Tekie

tekie

So, let’s start! Tell us a bit about yourself. For example, name, profession, and personal interests. I’m Asim Rais Siddiqui, and I’m the co-founder and CTO of TekRevol. We specialize in developing custom software solutions and helping businesses leverage technology to embark on the path to digital transformation. My interests are varied but also closely connected with the work I do. I’m heavily interested in emerging technologies like blockchain and AI and spend quite a bit of time reading up on them and researching their transformative impact. Interesting! What was your latest Hackernoon Top story about? My latest Hackernoon Top Story was about the Saudi Megacity Project NEOM and the implications it might have on the future of smart cities and urban development. I explored NEOM's ambitious plans for sustainable living, advanced technologies, and eco-friendly infrastructure while assessing the potential challenges and opportunities this project presents for both Saudi Arabia and the global community. Do you usually write on similar topics? If not, what do you usually write about? I write about everything tech, and smart cities are just one aspect of that. I also have a keen interest in writing about AI and blockchain. These technologies are at the forefront of innovation, reshaping industries, and pushing the boundaries of what's possible. Whether it's discussing AI's role in healthcare, finance, or autonomous systems or delving into the potential of blockchain for secure transactions and decentralized applications, I aim to provide insights into the rapidly evolving tech landscape. Great! What is your usual writing routine like (if you have one?) Whenever I come across or read something interesting that makes me really think, I feel the need to do research on it and put those thoughts into words. That’s how most of my stories come about. I designate focused morning hours in a distraction-free workspace to write. I’m also a firm believer in the 'write first, edit later' approach to maintaining flow. Once I’m satisfied with what I’ve written, I’ll usually make someone go over it to hear what they have to say. If I have some new ideas or thoughts to add, I make those changes before finally editing the whole story and sending it over. Being a writer in tech can be a challenge. It’s not often our main role, but an addition to another one. What is the biggest challenge you have when it comes to writing? As a writer in the tech industry, one of the biggest challenges I face is balancing writing with my primary responsibilities. Striking the right balance between technical responsibilities and crafting clear, engaging content can be demanding. Additionally, conveying complex technical concepts in a way that's understandable to a broader audience can also be challenging. However, I see these challenges as opportunities for growth, as they push me to continuously improve my communication skills and bridge the gap between technology and non-technical stakeholders. What is the next thing you hope to achieve in your career? My company, TekRevol, is my utmost priority for now, and its growth is synonymous with mine. Right now, we’re at the crucial scaling and expansion stage and are open to innovating and trying new things. That’s exactly what we’ve been doing the past few months to see where that takes us. Without trial and error, we wouldn’t have gotten where we are today either. So, for now, I just hope that we can get through this stage successfully and cement ourselves as industry leaders around the globe. Do you have a non-tech-related hobby? If yes, what is it? As someone who spends over 12 hours in my office every day, I don’t get a lot of free time. So when I’m home, I try to make the most of the time I have to spend with my family, especially with my daughter. What can the Hacker Noon community expect to read from you next? To be honest, I don’t know either yet. But ever since I’ve been reading up on NEOM and the potential it has to change the future of smart cities, I have been very interested in previous smart city projects around the globe as well. So, you might just read my take on one of those and what NEOM can learn and unlearn from those examples. What’s your opinion on HackerNoon as a platform for writers? HackerNoon is undeniably an excellent platform for writers, particularly those in the tech industry. It’s commendable that it provides a platform for both emerging and established writers to showcase their expertise, making it a valuable resource for anyone seeking to stay updated on the latest tech trends. I believe that HackerNoon is an ideal platform for writers looking to make an impact in the tech industry. Thanks for taking the time to join our “ ” series. It was a pleasure. Do you have any closing words? Meet the writer I believe that staying curious and adaptable in the tech world is essential, as it's an ever-changing landscape. This curiosity is what has gotten me so far, and I look forward to continuing my exploration of cutting-edge technologies and sharing my insights with the readers on Hackernoon.

Meet the Writer: HackerNoon's Contributor Asim Rais Siddiqui, Co-Founder & CTO of TekRevol

https://www.youtube.com/watch?v=fFJXEf52goY?embedable=true Battle of Olympus is an arcade-style fighting game, with roguelike elements that is placed in the futuristic cyberpunk city of Olympus. Conquer your rivals and upgrade your character to become the next leader of the gods or you can join a team and take over the city to compete against other players. Rise to the top of Olympus and test your mettle! In this Tekken-inspired blockchain fighting game, you will be able to show off your 1v1 fighting skills with lightning fast moves and by playing as legendary characters. As you improve your skills in Battle of Olympus you’ll have access to much more powerful equipment for your god. You can earn this gear by completing missions, killing bosses and helping your team win  seasons to maximize your potential winnings. Each piece of gear influences your god’s fighting style. Your combos will change as well as your move set, allowing you to strategically plan your next move and defeat your opponents in ways they will never see coming. They might not see it, but they will surely feel it. In Battle Of Olympus, you can experience randomly generated missions, season-based competitions, and seasonal rewards! If this sounds like something that tickles your fancy, check out our roadmap so you can follow along with the development process of our game below. How Players Earn As a play-and-earn game, Battle of Olympus allows players to get compensated while they play without sacrificing quality game play. There are two main ways players can make money with Battle of Olympus: NFT minting and trading: Players will have the option to mint their characters and gear, and trade them on the marketplace. The more you play, the higher your chances of earning top-tier gear to improve your god. Seasons: Join forces with other players in Battle of Olympus for a season to conquer the different boroughs of Olympus. At the end, the winner gets the spoils. Features PvP & Story Mode Want to let off some steam with your friends and knock each other out ? Look no further than Battle Of Olympus. Or maybe you want to find your own way through the engaging storyline? Pick your poison, as we have implemented both of gameplay styles into Battle Of Olympus. (virtually please) Online PvP & Controller Support Battle other warriors all over the world with your favorite controller! Whether you game on a Playstation, Xbox, mouse and keyboard or even . You can always use your weapon of choice to bring the pain. this thing The Mechanics Three buttons. That's all you need to bring down the hammer in Battle of Olympus and execute deadly combos with lightning fast precision. Punch, kick and use special moves to bring down your opponents and taste victory. Follow us! Keep an eye on the to keep up with the latest content on our blog every week. On the website, you can find key information, like our roadmap with dates you’ll want to take note of. You will also see some of our next projects (which we can’t share much about yet), but keep your eyes peeled and official Battle of Olympus website follow us on all of our socials. Make sure to sign up for Early Access Here Meet the Revenant team at DCENTRAL Miami 2022 https://www.youtube.com/watch?v=H9AA5jtm9t8?embedable=true Dcentral Miami is the LARGEST DeFi & NFT conference. It has over 5000 attendees and this year we’re giving you a chance to win a ticket to one of the most awaited events of the year! With $4000 in prizes up for grabs, don’t wait to win! Just do it by clicking here! Until next time!

