Aloha and welcome to Business in Hawaii with Reg Baker. We broadcast live every Thursday from 2 to 2.30 from the downtown studios of Think Tech Hawaii and the Pioneer Plaza. For those of you that are watching the weather, still kind of hazy and wet outside, but it's going to get better, I promise. So hopefully in a week or so we'll have the sunshine back and we'll be able to get outside and enjoy the sun again. This is a show that focuses on success stories in Hawaii, particularly of businesses and their owners. Every once in a while we have a guest on the show that helps support the successful business people and how their leadership skills are used to make the companies more successful and to be able to sell the product and basically have the lifestyle that they're looking for. Today we're going to have Rusty Komori, who is one of the most winningest coaches in the country and he'll explain more about what that means here shortly. But Rusty, I want to welcome you to the show. It's great to have you here today. Great to be here, Reg. Now there's a question that I've got and I've seen a lot of visibility. Your name and your picture has been out there so much and I've been hearing about Rusty this and Rusty that. I've got to ask this question, is Rusty your real name? Yes it is. Rusty is my real name. I have my driver's license that I can show you. I have my credit card that I can show you. Very good, I get it. When I was growing up people called me Reggie, but that wasn't my real name. And so I don't have the driver's license, but it's good. But Rusty is, and I've got a particular fondness for any first name that starts with R, because all of my children's are R's, all my brothers are R's, my father and my grandfather were all R's. So Rusty, you fit right into the family. I'm glad I'm an R too. Great. Tell me a little bit about yourself Rusty, you've been in Hawaii for a long time I think. Yeah, I'm born and raised in Hawaii, I actually played baseball and then soccer in my youth. And then I went to Damien High School and I started playing tennis in 9th grade, but tennis and soccer had conflicting seasons for varsity sports. So I actually chose soccer that freshman year while I continued practicing tennis. And then I was on varsity tennis for Damien High School, 10th, 11th and 12th grade. And then got a partial scholarship to Creighton University. And pardon me, where's Creighton? Omaha, Nebraska, the heart of America. Oh boy, it's a little chilly over there sometimes. I got to experience all the seasons, the change of seasons. And when I was at Creighton on a partial tennis scholarship, it was great just because I started tennis so late that I kept improving tremendously through college. And my intent was to go to law school after Creighton. I did take the LSATs and when I came back, I started teaching tennis at Wiley Country Club and Punahou School. And a lot of my adult tennis students were attorneys and they all had glasses and the glasses appeared like it was three inches thick. And I asked them what they did all day and they said, oh, we read all day. You're going to read all day. And I thought to myself, I don't want to read things that I have to read. I want to read things that I'd like to read. So that was the end of my pursuing law. And I just continued coaching and giving tennis lessons. Very good. And I would assume that that was a really good choice because you had an outstanding career as a tennis coach. Well, looking back, yes. Success, it's funny because you can never measure success going forward. Success can only be measured looking backward. And I was just in present focus at that time just trying to be the best tennis pro and tennis coach that I could be. And you've done very well at that, obviously. And tell me a little bit. Was it just a natural transition for you to just go from player to coaching? Or does it take a special personality or a person to do that? Well, I think we've all been on teams growing up, whether it's a sports team or a business team or a debate team or whatever. And you know that you learn from whoever the coach or the leader is, whether they're doing good things or they're doing bad things. And you kind of make mental notes along the way. And for me, I was really shy and introverted growing up. And when I was a sophomore on the Damien tennis team, I was number one on the tennis team and the captain. And it forced me to be in a leadership role where I would have to help my teammates along. And that started actually breaking me into that leadership situations. Did you find that by helping the younger players, the coaching and the teaching, if you will, actually made your game a little bit better too? Yes, it does. A lot of my former students and former players, when they start to do coaching themselves, some of them, they have a big appreciation of how it is on the other side and how stressful or how naughty they were at times when they were students or players. And now they're having to deal with the same situation, coaching some of the players that they are. And I think that's an interesting point. I forget who said it, but someone once said that if you really want to learn a topic, write on it or teach it. And you really have to know your stuff in order to be able to teach a certain subject, regardless of what that is. And it just makes those skills all the better because you're constantly practicing to get better at teaching. Oh, yes, I agree. And so that's one of the reasons why I used to teach and enjoyed it thoroughly. It's so nice to be able to see the light go on. And there's a certain satisfaction in taking a player and watching them progress and get better and better and better based on some of the tips and the thoughts that you're sharing with them. There is. I like it when the light stays on all the time. Yeah, absolutely. I think those power outages are no fun. It's very stressful. Very good. So now you've been doing the teaching thing for a while. You were out of Punahou for quite a while, weren't you? Yeah, I was a tennis pro at Punahou School for 25 years and head coach for the Punahou Boys Varsity Tennis Team for 22 years. And we were fortunate to win 22 consecutive state championships. That's amazing. And that's, from what I understand, one of the best in the country. Yeah, I didn't know anything about that until we were going for our 17th consecutive championship. And the media had told me that there's a swimming team in Colorado that has 16 consecutive state championships. So if you win, you and your team will be the national record, the longest streak in the United States in all sports. So I thought, whoa, this is, I don't want my team members to feel any unnecessary pressure there. But yeah, it's really great that we have that as an accomplishment. But it's great if we can have everyone try to lead in the way that we did and kind of achieve the things that we achieved. Sure. And not only did you hit the 17, but you went on to go all the way up to 22. Yes. So I guess it's going to be a while before anybody beats that. I would be happy if somebody reads my book and is inspired and motivated and then beats my record of 22 consecutive. That would make me happy. Well, and that would be a great testimonial for the book, which we're going to go into in the second half here. But it also, I think, would help propel book sales right through the ceiling. Now, you shared with me something unique about what you've done, 22 consecutive state championships.  