term sustainability. Propchain's journey is marked by significant milestones, strategic focus, and innovative real estate strategies. With its dedication to digitally empowering the real estate value chain through investing and strategic positioning in the global market, Propchain is set to redefine the real estate investment landscape and continue its path of success. This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here

Propl

propl.net

-- employees

Since n.d.

COMPANY RANKING

PROPL

EVERGREEN INDEX #8859

Propl WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

Propl

propl.net

-- employees

Since n.d.

COMPANY RANKING

PROPL

EVERGREEN INDEX #8859

RELATED COMPANIESRANK

STORIES ABOUT PROPL

Propl WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!