Battle Of Olympus: A Tekken Inspired Blockchain Fighting Game

Howdy Hackers! I’m German Tebiev, the Software Development Process Architect @ . Devexperts First off, I’d like to express my gratitude to the staff, and all other beautiful humans of HackerNoon, for nominating me for a 2022 Noonies award!☺️ I’ve been nominated for the following category, and if you think my writing offers good value, please take some time to check out these award pages and vote for me: HackerNoon Contributor of the Year- PRODUCTIVITY As a writer in the tech industry, I believe that the most significant enhancements we can make in our industry are non-technical. Our software development processes are rather basic and we also try to solve everything with software. I firmly believe in the following words by Peter Drucker: The most important, and indeed the truly unique, contribution of management in the twentieth century was the fiftyfold increase in the productivity of the manual worker in manufacturing. The most important contribution management needs to make in the twenty-first century is similarly to increase the productivity of knowledge work and the knowledge worker. Learn more about my views on productivity, IT management, and my tech industry journey via the interview below. 1. What do you currently do, and what’s your favorite part about it? What I do has a well-known name: management. Unfortunately, quite a few people would be happy to hear something about management. In books and articles covering the topic, you can regularly find something like: be a leader, do not be a manager. I can understand this request. The major problem is that overwhelmingly, ones with the management title often try to achieve the system’s (e.g., the team’s) goals violently. You have been there: long hours, poor requirements, no explicitly set expectations, and no learning. There is the opposite way, based on the knowledge of Deming, Drucker, Ohno, Goldratt, and many other diligent people. This way is about continuous learning, empathy, statistics, systems theory, and more. In the end, it is about making systems so capable that they surmount yesterday’s challenges with much less effort. Now I try to apply all my knowledge of scientific management to software development. I like that we are at the beginning, with so many things to do. 2. How did you get started with your Tech Career? I entered my first university to get a bachelor’s degree in management in 2009. After the first year, I thought, well, I enjoyed this, but how can I be helpful to the world? There was no answer, and I started looking into programming. I started with the markup language in the vk.com social network. Then I switched to learning HTML and JavaScript. These days, I was trying to write down my lectures in HTML to receive some practice. After a few years and a few trials of running a project with my friends, I decided it was time to go in-depth. I entered for the second bachelor’s degree in computational mathematics and cybernetics. Seven months later, I was on my first job creating educational games for children. 3. If Utopia were a color what color do you think it’d be and why? I like green. Especially when green trees fit into our cities’ landscapes.🙂 4. If everything about HackerNoon changed drastically, what is one detail you’d like to keep exactly the same?  OR What’s your favorite thing to do with HackerNoon and why? My favorite thing about HackerNoon is the editorial support you provide. It gives a pleasing sense of teamwork.☺️ 5. Tell us more about the things you write/make/manage/build! I write on two topics: personal productivity and IT management from the perspective of several praised theories. These two topics are of the most significant interest to me as I feel they are where we can gain the most important win as a programming community. I also have several articles on technical topics in . The funniest ones I find there are about monorepos and polyrepos. the Uploadcare blog 6. What’s your favorite thing about the internet? The fact that here we can meet people whom we would never meet otherwise. 7. It’s an apocalypse of ‘walking dead’ proportions and you can only own a singular piece of technology, what would it be? I would take what we now know as a kanban board with flow analytics attached to it. With these two things, we can restore civilization. Here is an example of what we can achieve knowing the flow-oriented approach: In fact, the antecedents of a focus on efficient flows can be traced to the sixteenth century, more precisely, to the Venetian Arsenal in Northern Italy, which was the most powerful and efficient shipbuilding enterprise in the world. The arsenal was capable of producing a fully equipped merchant or naval vessel in less than a day. Elsewhere in Europe, it could take months to produce a vessel of a similar size. 8. What is your least favorite thing about the internet? Good things sometimes are hard to discover. 9. If you were given $10 million to invest in something today what would you invest in and why? First, I would need to invest in discovering something that would provide a constant cash flow, as I’m not sure that $10 million would be enough. Then I would invest in the giant books graph, containing all the references between all ever written books. It would provide us with some insights into the structure of the knowledge of humanity. 10. What’s something you’re currently learning or excited to learn? Currently, I read about the evolution in Richard Dawkins’s “The Blind Watchmaker”. It has rather interesting logic, quite different from what we are used to. 11. Would you rather travel 10 years into the past or 10 years into the future? Give reasons for your answer. I would instead discover opportunities to help me feel good in 10 years and later.🙂

Our Most Significant Enhancements are Non-Technical: Interview with Noonies Nominee German Tebiev