Well, the state championship trophy is a huge, beautiful Koa trophy. And I've been presented it 22 times. And during my first year of coaching, I just made a decision that I would give it to a player that I felt really was instrumental in keeping, in helping our team achieve that state championship. Not necessarily the state champion or the doubles champion, but any player that really was a great team player that went above and beyond. And I had no idea that I would be giving out 22 state championship trophies. And to this day, I own zero. And it makes me proud because what would I do with all 22 trophies? It means so much more for me to have 22 players have it. Because when you look at a trophy like that, it's so beautiful. But there's a deep meaning behind how and why we won the championship. The sacrifice that you do as a player, that your parents make, that you do for your teammates. There's a really deep meaning when you look at what a trophy really means. Well, and sometimes it's the result of many, many years of practice. I agree. And so there's a tremendous commitment that's got to be made to get to that point. And for you to be willing to share that trophy with your players, I think that speaks very highly. I can't think of anything more rewarding for the players to be able to get one of those things. Oh, yeah. It's priceless when I present it to them. And it's just to this day, all of them, when I run into them, they'll talk about it. They said, hey, coach, we got the trophy in a really nice spot. You'd be proud. And I'm like, OK, keep dusting it. One of these days, you should ask for them to send you a picture of where they've gone. And then you can put it in your book. Here's some of the trophies. And here's where they're currently sitting with some of my former, you know, can I call them students or athletes? Yeah, students, players, team members, yeah. And that's excellent. So now you're no longer Punahou. You're doing something else. Yeah, I left Punahou in 2015. I just thought if, you know, I love Punahou and I love coaching the team. But every year, there's only 12 boys on the team that would have that experience. And so many people through the years were always asking, you know, you should write a book. Or what do you guys really do? You know, what do you guys do in practice? How do you achieve and sustain success? And so I thought, you know, if I stayed at Punahou, I probably wouldn't write a book because I would be distracted or just do some other things. But if I left, I would focus on writing the book. And that's what I did. And by writing the book, I felt that I could help all sports teams or businesses or organizations just in terms of the leadership to really help them maximize their potential and put them in better positions for success. Right. Now, the book is currently out there. You're marketing it. And we actually have a picture of the book that we're going to show on the screen here. But we're going to probably go into more detail in that book. When we come back from the break, there's an awful lot in there, a lot of leadership skills. You got some piece to success that we can talk about. And I want to save that for the second half of the show because there's a lot to talk about there. But in addition to writing the book, you're also out doing a lot of presentations and you're talking to a lot of different people and groups. Yeah. I'm doing a lot of motivational speaking. And it just seems that so many CEOs or presidents of companies or head coaches of sports teams, they're just thirsty for something new and fresh with leadership. And many of them have read the book. They love it. And they'll ask me to come and be a guest speaker. And it's funny because one of the things that I actually share with them is in tennis, there's no timeouts and there's no substitutions. When things get chaotic in a football game, you often see the coach call a timeout. In tennis, we have no timeouts. And in basketball, if you have a player playing and it's just not their day and they're struggling, well, you substitute them, you put a better player in. In tennis, I can't do that. There's no timeouts and there's no substitutions. So I really have to coach my players to coach themselves a lot when they're on the tennis court. And that's a very interesting distinction because I'm not sure that there's very many sports, maybe like boxing, where you don't have a timeout for boxing. But the rounds are only three minutes each. And so it's unique. I mean, it takes a special type of coaching skill, I guess, to make that happen. And it really requires the players to keep their head in the game, too. Exactly. Can't have any mental lapses. Mental lapses lead to losses. Yeah. And that's true in almost anything. Exactly. In business as well. Lost opportunities. It is. It is. We're going to take a short break. And we're going to come back in about 60 seconds. And we're going to get into the book a little bit more. So that's where the focus of the second half is going to be. This is business in Hawaii with Reg Baker. We're here with Rusty Komori, who is going to be sharing with us some of his insights in the book that he just wrote that is actually turning out to be very popular. So we'll be right back in 60 seconds. Hello, everyone. I'm DeSoto Brown, the co-host of Human Humane Architecture, which is seen on Think Tech Hawaii every other Tuesday at 4 PM. And with the show's host, Martin Desbang, we discuss architecture here in the Hawaiian Islands and how it not only affects the way we live, but other aspects of our life not only here in Hawaii, but internationally as well. So join us for Human Humane Architecture every other Tuesday at 4 PM on Think Tech Hawaii. Hi, everyone. I'm Andrea Gabrieli, the host for Young Talent's Making Way here on Think Tech Hawaii. We talk every Tuesday at 11 AM about things that matter to tech, matter to science, to the people of Hawaii with some extraordinary guests, the students of our schools who are participating in science fair. So Young Talent's Making Way every Tuesday at 11 AM only on Think Tech Hawaii. Mahalo. Welcome back. This is Reg Baker, business in Hawaii. I'm here today with Rusty Komori. We're talking about his new book, Beyond the Lines, that has turned out to be very successful in some leadership circles here in Halaululu as well as on the mainland. It's a book about leadership and some of the skills and some of the insights that he has after having 22 consecutive state championships being a tennis coach here in Hawaii. It's gotten so popular that not only are the business leaders involved and business people, but even the CPAs have picked up on this. And in the recent newsletter that the Hawaii's ICPAs have, they even called it Hala, the April 2018 edition, they actually have a book review done by one of our former Hawaii's ICPA chairmans and talked very highly of the book and highly recommends it. So we're going to talk about this a little bit. Rusty, give me a general thought. What triggered you to write the book? What was the objective here? Well, being in sports teams in my youth, I was thinking there's some really great coaches that I've had and there's some not so great coaches that I've had. And I just thought, why are there so many bad coaches or bad leaders in the world? It's because nobody taught them how to be a good one. They could have the right intentions. They could have the right perspective in wanting to be a coach or wanting to be a leader, but they just might not know how to do it. And so I thought that if I could write a book to really share what we did in our put a whole tennis teams, it would not only help sports leaders, but it would help business leaders. It would help parents. I have a lot of parents that have read the book that's saying, telling me thank you because it's like serving as a guide for their leading their sons and daughters. Whether they're in athletics or not, some of the basic concepts are going to be valid, right? Exactly, exactly. When I became head coach for the put a whole boys varsity team, my first priority was to develop champion athletes of character first and then great tennis players second. So you have to have the right priorities set first. Success and winning is dependent on the values, the disciplines, the principles that the leader has, and then how that leader instills that with their team. Now this is a comment coming from me. We need to send a few cases of this over the state legislature so they can take a look at it. Maybe there'll be some changes. But those are the character is something that we can never lose sight of. We have to keep our eye on that ball particularly because without character, everything's going to crumble at some point. Take a look at some of the stories that are out there today. And I've written about this. I have a column that I do with Hawaii Business Magazine. And we've looked at Uber. You remember about six months or a year ago? Uber had a major problem because of some of the things that were going on within the inner circle there. There was a breakdown in the ethics and the character of the people that were running the company. Now