The Tekken 8 reveal trailer has arrived. In it, we’ve got a look at the story mode and the Tekken 7 story mode. But what else can we expect from the upcoming fighting game? The game is coming to PlayStation 5, Xbox Series X, PC, and Steam. However, the trailer didn’t give us any details about the release date or other characters. It's time for a next-gen grudge match! 🥊 Take the fight to a new level with . #TEKKEN8 Watch it in 4k: https://t.co/0ac3QyZiOz pic.twitter.com/hUulkqPdoU — TEKKEN (@TEKKEN) September 13, 2022 Tekken 8 gameplay video The Tekken 8 reveal trailer has been released and it is a great first look at the new game. At under two minutes, it gives you an inside look at what the game will be like. The trailer has some interesting details, such as the use of real-time PlayStation 5 graphics. The trailer also shows the characters battling and uses cinematic camera angles. However, Bandai Namco has yet to announce the release date for Tekken 8. Watch the Official Trailer: https://youtu.be/07FdDRbdurg Tekken 8 is coming to the PlayStation 5, Xbox Series X/S, and PC. The gameplay video shows Kazuya Mishima and Jin Kazama battling in a rainy battle. The game will be a return to Tekken’s storied history, and this trailer promises to deliver plenty of action for fans of the franchise. Tekken 8 is a 3D fighting game with a complex combat system. It has quickly become one of the most popular fighting game franchises. Its latest installment is expected to launch sometime in the next few months. Since Tekken 7 was a breakout success, Tekken 8 is a much-anticipated sequel. A new camera system is introduced in Tekken 8, giving players a better look at how the game plays. It also shows more of the battlefield than in previous games, including weather effects and Rage Moves. The latter mechanic was introduced in Tekken 7 and is returning in Tekken 8. The gameplay video also shows the use of Rage Moves, which are super arts that enable players to perform attacks in a unique way. Tekken 8 story mode vs Tekken 7 The Tekken 8 reveal trailer is here, and it’s a great first look at what the new fighting game will look like. While it’s under two minutes long, it gives you a glimpse of what’s to come. According to a post on the PlayStation Blog, the trailer was filmed on a PlayStation 5 while running at 60 frames per second. It also features the same character models and backgrounds as the in-game version. A father and son showdown will be the highlight of the Tekken 8 story mode. It’s not clear when the game will be released, but it is expected to be available for the PlayStation 5 and Xbox Series X and S. The trailer features a scene from the main story. Tekken 8 was unveiled during the September State of Play event by Sony, and the reveal trailer showcased a short gameplay demo. In it, Kazuya and Jin were fighting on a cliffside in the rain. The storyline looks to continue from the Tekken 7 game, which was released in 2015. Tekken 8 is coming to PlayStation 5 and Xbox Series X, as well as PC via Steam. The reveal trailer didn’t show the game’s release date, but it did reveal the names of some of the characters, including Ryu, Jin, and Kazuya Mishima. It will be released on PlayStation 5 and Xbox Series X, but won’t be coming to the Nintendo Switch, which was announced last week. Tekken 8 teaser trailer The Tekken 8 teaser trailer is not quite cinematic but it gives us a glimpse into what to expect. It shows some of the game’s characters in a rainy battle, which is promising. It also shows a story mode in development. However, this trailer doesn’t reveal much in terms of other characters and release date. Tekken 8 is a fighting game with some pretty impressive graphics. It looks like a pre-rendered movie, but it is actually real-time footage from the PlayStation 5 version of the game. This means that the background effects and skin textures are more detailed than in previous Tekken games. Tekken 8 is very different from Tekken 7. The first installment of the series was released in arcades and was eventually made available for PC. The gameplay is much improved and the visuals are much more advanced. This is a major step forward for the series. However, there are still a few things we should look out for. The main focus of the game’s story mode is the rivalry between Jin and Kazuya. While the previous game featured dynamic battles between the two characters, Tekken 8 could benefit from some more substantial story scenarios and endings for characters who aren’t in the main campaign. Tekken Tag Tournament 2 Tekken Tag Tournament 2 features 59 different characters, including classic characters and newcomers. This makes it the largest roster in the series. Not only does the game feature new characters, it also provides an array of new moves and encourages experimentation and creativity. Whether you want to play competitively or with your friends, you can find a new style for the game. Players choose two characters to participate in a match and can switch between them anytime. The character with the lowest life bar in a match loses that round. The game’s mechanics are refined, with each character able to perform an amazing variety of moves and combos. Fans love the tag team format and the ability to mix and match fighters to form tag teams. The gameplay is similar to the first Tekken game, but this sequel takes it to the next level with a wide variety of new characters. Unlike its predecessor, Tekken Tag Tournament 2 introduces a new tag combo, which allows the player to attack multiple opponents simultaneously. The Tekken Tag Tournament series has been an absolute hit with fans for years. This PlayStation 2-exclusive title introduced the Tekken tag mechanic and improved it even further. In addition to the new tag mechanic, players can now manage fighters’ health and tactics. The Snoop Dogg stage is another new addition to the franchise. Tekken Tag Tournament 2 features an extensive roster of 61 characters. With new additions such as Mushroom Battles and Exclusive Costumes, the game brings a new and improved experience to fans of the series. In addition, it features multiplayer and multi-player match options. The game also includes new stages and modes. The Tekken series has a long history and is no stranger to update cycles. Its next installment, Tekken 8, has been in development for over a decade. It has received a huge fan following and has been a hit with millions of players worldwide. The Tekken series also has a strong storyline. The first part of Tekken featured a father and son battle. In Tekken 7, the son killed his father, but the father survived and later jumped over him to kill him. Kazuya’s fate isn’t clear at the moment, but we can expect more details in Tekken 8. Tekken Mobile If you love the Tekken series, you’ll love Tekken 8 Mobile. This fighting game lets you take the fight to a whole new level. The game features a father-son showdown, which will test the skills of both father and son. Watch the trailer to get a preview of how the game plays and how you can take the fight to a whole new level! Each Tekken Mobile fighter has a set of 9 Waza cards that he can use to inflict more damage than his opponents. These cards are found in the lower right corner of the screen, and you can tap them to use special attacks. The Waza cards include guard break cards, which break the defense of your opponent, and strike cards which deal maximum damage. Tekken 8 is one of the most beloved fighting games in history. The game has been adapted to mobile platforms by Namco, the maker of the popular arcade game. While the arcade version was shut down earlier this year, Tekken is back for a grand comeback on mobile. Tekken 8 Mobile features four game modes, including a story mode and multiplayer modes. The game also features a Dojo mode, which lets players participate in asynchronous PvP matches. Each chapter of the game includes three “attackers” – the best two “defenders” and the strongest “attackers.” The players can also change fighters after a few matches. However, players must leave the current chapter in order to change their fighters, or else their progress will be reset. Tekken 8 Mobile features incredible lighting effects and cinematic sequences. The game also sports a cast of redesigned characters with finer graphical details. The game also features a storm-like stage, with realistic rain effects and dynamic lighting. Tekken 8 Mobile has received positive reviews from critics and gamers alike, and a new version of the game was recently announced by developer Bandai Namco. The game is a sequel to Tekken 7, which was released on PC and consoles during the previous generation. Character customization Tekken 8 is a highly anticipated game. This new fighting game has some great new features including character customization. Players will now be able to make their characters look as if they were from a different era. This is a welcome addition for fans of the Tekken series, as it provides a new way to play the game. The last Tekken game, Tekken 7, featured great character customization. The game even offered an outfit creator, allowing you to build outfits for each character. Character customization is a great way to express yourself and make your own unique character. You can even customize your characters online – if you can find people who want to play your character. Tekken 8’s roster should include a great mix of returning fighters and unique new faces. While the game has been teased at EVO last month, it has yet to receive a formal release date. In the meantime, fans can expect the game to be available on PlayStations, Xbox Series XS, and PC via Steam. Tekken 8 is set to be one of the biggest fighting games of all time, so expect it to be highly anticipated. Story Mode Tekken 8 is a fighting game with a new story mode that focuses on the story of Kazuya Mishima and Jin Kazama. They go up against each other in a game that takes place on a new world with a new set of environments. The game features dynamic arenas and new backgrounds, which are sure to give the game’s fights a whole new look. The Tekken 8 trailer shows off these visual effects in a way that is not possible with a typical trailer. It also shows off some of the new playable characters, including Kazuya Mishima, Jin Kazama, and Heihachi. The story mode in Tekken 8 isn’t the first game to use a story mode, but it’s a welcome addition. The previous games in the series featured this mode, but it never felt like the main event of the game. It was mainly used to drive merchandising and advertising. But Tekken 8’s story mode is a must-have for Tekken fans. The story mode in TEKKEN 8 includes several characters who are unplayable outside of the story mode. You can play as Kid Kazuya, the younger version of Kazuya Mishima. You can also play as Kunimitsu II, the daughter of Kunimitsu from the previous Tekken games. She has inherited her mother’s vendetta against Heihachi. Another new character is Lucky Chloe, a freestyle dance fighter that uses a kitten-themed costume. Tekken 8 is still in development, but it has already been confirmed that it will be available on PC. The game’s engine is pushing the feeling of power even further, with more realistic waves, storms, and tornadoes. In addition, this game is said to be the longest-running story in a video game. It’s still unclear when Tekken 8 will come out, but we’ll know more once the game is out. Tekken 8’s story mode continues the story from Tekken 7, which has focused on the defeat of Heihachi Mishima. Now, Kazuya Mishima and Jin are on a journey to achieve world dominance. Also Published On: Tekken 8 Reveal Trailer Official Review – All You Need to Know About the New Fighting Game - MashRadar

Tekken 8 Reveal Trailer and All You Need to Know About the New Fighting Game

Tekken Trilogy (PS1) Retro Game Review

In recent Smash Bros news, the Super Smash Bros. Ultimate roster has gotten a little bigger, with the announcement of a new DLC character. With an initial roster size of 74 characters, that includes all of the characters from the previous games, Super Smash Bros. Ultimate is one of the most ambitious video games in recent years. Here are more details on the new DLC character, Kazuya Mishima. Super Smash Bros Ultimate News: New Character Details Jumping out of Tekken, the immensely popular fighting game franchise, is Kazuya Mishima, one of the series’ most iconic characters. After spending most of the time trying to take down his own father in Tekken, Kazuya will be put to the test when he joins the Super Smash Bros. Ultimate roster. Along with the character himself, the DLC bundle will come with a new stage based on a classic Tekken arena. In the background of the stage will be Heihachi Mishima, the father of Kazuya. Tekken characters are known for having a lot of moves and combos, with some characters having over in their repertoire. One might think that a Tekken character would’ve been astronomically toned down for Super Smash Bros, but it seems that’s not the case. 100 moves In the Nintendo Direct showcasing Kazuya, they showed that he still has many moves at his disposal. Sure, he doesn’t have dozens and dozens of moves, but it’s wild how many Kazuya still has. And with the inclusion of Kazuya in Smash Bros, he now joins the elite list of fighting game icons that have been included in the game. Ryu and Ken from Street Fighter, and Terry from Fatal Fury were previously added to the game as playable characters; with Guile from Street Fighter and Akira Yuki from Virtua Fighter also appearing as assist trophies. Kazuya Mishima has been a staple of the Tekken franchise since the beginning, and he will feel right at home with other video game legends. With one more DLC character yet to be revealed, we can’t wait for more Smash Bros. news in the future More in Gaming: 1. What is the Sony PlayStation 5 System Software Beta Program? 2. Top 25 Publications about AI You Have to Read 3. A Plague Tale: Innocence Remastered Arrives in July for Next-Gen Consoles For more Super Smash Bros news, make sure to down below! subscribe to our newsletter