they've addressed it, it's been fixed, and they're moving on, and that's great. But that's just an illustration or example of what happens when you lose sight of maintaining that ethical or character compass. Yes, having integrity and ethics is huge. I mean, you need to have integrity and ethics. And that's part of your character. You don't want to win at all costs. You want to win correctly. You want to win the right way. You want to succeed with having a great character with not just yourself, but with your whole team. Well, and that also motivates the entire team. I think, and correct me if I'm wrong, but any leader, any coach that has the high moral ground, their players, their employees are going to be more comfortable following that lead. If they ever question, I guess, the moral character of their leader, there's going to be issues. There's going to be problems with that. They're not going to stick around. Do you think that's a fair assessment? Oh, you're totally right. If the leader leads correctly and consistently with the right values, principles, and disciplines, then success and winning is a byproduct of what you do every day. And some of the problems that some of these leaders have is these leaders have values, great principles, great disciplines, but they don't know how to train that or teach that to their team members. There's a disconnect. And that's what this book is really helping them with, is to try to really connect with the team members to really help everyone individually, which will help the whole team collectively. See, what I'm hearing is that this is not only a book on leadership, but also corporate culture. I mean, because once you get the leaders to take a look and understand what you're trying to communicate, then it changes the whole corporate culture of that entity. And that's pretty much what we're talking about, I think. Yeah, it's a culture of excellence. And the leader sets the tone for the environment. If the team members feel safe, if it's fun, if it's somewhere that they love to be at, look forward to going, that's the leader's job to really create that environment. Now let's talk specifically about the book a little bit. Now I don't want to give away too much that's in there, because otherwise people won't buy the book. But give us a taste. What are some of the basic concepts that you're communicating? Maybe one or two of the really gotcha ones that catch people. Yeah, so the basic, the biggest parts of the book is the four P's of success and the eight keys in achieving and sustaining success. So the four P's, the first P is people. You know, are you good with your people? Do you have empathy for them? And you as the leader might have empathy for them, but your team members need to feel and they need to know that you do have empathy for them, that you actually care about their own improvement, their own values and what they want to do. And so, you know, focusing on people is the first P. The second P is purpose. What is our goal? What is our mission? What are we trying to accomplish together as a team? And can I give them a vision, a clear vision for this mission? The third P is process. Can I have a detailed process that I can share with my team members about how we're gonna achieve the goals that we want? Oftentimes the leader has the process, but they might not share it with the team members. So the team members might be wondering why the coach or the leaders making decisions or why is this lineup a certain way or whatever. I like to share everything that I'm doing with the team. And if you focus on people, purpose, process, that equals the performance. And that's the results, that's the productivity. And those four P's are the general framework and then the eight keys provide the details in how to really lead your organization. You know, what's really interesting, Rusty, is that I'm looking at it from a business angle or perspective. And what I hear are things that kind of remind me of having a mission statement and having a value statement and having the goals and objectives and having all of this that's communicated to everybody to make sure everybody's behind it, that they believe in it, that it gives it purpose and where they wanna go. You know, so I can see where there's an easy jump, you know, from the coaching athletic world into the business world, because a lot of these things people are already familiar with, but they don't maybe appreciate how important they are. No, I totally agree. And you're so right on that. One of the first things that I would tell my team when after tryouts are done is to welcome adversity, that we're gonna have major challenges, we're gonna have big time adversity this coming year. So I don't know when it's gonna happen, but we're gonna have to be prepared for it. And I would tell them we need to look forward to that adversity, to that challenge, because if we can get through it, we're gonna become better, stronger and tougher for going through that experience. And so a lot of that is just the mindset in looking forward to challenges rather than hoping that it won't happen, which inevitably it will. You know, and it's that perspective.  How are we gonna address this challenge? It's just a different shift in perception. Yeah, totally. You know, it's the mindset. The brain controls the body. And if you can control your thoughts, your hands and your mouth that I would tell my guys, then we have a chance in controlling the tennis ball. And if we cannot control our thoughts or our hands or our mouth, then we're really shooting ourselves in the foot. In tennis, you know, a typical tennis match might last two hours, but the actual ball, when the ball is in play, is only in play for about 15 to 20 minutes. So what you're thinking during the other one hour and 40 or one hour and 45 minutes greatly impacts those 15 or 20 minutes that the ball is in play. I know that there's an analogy that I like to repeat. Different sport, but in golf. And they say the biggest distance on any golf course is what's between your ears.  That's the difference between winning and losing. It's the couple of inches between ear to ear. Now, the book, it's not really that thick. It's only, it looks like maybe 150 pages or so. So would you say it's an easy read, but it's powerful and a message that it's sending? Yeah, it's very easy reading. This is how easy it is, Reg. I have a fourth grader, a fourth grade student that's read the book, that absolutely loves it, is telling me all kinds of examples in the stories and how it relates to her. And I have CEOs and presidents of companies that have read the book that are calling me or emailing me saying how impactful and meaningful this leadership book is and everyone in between. And I just feel so thankful and grateful that the book is improving countless people's lives. Well, and I know I joked about this earlier, but this is in the middle of taxis and it's a very challenging time. But for the CPA community to pick up the book and to get into it and have a book review on it, right in the middle of tax season, that says a lot, at least in my book. We're gonna be wrapping up here. We've got about 30 seconds. Any final words that you'd like to say or any events coming up that you'd like to promote? Well, basically the book is available on Amazon and Barnes & Noble. And from what I understand, it got sold out a few times. It got sold out three times on Amazon today as well. But which is a great thing. And the book is also available on my website, RustyKomori.com. And yeah, I'm just so excited to be doing a lot of inspirational, motivational speaking for sports teams and businesses. It's great to have you in the community. It's great to have you here in Hawaii helping out the business community. I just can't thank you enough. We need more of this. This is a true success story. So it's great to have you on the show. Thank you, Wrench. This is Business in Hawaii with Wrench Baker. We broadcast live every Thursday from 2 to 2.30 from the Pioneer Plaza in downtown Hololulu. Want to thank Rusty Komori for being on the show today. He's got a very busy schedule. And I would recommend getting the book beyond the lines. There's a lot of good information inside there. Thank you for the ThinkTech staff for doing a super job today. Until next week, aloha.