Smash Bros. News: Tekken Character Announced as DLC

Authors:
(1) Tinghui Ouyang, National Institute of Informatics, Japan (thouyang@nii.ac.jp);
(2) Isao Echizen, National Institute of Informatics, Japan (iechizen@nii.ac.jp);
(3) Yoshiki Seo, Digital Architecture Research Center, National Institute of Advanced Industrial Science and Technology, Japan (y.seo@aist.go.jp). Table of Links Abstract and Introduction Description and Related Work of OOD Detection Methodology Experiments and Results Conclusions, Acknowledgement and References V. CONCLUSIONS In this paper, we addressed the issue of out-of-distribution (OOD) data in AI quality management by proposing a framework that combines deep learning and statistical measures for OOD detection. Initially, we leveraged the strong feature representation and dimensionality reduction capabilities of AE to extract activation traces from hidden neurons as input features for OOD analysis. Subsequently, we employed five statistical measures, namely KD, LOF, MD, kNN, and the proposed LCP, using these representative features for OOD detection. Our findings revealed that the proposed LCP, which incorporates both neighbor information and data reconstruction error, outperforms the other measures in OOD detection. Thus, it was proved to be valuable for describing and detecting OOD data. Furthermore, this research extracted reasonable corner case data with high OOD scores from the given datasets, such as MNIST, CIFAR10, and GTSRB datasets. These corner case data have high OOD scores and exhibit abnormal characteristics compared to normal data. Therefore, detecting such data using the proposed method is helpful in future AI quality assurance, particularly for quality analysis related to data security. VI. ACKNOWLEDGEMENT This research is supported by the New Energy and Industrial Technology Development Organization (NEDO) project ’JPNP20006’, and JSPS Grant-in-Aid for Early-Career Scientists (Grant Number 22K17961). REFERENCES [1] The National Institute of Advanced Industrial Science and Technology (AIST). Machine learning quality management guideline, 2023. https://www.digiarc.aist.go.jp/en/publication/aiqm/. [2] Kexin Pei, Yinzhi Cao, Junfeng Yang, and Suman Jana. Deepxplore: Automated whitebox testing of deep learning systems. In proceedings of the 26th Symposium on Operating Systems Principles, pages 1–18, 2017. [3] Tinghui Ouyang, Yoshinao Isobe, Saima Sultana, Yoshiki Seo, and Yutaka Oiwa. Autonomous driving quality assurance with data uncertainty analysis. In 2022 International Joint Conference on Neural Networks (IJCNN), pages 1–7. IEEE, 2022. [4] Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, and Thomas G Dietterich. Anomaly and novelty detection, explanation, and accommodation (andea). In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pages 4145–4146, 2021. [5] Jingkang Yang, Kaiyang Zhou, Yixuan Li, and Ziwei Liu. Generalized out-of-distribution detection: A survey. arXiv preprint arXiv:2110.11334, 2021. [6] Varun Chandola, Arindam Banerjee, and Vipin Kumar. Anomaly detection: A survey. ACM computing surveys (CSUR), 41(3):1–58, 2009. [7] Marco AF Pimentel, David A Clifton, Lei Clifton, and Lionel Tarassenko. A review of novelty detection. Signal processing, 99:215–249, 2014. [8] Chuanxing Geng, Sheng-jun Huang, and Songcan Chen. Recent advances in open set recognition: A survey. IEEE transactions on pattern analysis and machine intelligence, 43(10):3614–3631, 2020. [9] R´emi Domingues, Maurizio Filippone, Pietro Michiardi, and Jihane Zouaoui. A comparative evaluation of outlier detection algorithms: Experiments and analyses. Pattern recognition, 74:406–421, 2018. [10] Jing Li, Pengbo Lv, Huijun Li, and Wanghu Chen. Outlier detection based on stacked autoencoder and gaussian mixture model. In 2022 IEEE International Conference on Big Data (Big Data), pages 3763–3769. IEEE, 2022. [11] Michael E Tipping and Christopher M Bishop. Probabilistic principal component analysis. Journal of the Royal Statistical Society Series B: Statistical Methodology, 61(3):611–622, 1999. [12] John A Quinn and Masashi Sugiyama. A least-squares approach to anomaly detection in static and sequential data. Pattern Recognition Letters, 40:36–40, 2014. [13] Reuben Feinman, Ryan R Curtin, Saurabh Shintre, and Andrew B Gardner. Detecting adversarial samples from artifacts. arXiv preprint arXiv:1703.00410, 2017. [14] Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin. A simple unified framework for detecting out-of-distribution samples and adversarial attacks. Advances in neural information processing systems, 31, 2018. [15] Kathrin Grosse, Praveen Manoharan, Nicolas Papernot, Michael Backes, and Patrick McDaniel. On the (statistical) detection of adversarial examples. arXiv preprint arXiv:1702.06280, 2017. [16] Ahmed Abusnaina, Yuhang Wu, Sunpreet Arora, Yizhen Wang, Fei Wang, Hao Yang, and David Mohaisen. Adversarial example detection using latent neighborhood graph. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 7687–7696, 2021. [17] Bruno Andriamanalimanana, Ali Tekeoglu, Korkut Bekiroglu, Saumendra Sengupta, Chen-Fu Chiang, Michael Reale, and Jorge Novillo. Symmetric kullback-leibler divergence of softmaxed distributions for anomaly scores. In 2019 IEEE Conference on Communications and Network Security (CNS), pages 1–6. IEEE, 2019. [18] Jianbo Yu, Xiaoyun Zheng, and Shijin Wang. A deep autoencoder feature learning method for process pattern recognition. Journal of Process Control, 79:1–15, 2019. [19] Lukas Ruff, Robert Vandermeulen, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel M¨uller, and Marius Kloft. Deep one-class classification. In International conference on machine learning, pages 4393–4402. PMLR, 2018. [20] Jinhan Kim, Robert Feldt, and Shin Yoo. Guiding deep learning system testing using surprise adequacy. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE), pages 1039–1049. IEEE, 2019. [21] Zenan Li, Xiaoxing Ma, Chang Xu, and Chun Cao. Structural coverage criteria for neural networks could be misleading. In 2019 IEEE/ACM 41st International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER), pages 89–92. IEEE, 2019. [22] Shiqing Ma, Yingqi Liu, Guanhong Tao, Wen-Chuan Lee, and Xiangyu Zhang. Nic: Detecting adversarial samples with neural network invariant checking. In 26th Annual Network And Distributed System Security Symposium (NDSS 2019). Internet Soc, 2019. [23] Tarem Ahmed. Online anomaly detection using kde. In GLOBECOM 2009-2009 IEEE Global Telecommunications Conference, pages 1–8. IEEE, 2009. [24] Siying Xu, Huiyi Liu, Liting Duan, andWenjingWu. An improved lof outlier detection algorithm. In 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA), pages 113–117. IEEE, 2021. [25] Laurens Van der Maaten and Geoffrey Hinton. Visualizing data using t-sne. Journal of machine learning research, 9(11), 2008. [26] Yann LeCun. The mnist database of handwritten digits. http://yann. lecun. com/exdb/mnist/, 1998. [27] Alex Krizhevsky, Geoffrey Hinton, et al. Learning multiple layers of features from tiny images. 