The Adventures of Sam Spade, detective, brought to you by Wild Root Cream Oil Hair Tonic, the non-alcoholic hair tonic that contains lanolin. Wild Root Cream Oil, again and again, the choice of men who put good grooming first. Uh, uh, Foggy. Did you go in? Coincidence. I was just reading my new library book. And it's all about a body in the water, pushed over a cliff. And there's a strangest girl in it with a, with a strange mother. And she drinks the girl and runs away with a chauffeur that rich people. They can't do that. They're stealing my materials. Oh, no, Sam. No. It's by Owen Fitzsieven. He's very well thought of. Mother always understands his plot. Not tonight, she won't. Staring our angel, I'll be right down to dictate my report on the critical author, Caber. 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And now with Howard Duff starring as Spade, Wild Root brings to the air the greatest private detective of them all, in the adventures of Sam Spade. Come on in, let's get this over with. Can you wait till I finish this chapter? Let's get the page to go. The detective had just found this girl in a sorted rooming house. He had this fight with her boyfriend and buoyed him, and now butter wouldn't melt in her mouth. But I don't trust her. What's the name of the book? Morgue Fruit. His last was a spindly stiff. That was about this neurotic nurse who was in love with her employer. Effie, how long have you been reading this kind of trash? What's not to make this character live? And I love his detective. He's real hard-boiled like an dachel hammock. Dachel hammock? Mark your place and come here. All right, sir. Ready? Yes, sir. I can hardly wait. That's the way I like it, eager. Depends on the chapter, I mean. I wonder what she's up to. She's guilty, of course. Of course, but why not? You can read it when I'm finished. Oh my goodness, we've got a report to get out. And here we are, chattering about books. Date, August. I will give the date. Yes, Sam. Uh, date? Hello there. To a missing persons bureau, Saphiciska Police attention, Sergeant Schwartz from Samuel's Bay, licensed number 137-596. Subject, Gabrielle Leggett. Here, Dave. I should have handed it over to you at the start, but you know me, I'm greedy. I cashed the cheque she'd sent me as a retainer without consulting my better judgment, gave the money to Effie to pay bills without batting an eye, borrowed a dime car fare from the corner news boy without collateral, and arrived in front of the Leggett mansion on Nob Hill without the foggiest notion of what I had been retained for. I'm good to Leggett, Mr. Spade. It's about my step-daughter, Gabrielle. She's been missing since the funeral. Uh, whose funeral was that, Mrs. Leggett? My husband, Gabrielle's father. That was nearly three weeks ago. She came to me afterwards and said she was going down to Casada to our country place for a few days that she wanted to be alone with her grief, but I discovered that she never arrived at Casada. Do I make myself clear, Mr. Spade? Yeah, except for one thing. Why do you want her back? First, she may do something to disgrace me. She'll undoubtedly try her best to do so. Secondly, unless I get her signature to some papers, in accordance with her father's will, I can't go on living in this house. Furthermore... That's okay. You've convinced me. Now, when she left, what did she take with it? Just one piece of light luggage and her liquor case, of course. She drinks, you know. Well, it's not my place to disapprove. I merely thought it might help you to know. Well, we could case all the boys in town, but it'll take a lot of time and a lot of money besides them on the wagon. Well, you might talk to Eric, my chauffeur. He drove her to the station or says he did. Where do I find him? Let's see. Ten o'clock. He'll be loitering down the hall somewhere in the neighborhood of the linen closet, helping the upstairs maid fold the sheets. I'd knock first, if I were you, and avoid embarrassment. Thanks for the tip. Oh, mine, if I have a look at your stepdaughter's room. Eric will give you the key. I'm not a loud one. There he is. It's okay, Myrtle. Anytime. You Eric? Collinson. What can I do for you? I'd like the key to Miss Gabrielle's room. You the law? Why? You expecting some? The old lady's been threatening the Yelp cop. She decided to whisper instead. Oh, Private Dick.  Okay, I'll let you in her room. Come on. Mrs. Leggett says she drove Gabrielle to the station. She says that, does she? Isn't that what you told her? I'm not telling you what I told anyone. Search yourself. After you. What's eating you? Nothing at all. Just want some privacy. Oh, now wait a minute. I'm responding. Go help Myrtle. Give me those keys. Oh, listen. You can't. Hello. Hi. Let me in. Don't have your lights on. The room was, shall we say, untidy. The mirror dressing table was chipped around the edges and the rain's held a scouter across it between two polo pony bookends. It was a mess of books. Three odd volumes of a Harvard five-foot shelf.  I picked one up and opened it to the title page. It was called Morgfruits. And it was by Owen Fitz-Steven, author of the corpulent cadaver, the spindly stiff and the kiss off. It was autographed to the author's great and good friend, the late Edgar Leggett. The signature looked familiar, but it didn't look like a lead. Neither did anything else in the room. I started to unlock the door with the key on the ring. I grabbed away from Eric and the light caught the smooth side of a Christopher medal. It was engraved for Eric Forever Gabby. When Forever Eric went off duty that night, he went across town. The trail ended at a crummy broken down rooming house out in the film house. He let himself in with a key and climbed the stairs. I waited until he was out of sight. In more time than it takes to tell, the door cracked open and a nose that could only belong to a landlady raised it out at me. She was, uh, gumming a sense in. What do you want? They, uh, get settled in all right? They ain't nobody settlin' in on me. Never touched me. You got me wrong, Mom. I, uh, meant the newlyweds. Did they, uh, raise the rent money all right? Oh, damn. Raise it and spend it. She's a Dick Smither. Dick Smither. Socks it up all day and throws a dead shoulder out the window. And they call it honeymoon. Uh, ex-husband, darling. I came to figure the back alimony out. Well, good to me. I'll see she gets... Oh, no, you don't. No, no! Don't you come pushin' in here. Quiet. After hours. Don't allow callers in here after 10 o'clock. House rules.  Well, I don't. What's their room number? Now give it to me or I'll shake it out of you, Barlin. 212. 212. And if I want for these new uppers, I'd let you try it. Oh, is that what those are? Uh, thank you, Grand Duchess Marie. Smart Alec. No wonder you can't hang onto a woman. Yes, all right. You're sober to drink. I did not. Alimony's so good. Weston Union. Told you to stay away and I'll beat it. Eric, what is it? Uh, look, Eric. I don't want any trouble, but I'm comin' in. Over my dead body. Eric! Get back in the room, Gabby. Now look, I won't let you hurt her, so... Now look, Collinson. Don't make me do it. I don't want to. Okay, I'm sorry. What have you done to her? Nothing in the bucket of cold water can't cure. Sit down. I want to talk to you. Who are you? Sam Spade. I'm a private detective. Your stepmother hired me to find you. Oh. You know why she wants to find me? Do you?  To kill my father. Now she'll kill me. Can you prove that?  She could drink three quarts of brandy in any evening. Do you believe a man like that could die of heart failure? Frankly, I could. Now she's starting to think how to talk about me. She wants to railroad me to the insane asylum. Do I seem crazy to you? No. A little nervous, maybe. This idea you have about your father's death. Talk some more, will you? All right. I'll tell you the whole thing. I've got to have a drink first. I can't get to the top of it. Give me a hand, will you? Sure. Now you need a corkscrew for this one. Yeah, I think there's one down there in the cupboard. I don't see one. Back in the corner. There's a father. There. No, there's nothing. Hey! I dreamed I was a character in a detective story. The title of the story was Morgfroth. In the author, a man named Fitz Steven, was trying to figure out a way to turn me into a red herring before knocking off his number one suspect.  That's what he thought. The makers of wild root cream oil are presenting the weekly Sunday adventure of Dashel Hammett's famous private detective, Sam Spade. Who's on good grooming? If you want the well-groomed look that helps you get ahead socially and on the job, listen. Recently, thousands of people from coast to coast who bought wild root cream oil for the first time were asked, how does wild root cream oil compare with the hair tonic you previously used? The results were amazing. Better than four out of five who replied said they preferred wild root cream oil. Remember, non-alcoholic wild root cream oil contains lanolin. And here's the announcement we promised you. Now you can get wild root cream oil, America's leading hair tonic in a generous new 25-cent size on sale at all drug and toilet goods counters. It's also available in larger economy bottles and the handy new tube. Get wild root cream oil again and again the choice of men who put good grooming first. By the way, smart girls use wild root cream oil, too. And mothers say it's grand for training children's hair. Go back to the critical author caper. Tonight's adventure with Sam Spade. I came to and it came to dawn and I was still a character with a detective story and I felt more like a red herring than I had in my dream. I had dragged myself across my own trail and wound up no place. My quarry had fled, leaving nothing behind but empty bottles with fingerprints on them. I lifted a few and hustled over to the Bureau of Identification. Half an hour later, I got the report. They were mine, all mine. I wondered what a detective novelist would make of that. I decided to find out.  He was plowing the same field for literary material and we pulled forces. I got more out of the combination than he did since he knew the spoof racket inside out. I cleaned up my job in a couple of weeks and we parted friends. His San Francisco apartment was on the sixth floor of the St. Mark. He was standing at its door holding out a lean hand to greet me when I got there. Yeah, they're looking fit, Sam. Little red in the face. That's the red herring I ate last night. How's the literary grip go? You haven't been reading me? No, where'd you get that funny idea? Oh, it was something in your tone as in the voice of one who has bought an author for a couple of dollars.   You autographed the book for Edgar Leggett. Oh, yes, yes. Morgue fruit, distressingly prophetic. What do you know about that family? How well do you know the girl, Gabrielle? Well, quite well, since she's a duplicate of her father. She has brains, but there's something black in her. Something she doesn't want to think about but can't forget. She's a neurotic who keeps her body sensitive and ready. I don't know what for. While she drugs her mind with drink and lunatic notions. Yet she's cold and she's sane.  I hope you don't think any of this stuff means anything to me. Oh, yes, I remember you now. You were always like that. Tell me what's up while I try to find one syllable words for you. You know the fella that drives for him? Oh, Eric? Mm-hmm. Well, he was released from Folsom and Leggett's custody when he was 18 years old, murdered his father. Nice kid, what about it? Mrs. Leggett hired me to find Gabrielle. I found her with Eric in a rooming house out in the Fillmore. She begged me to save her from her stepmother's murderous schemes, and then she knocked me cold. Well, that's trivial. I've been thinking of the Leggett family in terms of doom on you. Bring me a piece of Jim Crackery out of O'Henry.  Or, no, that won't do. Not sufficient motive. Murder has to have a motive, you know. Why? She's insane, isn't she? I wonder. Are you saying that carelessly or do you really think she's off? Well, I don't know. She's got a kind of a wild look about her. Her eyes shift from green to brown and back without ever settling on one color.  Are you who make your living snooping, sneering at my curiosity about people and my attempts to satisfy them? No, it wasn't different, O'Henry. I do mind with the object of putting people in jail and I get paid for it, though not as much as I should. I do mind with the object of putting people in books and I get paid for it, though not as much as I should. Yeah, but what good does that do? What good does putting them in jail do? Relief's congestion. You put enough people in jail and cities wouldn't have any traffic problems. And that's fine. All you have to do is wait till one of them kills the other and put the survivor in jail. That's simple.  Perhaps they both have plans. Both Gabrielle and her step-mother. Looks as if you'd have to guard both of them. I think I'll settle for my client. As far as Gabrielle's concerned, her husband ought to be able to watch out for her. What? All right. Now, there you are. You didn't tell me anything about that. Lord knows how much else there is you haven't told me. Pardon me. Don't go away. Telegram, sign here. Oh, thank you. There you are. Thank you, sir. I wonder what... Good Lord, this is positively corny. Listen to this, babe. I appeal to you as a friend of my dead husband, calm immediately, sunset, hotel, quesada, trouble, danger, and if you do not communicate, Gabrielle must not know. Sign... Go to Leggett. Spade. Did you have this wire sent to me as a prank? I was just going to ask you if you sent it to yourself as a prank. I have it. The key to the whole thing. It's a red herring. I didn't think that Stephen would be able to hold out very long against his professional curiosity I caught the next bus for quesada. Quesada is a one-hotel town pasted on the rocky side of a young mountain that slopes into the Pacific Ocean some 80 miles from San Francisco. I got there at 11 something that night, stepped down from the bus and crossed the street to the sunset hotel. Mrs. Leggett registered here. What's your name? Oh, she left a message for you, said for you to wait right here and don't leave till she gets back. Where was she going? It was probably over visiting with her daughter and her new son and her new over through the cove. How do you get there? You never be able to find it at night unless you went all the way around by the east road, not then I'm sure unless you knew the country. How do you get there on the daytime? You go down this street, you take the fork on the ocean side and follow that up along the cliff. It's easily enough found in the daytime but you're never in the world. It's the first time. I waited until morning.  I found the road out to the point but it had never really been a road. The side of the ledge became steeper and steeper until the path was simply a narrow shelf on the face of the cliff. The cliff that sheared off 150 feet or more to rattle out into the ocean. A breeze from the general direction of China was pushing fog over the top of the cliff making a noisy lather of seawater at the bottom. The cliff was steepest. I checked my cigarette over the edge and watched it spin downwards and that's when I saw it. They go way steep into the Pacific to lift the body. I got my hands under the armpits found solid ground for my feet and dragged it up beyond the high tide mark. It was Gertrude Leggett. Somebody came staggering down the beach to meet us. You're dead? Yeah, Gabrielle, she's dead. Four of the witches are dead.  Sit down there. Sit down. What's the big idea? Don't you know I was sick? Somehow I don't think you're that sick. I think you could make some sense. Sense? That's a laugh. You don't know me. I've never been able to think clearly the way other people do. No matter what I try to think about there's a fog that tries to get between me and it. You understand how horrible I can become going through life like that? Nuts. Nobody thinks clearly no matter what they pretend. Thinking's a dizzy business. A matter of catching as many of those foggy glimpses as you can and fitting them together the best you can.  