2009. [28] Tom Fawcett. An introduction to roc analysis. Pattern recognition letters, 27(8):861–874, 2006. [29] Tinghui Ouyang, Vicent Sanz Marco, Yoshinao Isobe, Hideki Asoh, Yutaka Oiwa, and Yoshiki Seo. Corner case data description and detection. In 2021 IEEE/ACM 1st Workshop on AI Engineering-Software Engineering for AI (WAIN), pages 19–26. IEEE, 2021. [30] Stallkamp, Johannes, Marc Schlipsing, Jan Salmen, and Christian Igel. The German traffic sign recognition benchmark: a multi-class classification competition. In The 2011 international joint conference on neural networks, pages 1453-1460. IEEE, 2011. This paper is available on arxiv under CC 4.0 license. Authors: (1) Tinghui Ouyang, National Institute of Informatics, Japan (thouyang@nii.ac.jp); (2) Isao Echizen, National Institute of Informatics, Japan (iechizen@nii.ac.jp); (3) Yoshiki Seo, Digital Architecture Research Center, National Institute of Advanced Industrial Science and Technology, Japan (y.seo@aist.go.jp). Authors: Authors: (1) Tinghui Ouyang, National Institute of Informatics, Japan (thouyang@nii.ac.jp); (2) Isao Echizen, National Institute of Informatics, Japan (iechizen@nii.ac.jp); (3) Yoshiki Seo, Digital Architecture Research Center, National Institute of Advanced Industrial Science and Technology, Japan (y.seo@aist.go.jp). Table of Links Abstract and Introduction Abstract and Introduction Description and Related Work of OOD Detection Description and Related Work of OOD Detection Methodology Methodology Experiments and Results Experiments and Results Conclusions, Acknowledgement and References Conclusions, Acknowledgement and References V. CONCLUSIONS In this paper, we addressed the issue of out-of-distribution (OOD) data in AI quality management by proposing a framework that combines deep learning and statistical measures for OOD detection. Initially, we leveraged the strong feature representation and dimensionality reduction capabilities of AE to extract activation traces from hidden neurons as input features for OOD analysis. Subsequently, we employed five statistical measures, namely KD, LOF, MD, kNN, and the proposed LCP, using these representative features for OOD detection. Our findings revealed that the proposed LCP, which incorporates both neighbor information and data reconstruction error, outperforms the other measures in OOD detection. Thus, it was proved to be valuable for describing and detecting OOD data. Furthermore, this research extracted reasonable corner case data with high OOD scores from the given datasets, such as MNIST, CIFAR10, and GTSRB datasets. These corner case data have high OOD scores and exhibit abnormal characteristics compared to normal data. Therefore, detecting such data using the proposed method is helpful in future AI quality assurance, particularly for quality analysis related to data security. VI. ACKNOWLEDGEMENT This research is supported by the New Energy and Industrial Technology Development Organization (NEDO) project ’JPNP20006’, and JSPS Grant-in-Aid for Early-Career Scientists (Grant Number 22K17961). REFERENCES [1] The National Institute of Advanced Industrial Science and Technology (AIST). Machine learning quality management guideline, 2023. https://www.digiarc.aist.go.jp/en/publication/aiqm/. [2] Kexin Pei, Yinzhi Cao, Junfeng Yang, and Suman Jana. Deepxplore: Automated whitebox testing of deep learning systems. In proceedings of the 26th Symposium on Operating Systems Principles, pages 1–18, 2017. [3] Tinghui Ouyang, Yoshinao Isobe, Saima Sultana, Yoshiki Seo, and Yutaka Oiwa. Autonomous driving quality assurance with data uncertainty analysis. In 2022 International Joint Conference on Neural Networks (IJCNN), pages 1–7. IEEE, 2022. [4] Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, and Thomas G Dietterich. Anomaly and novelty detection, explanation, and accommodation (andea). In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pages 4145–4146, 2021. [5] Jingkang Yang, Kaiyang Zhou, Yixuan Li, and Ziwei Liu. Generalized out-of-distribution detection: A survey. arXiv preprint arXiv:2110.11334, 2021. [6] Varun Chandola, Arindam Banerjee, and Vipin Kumar. Anomaly detection: A survey. ACM computing surveys (CSUR), 41(3):1–58, 2009. [7] Marco AF Pimentel, David A Clifton, Lei Clifton, and Lionel Tarassenko. A review of novelty detection. Signal processing, 99:215–249, 2014. [8] Chuanxing Geng, Sheng-jun Huang, and Songcan Chen. Recent advances in open set recognition: A survey. IEEE transactions on pattern analysis and machine intelligence, 43(10):3614–3631, 2020. [9] R´emi Domingues, Maurizio Filippone, Pietro Michiardi, and Jihane Zouaoui. A comparative evaluation of outlier detection algorithms: Experiments and analyses. Pattern recognition, 74:406–421, 2018. [10] Jing Li, Pengbo Lv, Huijun Li, and Wanghu Chen. Outlier detection based on stacked autoencoder and gaussian mixture model. In 2022 IEEE International Conference on Big Data (Big Data), pages 3763–3769. IEEE, 2022. [11] Michael E Tipping and Christopher M Bishop. Probabilistic principal component analysis. Journal of the Royal Statistical Society Series B: Statistical Methodology, 61(3):611–622, 1999. [12] John A Quinn and Masashi Sugiyama. A least-squares approach to anomaly detection in static and sequential data. Pattern Recognition Letters, 40:36–40, 2014. [13] Reuben Feinman, Ryan R Curtin, Saurabh Shintre, and Andrew B Gardner. Detecting adversarial samples from artifacts. arXiv preprint arXiv:1703.00410, 2017. [14] Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin. A simple unified framework for detecting out-of-distribution samples and adversarial attacks. Advances in neural information processing systems, 31, 2018. [15] Kathrin Grosse, Praveen Manoharan, Nicolas Papernot, Michael Backes, and Patrick McDaniel. On the (statistical) detection of adversarial examples. arXiv preprint arXiv:1702.06280, 2017. [16] Ahmed Abusnaina, Yuhang Wu, Sunpreet Arora, Yizhen Wang, Fei Wang, Hao Yang, and David Mohaisen. Adversarial example detection using latent neighborhood graph. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 7687–7696, 2021. [17] Bruno Andriamanalimanana, Ali Tekeoglu, Korkut Bekiroglu, Saumendra Sengupta, Chen-Fu Chiang, Michael Reale, and Jorge Novillo. Symmetric kullback-leibler divergence of softmaxed distributions for anomaly scores. In 2019 IEEE Conference on Communications and Network Security (CNS), pages 1–6. IEEE, 2019. [18] Jianbo Yu, Xiaoyun Zheng, and Shijin Wang. A deep autoencoder feature learning method for process pattern recognition. Journal of Process Control, 79:1–15, 2019. [19] Lukas Ruff, Robert Vandermeulen, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel M¨uller, and Marius Kloft. Deep one-class classification. In International conference on machine learning, pages 4393–4402. PMLR, 2018. [20] Jinhan Kim, Robert Feldt, and Shin Yoo. Guiding deep learning system testing using surprise adequacy. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE), pages 1039–1049. IEEE, 2019. [21] Zenan Li, Xiaoxing Ma, Chang Xu, and Chun Cao. Structural coverage criteria for neural networks could be misleading. In 2019 IEEE/ACM 41st International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER), pages 89–92. IEEE, 2019. [22] Shiqing Ma, Yingqi Liu, Guanhong Tao, Wen-Chuan Lee, and Xiangyu Zhang. Nic: Detecting adversarial samples with neural network invariant checking. In 26th Annual Network And Distributed System Security Symposium (NDSS 2019). Internet Soc, 2019. [23] Tarem Ahmed. Online anomaly detection using kde. In GLOBECOM 2009-2009 IEEE Global Telecommunications Conference, pages 1–8. IEEE, 2009. [24] Siying Xu, Huiyi Liu, Liting Duan, andWenjingWu. An improved lof outlier detection algorithm. In 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA), pages 113–117. IEEE, 2021. [25] Laurens Van der Maaten and Geoffrey Hinton. Visualizing data using t-sne. Journal of machine learning research, 9(11), 2008. [26] Yann LeCun. The mnist database of handwritten digits. http://yann. lecun. com/exdb/mnist/, 1998. [27] Alex Krizhevsky, Geoffrey Hinton, et al. Learning multiple layers of features from tiny images. 2009. [28] Tom Fawcett. An introduction to roc analysis. Pattern recognition letters, 27(8):861–874, 2006. [29] Tinghui Ouyang, Vicent Sanz Marco, Yoshinao Isobe, Hideki Asoh, Yutaka Oiwa, and Yoshiki Seo. Corner case data description and detection. In 2021 IEEE/ACM 1st Workshop on AI Engineering-Software Engineering for AI (WAIN), pages 19–26. IEEE, 2021. [30] Stallkamp, Johannes, Marc Schlipsing, Jan Salmen, and Christian Igel. The German traffic sign recognition benchmark: a multi-class classification competition. In The 2011 international joint conference on neural networks, pages 1453-1460. IEEE, 2011. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Advancing OOD Detection: A Deep Learning Approach