You've been so busy trying to prove that you're nuts that's the one you haven't really driven yourself nuts. How do you know I haven't? Because you're too anxious to admit it. All right, I'm sane if you want it that way. I'm just evil. There's something black inside me. What was that again? Something black. Everybody knows that about my family. My father too. Who told you that? I always knew it.  But I know better. I know how to open the door where she keeps the gun.  I know how to open the door where Gertrude lies on mother's bed. And we play killing the witch. And she comes in in the night and bends over my crib. And she's changed herself. So she looks like mother instead of a witch. But I know better. And I hold up the gun with both hands. It's very hard to pull with both hands. It's very hard to pull with triggers. But I must do it or the witch shall eat me up.  Now listen to me. You were beginning to make some sense. I don't run away from it.  That's your stepmother? She was my nurse. She married father. Not so fast.  Four. Four and a half. Did your father know about the game with the gun? No, I don't think so. Did anybody? Gertrude said I must never tell anyone. I never did. Not till I grew up. I was with Owen Fitz Stephen. I had a lot to drink. I told him after that he began seeing Gertrude. When finally my father died. But it didn't do her any good. Because Owen really loved me. Now watch it. Now let's get this straight. You'll have to straighten it out again later on with a doctor to help you. This is to help me.  Then she filled you full of ideas of guilt and fear so you'd keep quiet about it. When you told the story to Owen, he blackmailed your stepmother to knock on off your father. That made you feel responsible to his death too so you ran away. Gertrude said I killed her too. You might, but I doubt it. Now try and remember. Was Owen up here tonight? I thought I heard his voice. But I hear voices sometimes. I'm hearing it again. Listen. Do you hear anything? I didn't hear anything but the wind and the beat of a surf at first. When I did hear the voice, I sent Gabby for a doctor before I investigated. He was pretty badly mangled in the rocks. He'd fallen nearly as far as he'd pushed Gertrude but was still alive. I made him as comfortable as I could and finally he opened his eyes. Oh, Sam. You messed yourself up good. Yeah. No more rocks for me. Not unless you make Alcatraz.  Thanks, Owen, but I never had any theory. Whole thing dropped into my lap. Don't be too sure of that. On the standard present, I admit nothing. Later on, if I'm forced to, the very number of my crimes will be to my advantage. On the theory that nobody but a lunatic could have committed so many. Well, there's not so many. Only Gertrude, your co-author of the murder of the late Edgar Leggett. Nonsense. Crimes and crimes dating from the cradle. Even literature should help me. Not your own books. Why not? Didn't the critics agree that the spindly stiff bore all the marks of authoritarian degeneracy evident in son to save my sweet neck? And I shall wave my mangled body at them. A ruin whose crimes and high heaven have surely brought sufficient punishment upon him. Yeah, you'll probably make a go of it. Legally, you're entitled to beat the jump of however anybody was. Legally? You mean insane? Tell me the truth, Sam. Am I? I think that's what they'll say. What's that? Spoils everything. It's no fun if I'm really cracked. No fun at all. This goes to show, doesn't it? No, there you go again, Effie. I mean, if anything like that happened in real life, you wouldn't believe it. You mean if anything like that happened in fiction? Oh, no. The author is never the guilty party. Well, this author was. But that's not fair. You're right. You're right, Effie. He shouldn't be even a suspect. Maybe a red herring, but... Type that up, Effie. All right, Sam. Anything else, Sam? Yeah, phone the drug store and order some red herrings. I mean some aspirin. More and more folks are turning to famous Wild Root Cream Oil every day.  It grooms your hair neatly and naturally the way other people like it.  So join the millions with handsome hair. Tonight or first thing tomorrow, ask at your drug or toilet goods counter for Wild Root Cream Oil. Also, ask your barber for a professional application. If you've never tried it before, get the generous new 25 cent bottle just introduced. It's Wild Root Cream Oil's get-acquainted size, and once you've made the acquaintance of Wild Root Cream Oil, you'll find you've made a lifelong friend. Come on in, twigletoes. Well, here it is, Sam. And I like it even better than morgue fruit. You did. I mean, it's not so realistic. I like a romantic type story myself. You do. Lots of atmosphere and psychology and those. Oh, you've got to have those. You really should be a writer, Sam. Well, you think so? Of course, detective stories don't pay much. Oh, that's true. But if you write enough of them, and look at all the material you've got. No good. Never do for fiction. But, Sam, there's already that radio series, The Adventures of You Know Who, Sunday Night. That's what I mean. I don't make a penny out of it. Well, it's your own fault. Sam, I don't want to seem critical, but if you played your cards right, you could have owned a piece of that show. What? And follow Blondie? Go home, Effie. I think I will, Sam. Just curl up with a good book. All right.  Well, when you find out, don't let me know. Oh, you know you can't wait. Well, I'll take it. Good night, Sam. Good night, sweetheart. The Adventures of Sam Spade, Dashel Hammett's famous private detective, are produced and directed by William Spear. Sam Spade is played by Howard Duff. Lorraine Tuttle is Effie. The Adventures of Sam Spade are written for radio by Bob Tallman and Gil Dowd. Musical direction is by Lud Gluskin, with score composed by Renee Gerrigank. Join us again next Sunday when author Dashel Hammett and producer William Spear join forces for another adventure with Sam Spade brought to you by Wild Root Cream Oil. Again and again, the choice of men who put good grooming first. This is Dick Joy, reminding you to... Get Wild Root Cream Oil, Charlie. It keeps your hair in trim. You see, it's non-alcoholic, Charlie. It's made with sooth and lanolin. You better get Wild Root Cream Oil, Charlie. Start using it today. We'll have a tough time, Charlie. Keep an eye on the galley. Get Wild Root... This is CBS, the Columbia Broadcasting System.


it it may have to be enough. And you know, I'm certainly excited about, you know, the people we have behind Garrett Cole, from a depth standpoint, from a number of young guys getting opportunities to pitch this year and showing a lot of promise. Look, I mean, you know, we still have a couple of months for the offseason unfold and I know cash is working hard to try and add pitching where he can. But you never know how in the end that's going to flush out so you've got to be prepared to go in with what you have and, you know, we're obviously, you know, really excited about some of the things we were able to see from from the development of the Davey Garcia's and the Clark Schmitz and Nick Nelson and Michael Kings of the world to, you know, obviously getting savvy back at some point to Domingo Hermon pitching himself back in into the conversation. So there's a lot of feel like we have good depth. Hopefully we're able to add to that bunch and and even maybe even see some more young guys emerge and put their names in the in there. You know, with the cesses and the wise ago who we know can give us length and possibly be starters for us. So we have a lot of good options, a lot of talented options. We'll see where the offseason goes as far as what we're able to add to kind of supplement that behind behind Garrett. I forgot money. And money, of course, who, you know, I think got us all excited this year and, and now looking forward to him taking that next step and going back into a regular full season and seeing what he builds on from there.


The results of this study suggest that Bruxism is common among children aged 7 to 10 years old. Children with Bruxism are more likely to have poor sleep quality, sleep for less than 9 hours per night, feel tired or pain in their facial muscles when they wake up, and experience daytime sleepiness. This article was authored by Eliezer Gomez-Alves, Daniela Malagoni-Fagundes and Merqualo Ferreira.


All right. Hi everyone again, welcome to opening for summit We're gonna talk about how companies use Loki to run their business and I'm Maria Bradshaw from Red Hat And I'm here with one of our customers Excellent So first I would like to speak a little bit about something that I really like which is all the customers that we have and all the Different use cases of how the technologies that we build here and in other communities come together to solve real-life problems The talk today will be a bit heavily focused on telco because I'm joined by Proxima's so that makes sense But obviously open stock is not just for telcos At Red Hat our open hybrid edge vision extends from the data center to the cloud all the way to the edge and it's still at the heart of Contributing collaborating and being part of open source communities and then distributing that Into enterprise ready software that can be used at many many different Places over the world hundreds of companies rely on that to run their business and We hope to continue to power a lot more innovation going forward As you can see open stack is a critical part of it So the physical layer, but it is part of a broad ecosystem of technologies that come together in addition to an ecosystem of partners That are not pictured here our customers really drive the roadmap that we built and Their use cases and their needs and the next needs of their business Drive the requirements that we bring together to the communities and continue to drive forward on their behalf Some customers are also active participants of the community and we love to see them other customers just through lack of resources or You know maybe haven't been exposed at really collaborating and contributing in open source communities rely on red hat and other vendors to do that we're very happy to have them and To help bring the technology forward It's a little bit of a bragging slide We don't do this often But the in the telcoside the 4g story is been won completely by open stack and that's something that we should be very proud of 4g transom open stack and In 5g core is also heavily powered by open stack as well those networks and the push on those networks and the weight of the Additional traffic that comes to that network is what's going to continue to drive the growth and the scale that we have seen in our partners and our customers Of course, it's not just open stack. We use Kubernetes as well. That's why you see open shift represented there because again This is a red hat slide, but as well as other partners and customers We have some leading operator transformation running multiple large-scale production deployments today and The way that they run that is not just open stack not just Linux not just Kubernetes is a combination of those now the open stack foundation calls Loki I call it a background him because it doesn't always represent that same order of Deployment but rather a mix of them is what makes them kind of come together in different configurations Rehearsal commitments to open stack still continues strong and again our commitment to the distribution that we ship as a product Is there but really that is driven by our full commitment to the community and the contribution that we do upstream So I'm very happy to see actually some contributors here. So congratulations to you And I'm happy now to pass that on to our customers. So Alan, would you tell us some more about your story? Thank you, Maria so indeed I'm gonna share about what we've been doing at Proximis in terms of Open shift and open stack deployment our experience and the different challenge and the type of Deployments that we are running currently So first maybe start with Presenting our company so Proximis we are the main provider of digital services and communication services in Belgium and in fact also in the mainland looks and some international market We provide the typical Telecom services so fix fix network mobile network TV platform ICT services for corporates But we are also a global voice carrier and one of the leader for mobile data services in the world Myself so I'm I'm leading the infrastructure solution architect team at Proximis and previously I was leading the Tech of Cloud team which has been building the whole solution together with the different vendor One thing important to know is that we we've been a full stack team meaning that we were taking care of the full Deployment meaning when I talk about the storage part the server side the open stack and all the shared services on top of it So how did it started in fact a few years ago Proximis launched a number of ambitious Transformation program and there were two interesting transformation program for us the first one was about Deploying what we call an IT private cloud the goal there was to provide a platform where our Developer our application will be deployed much faster than what we used to have previously and then we will embrace everything related to Kubernetes container way of Of Deploying software and then we had a second Program which were more related to the network transformation that was happening at that time the old NFV story where the goal was to Deploy telco services on Commodity server what is often reference as telco clouds with the different telco providers Some figures. So we are running currently a 15 open stack cluster each time we've associated Self cluster. It's around 900 computes three petabytes of self storage 50,000 virtual CPU and Both 4,000 VMs We use typically all the NFV tuning which are available and required for the different workloads We have everywhere cpu pinning isolation PCIe pass through for some use case SROV when we need some extra acceleration Next to the open stack. We also have an important open shift deployment We run a 10 open shift cluster always hosted on open stack and self storage and There we have around 400 worker nodes 10,000 pods 40,000 container and all of these for 89 application and these application are decomposed in around 800 micro services We also add in the program the ambition to virtualize as much as possible Everything we could so meaning that we we took the decision from the start to virtualize all the load balancer The firewalls the DNS the network tapping solution and so on all of these on top of open stack So how do the different clouds looks So the open shift cloud each time we run a dedicated Open shift cluster for IT services where we also in fact Four types of services. We have web services Mobile application which are used by our customer called center application and some middleware services Which are used completely in the ecosystem of of Proximus The main challenge we we we add with this kind of deployment was All the effort required for application refactoring for many of our teams It was the first experience with containers and Kubernetes. So it was about adopting a new Way of working if you look at the stack that we have it you will find back in the next slide Typically the same thing we always have a Cisco is the end on the bottom then we use a number of server commodity mainly HPE server or Dell server on top of it We have an open stack and self deployment and then we have For some cloud you will find the open shift and then a number of shared services At the other side we also have a connection with a corporate cloud where we run most of our workload then on VMware for more traditional workload and some network appliance then you've got the telco cloud deployment which are With the same basis But they are dedicated to network services We have a type of deployment for voice services and another one for data and other type of services The main challenge for this kind of deployment has been that Even if we deploy virtualize it's really still looking Very much where the same as when this workload were deployed on on bare metal So there is a refactoring of this application, but they come most of the time with plenty of NFV tuning requirements If you look we we have the same basis and then the type of services that we deploy are the typical Telco services so the IMS core with all the different NFV voice application server some SBC from oracle CIP firewalls recently the 5g UDM and then we are in the process of deploying some voice added services together with HPE on top of it We have what I explained previously all these short services that we virtualize as well So Palo Alto firewalls, we have the Octavia load balancer But they are in fact part of the open stack deployment We have AV load balancer info blocks DNS services and then Ixia cloud lens Which we are using for tapping for a very specific use case where You know in the telco industry it's always very interesting to have tapping to be able to do some KPI monitoring and so on But of course if you virtualize everything you have some use case where the different VNF are running on the same compute And then we cannot do the tapping the usual way we used to do on the network So we need to do it on a virtualize environment. That's where you we are using these Ixia cloud lens Tapping and then we have a very similar deployment for data TV and public micro services The main difference here is that you you've got also some special storage that we had to fit in our deployment for very specific use case where we had I think a S3 requirement where they could only use one index and the only vendor who could who could provide this was a you away When you see a number of Deployments, so we have the 5g core. It's not completely live because there is still this combined core Which is being deployed at the moment, but we also have email