DuckStation is a free, open-source, cross-platform PlayStation 1 emulator that allows you to play your childhood games on modern hardware and operating systems with maximum compatibility and top-notch speed. But before you question its legality, hear me out: It's completely legal to emulate games as long as you own the games themselves and the emulator does not violate any company policies, which it does not in this case. It's a fantastic emulator that guarantees to provide support for most games out of the box. I've tested some of my favorite games like Resident Evil, Tekken, and NFS, and they performed incredibly well. In this article, we will discuss some of its highlighted features, as well as how to install it on most Linux distributions, including post-installation steps. Features of DuckStation The following is a list of the unique features that this emulator offers: It's free, open-source, and cross-platform that supports Windows, Linux, and macOS.
Supports modern CPU architectures like x86-64 for desktops and armv7/AArch64 for Raspberry Pi and Apple Silicon.
It uses advanced hardware acceleration technologies like D3D11, D3D12, OpenGL, Metal, and Vulkan.
Upscaling and texture filtering are supported to enhance graphic experiences.
Played games are saved locally in the original PS1 format and can be shared across different platforms.
Easily customize digital or analog controllers to your needs.
Support loading cheats from existing lists.
Well, this one is not necessary in modern systems, but you can emulate CPU overclocking. How to Install DuckStation on Linux There are two ways to run DuckStation on Linux: one is using the portable AppImage, which doesn't require any installation, while the other involves using its Flatpak package, which requires installation but simplifies application management, such as upgrading to the latest version. I won't explain the steps for AppImage because it's quite easy: simply download the latest AppImage file from its release page and run it like a shell script. So, let's see how you can install DuckStation using Flatpak. To start, open your terminal and install Flatpak on your Linux system (it comes pre-installed in Fedora). # For Debian and Ubuntu-based distributions:
$ sudo apt install flatpak

# For Red Hat and Fedora-based distributions:
$ sudo dnf install flatpak Next, add the official Flathub repository that allows you to install Flatpak packages. $ flatpak remote-add --if-not-exists flathub https://dl.flathub.org/repo/flathub.flatpakrepo Finally, install the DuckStation Flatpak package with this command: $ flatpak install flathub org.duckstation.DuckStation Once the installation is complete, you can launch the application from the activities overview. Post-Installation Setup When you launch DuckStation for the first time, you will be presented with the following setup wizard, where you can specify the language and default theme. When done, continue by clicking on "Next". On the next screen, you'll be asked to provide a BIOS (or ROM) image to start the emulator and to play games. I won't be providing any ROM image links for legal reasons, but you can use an image from your own old PS1 unit or find one online. Next, it will ask you to specify the path of your game directory; just create one in your home directory and use that. If you have a game controller, connect it to your PC and map it according to your preferences. If not, don't worry—you can still use your keyboard and mouse. Finally, the setup is complete, and you can now exit the setup wizard by clicking on "Finish". That’s it. The DuckStation main window will now appear, displaying a list of all games located in the provided game directory. For now, I haven't added any games, so they are not appearing below. How to Uninstall DuckStation from Linux To uninstall the emulator for any reason, just open your terminal and execute this command: $ flatpak uninstall org.duckstation.DuckStation Wrap Up In this article, you learned how to play your favorite PlayStation 1 games on your PC using the DuckStation emulator. However, aside from this, there are other emulators, such as Ryujinx, that allow you to play Nintendo games on your PC. Many users still consider emulators illegal, particularly after Yuzu's case, but it's important to note that Nintendo took action against Yuzu for allegedly circumventing their software encryption. So, playing games that you own on an emulator is perfectly fine, as long as the developer isn't violating any rules or regulations set by the company. DuckStation is a free, open-source, cross-platform PlayStation 1 emulator that allows you to play your childhood games on modern hardware and operating systems with maximum compatibility and top-notch speed. emulator But before you question its legality, hear me out: It's completely legal to emulate games as long as you own the games themselves and the emulator does not violate any company policies, which it does not in this case. It's a fantastic emulator that guarantees to provide support for most games out of the box. I've tested some of my favorite games like Resident Evil, Tekken, and NFS, and they performed incredibly well. In this article, we will discuss some of its highlighted features, as well as how to install it on most Linux distributions, including post-installation steps. Features of DuckStation The following is a list of the unique features that this emulator offers: It's free, open-source, and cross-platform that supports Windows, Linux, and macOS. Supports modern CPU architectures like x86-64 for desktops and armv7/AArch64 for Raspberry Pi and Apple Silicon. It uses advanced hardware acceleration technologies like D3D11, D3D12, OpenGL, Metal, and Vulkan. Upscaling and texture filtering are supported to enhance graphic experiences. Played games are saved locally in the original PS1 format and can be shared across different platforms. Easily customize digital or analog controllers to your needs. Support loading cheats from existing lists. Well, this one is not necessary in modern systems, but you can emulate CPU overclocking. It's free, open-source, and cross-platform that supports Windows, Linux, and macOS. Supports modern CPU architectures like x86-64 for desktops and armv7/AArch64 for Raspberry Pi and Apple Silicon. It uses advanced hardware acceleration technologies like D3D11, D3D12, OpenGL, Metal, and Vulkan. Upscaling and texture filtering are supported to enhance graphic experiences. Played games are saved locally in the original PS1 format and can be shared across different platforms. Easily customize digital or analog controllers to your needs. Support loading cheats from existing lists. Well, this one is not necessary in modern systems, but you can emulate CPU overclocking. How to Install DuckStation on Linux There are two ways to run DuckStation on Linux: one is using the portable AppImage, which doesn't require any installation, while the other involves using its Flatpak package, which requires installation but simplifies application management, such as upgrading to the latest version. I won't explain the steps for AppImage because it's quite easy: simply download the latest AppImage file from its release page and run it like a shell script . release page run it like a shell script So, let's see how you can install DuckStation using Flatpak. To start, open your terminal and install Flatpak on your Linux system (it comes pre-installed in Fedora). # For Debian and Ubuntu-based distributions:
$ sudo apt install flatpak

# For Red Hat and Fedora-based distributions:
$ sudo dnf install flatpak # For Debian and Ubuntu-based distributions:
$ sudo apt install flatpak

# For Red Hat and Fedora-based distributions:
$ sudo dnf install flatpak Next, add the official Flathub repository that allows you to install Flatpak packages. $ flatpak remote-add --if-not-exists flathub https://dl.flathub.org/repo/flathub.flatpakrepo $ flatpak remote-add --if-not-exists flathub https://dl.flathub.org/repo/flathub.flatpakrepo Finally, install the DuckStation Flatpak package with this command: $ flatpak install flathub org.duckstation.DuckStation $ flatpak install flathub org.duckstation.DuckStation Once the installation is complete, you can launch the application from the activities overview. Post-Installation Setup When you launch DuckStation for the first time, you will be presented with the following setup wizard, where you can specify the language and default theme. When done, continue by clicking on " Next ". Next On the next screen, you'll be asked to provide a BIOS (or ROM) image to start the emulator and to play games. I won't be providing any ROM image links for legal reasons, but you can use an image from your own old PS1 unit or find one online. Next, it will ask you to specify the path of your game directory; just create one in your home directory and use that. If you have a game controller, connect it to your PC and map it according to your preferences. If not, don't worry—you can still use your keyboard and mouse. Finally, the setup is complete, and you can now exit the setup wizard by clicking on " Finish ". Finish That’s it. The DuckStation main window will now appear, displaying a list of all games located in the provided game directory. For now, I haven't added any games, so they are not appearing below. How to Uninstall DuckStation from Linux To uninstall the emulator for any reason, just open your terminal and execute this command: $ flatpak uninstall org.duckstation.DuckStation $ flatpak uninstall org.duckstation.DuckStation Wrap Up In this article, you learned how to play your favorite PlayStation 1 games on your PC using the DuckStation emulator. However, aside from this, there are other emulators, such as Ryujinx , that allow you to play Nintendo games on your PC. Ryujinx Many users still consider emulators illegal, particularly after Yuzu's case, but it's important to note that Nintendo took action against Yuzu for allegedly circumventing their software encryption. Yuzu's Nintendo took action against Yuzu So, playing games that you own on an emulator is perfectly fine, as long as the developer isn't violating any rules or regulations set by the company.

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