services SD one controllers machine-to-machine solution TV internet streaming. It's a very specific use case for some niche program not for the large one because for this we are using dedicated Deployment on some bare metal for this kind of workload and then of course for some microservices that we are Delivering to our customer. We also use an open shift cluster on this on this open stack It's typically for for two types of workload. We have what we call the TV back-end so everything Things like VOD recording TV guides and so on which are virtualized and on microservices and we also have the Proximus website portal and web services that we run on open shift as well So what have been the challenge and the Opportunity the tuning that we've been doing with our experience The first main challenge was the team skill set to take the responsibility of this type of cloud at the start of all the initiative the Responsibility was shared between different teams. You've got a traditional what we do for other project The network team is busy with the network side the server Team is only looking at the server side and then you have some middle team as well But this made it very difficult to progress in the project time because you need all this integration between the different part so we took very quickly the decision to create a multidisciplinary team where The responsibility we've shared was shared with the different part of the stack We also took the opportunity to work in a DevOps approach where every engineer was Asked to be to go a little bit beyond their circle of comfort So typically the network engineer would also need to know about open stack how it works Basically to be able to do some basic troubleshooting and also help with the integration The same effort was asked for The server guys which also need to be able to understand how the networking integration was working and help with some other problems So it was very interesting for everybody in the team very intense and a lot of learning for everybody that was involved The second Important challenge is what you you certainly heard in other presentation if you upgrade story If it's a telco cloud and you need to upgrade it becomes very quickly a challenge because these application are supposed to run 24 by 7 So some of the things that we've been doing is that we split of a cluster to try to align as much as possible the SLA So on one side what that you saw we have a voice of services Which are having the same kind of SLA and then we have over services which have a more relaxed SLA and What we also have done is that We consider every of these major upgrade as an opportunity to do a site resilience Which is also a typical requirement for telco provider. You need to prove to the regulation So you need to prove to the regulations that you are able to do site Isolation that you are able to run on one site and provide the type of Resilience that is expected from a telco provider It's quite a via but we still have a commitment to do it yearly each of the cloud is Isolated for several days to be able to do any kind of upgrade. It can be an open stack upgrade It can be a major network here organization and what happened is that we have a few days to do the other isolation to a safely degrade the service to make sure that the customer are moved to the second cloud and Then we do our activity and then again a few days to come back with the traffic But of course it requires a strong partnership because when we do this kind of intervention We need all the vendor to be available to be involved to to help us with the preparation And also to be able to react very quickly if anything happened because of course we cannot run on one site for a very long period another main Challenge is about aligning all of these so it's we we have all these different Part of the stack and we need to make sure that they are all compliant and that We don't Go into a trouble. So what we've been doing and I think it's it's very common We use infrastructure as a code approach Everything is deployed as much as possible with orchestration not only The open stack part but also the network part the shared services on top of it and some of the application Are also completely orchestrated to make sure that we have a baseline that we can Effectively reproduce on the different cluster and that we don't have a surprise or mismatch in the configuration What we've been also doing is that we we are Presenting the whole stack as a complete product. We have a version of the telco cloud It's version to where we align the different versions Then we'll move to later on a version 2.1 with the configuration that we will push then from the staging environment The labs and then to a production of the different clusters Something we we also face and where the collaboration with we've had that and other vendor was really key is Initially open shift and Kubernetes are not really forcing for career or workload So there were a number of challenge and some of them are still present for us on Specific workload where we need to make sure we have a flow segregation for example something that you you don't really need in it Workload, but for network we need to to make sure that the management network management flow are well segregated with The application flow and that some of the floor are very well organized in terms of security Something else was that we need is very high throughput Typically, we had a use case where for example, we needed to be able to To to to bring a workload we've hundreds of thousands of connection for a few seconds. So it was for Targeted advertisement where we are able for a football match for example to send a specific Advertisement for each of our customer based on this profile And it means that we only have a few second for which we need to send on open shift Hundreds of thousands of connections and then drill it down when it's when it's done and this was very interesting use case for for head up and for a vendor to to tune the configuration to make some of some additional upgrade of some component to make sure that we could achieve this This is objective Internally also it was a challenge for some of the open shift adoption it was very new for many of our teams and It was surprising they came from time to time with some very exotic functional requirement But also some very strange performance requirements. So it's a lot of discussion over time We also like then to to a vendor on our bike to be able to help us with the discussion with our teams and With the whole story of open shift We face a number of early birds Where the collaboration with we've had that was very interesting and very important things like the integration for the multi interface like multis Some known limitations that we discover together about the tagging the quota for The registry of open shift. Well, I think we have plenty of time to do the question So there are two Mike I think If there is any question about the presentation Well, I want to ask a little bit about when you did this sort of integration with Open shift and open stack or when running open stack Can you tell us a little bit about when did the journey started with open stack at Proxima's and then how has it grown into? different, you know data centers or and how do you project your growth? The open stack story started really with with in fact the IT transformation where they needed a platform to to be able to To start using container Solution and so on so we started the open shift and open stack at that time later on we had NFV story which started as well in the telco industry and of course we already had the perfect solution for that We had open stack and the adoption for open stack went very fast with the different telco vendor We at that time had a lot of discussion with our peers in other countries in Netherlands in Germany to make sure that we We took the right decision and I must say we have been comforted with our decision everywhere We saw it. It's the same type of deployment with open stack That has to be reassuring. I mean we're in Berlin, but you're in Belgium and you know Just meeting with the next countries next to you trying to come up with similar strategies Sometimes trying to approach vendors Kind of together or with joint Requirements actually help drive those to the to the community. So that was really good to see indeed Yeah, any questions from the team or from anyone present? well, thank you very much and Thank you to Alan for joining


Hello, I am welcome to the session, I am Deepika here. Let's discuss a question which says 100 surnames were randomly picked up from local telephone directory and the frequency distribution of the number of letters in the English alphabets in the surnames was obtained as follows. Now if the number of letters is 1 to 4 then the number of surnames is 6. If number of letters is 4 to 7 then number of surnames is 30 and for 7 to 10 it is 40, for 10 to 13 it is 16 and for 13 to 16 it is 4 and for 16 to 19 it is also 4. If letters in the surnames find the mean number of letters in the surname also find the modal size of the surnames in median. Now we know that the class mark is equal to of the modal class and f0 in modal class is greater than number of observations. As we will apply the formula median is equal to the lower limit of median class observations and see accumulative frequency of class the idea to solve the above questions. So let's start the solution. Let us is 1 to 4 to 7 then the number of surnames is 30 the number of surnames 4 and again to 19 it is 4. Now to find column as 1 to 4 is 1 to 19 the class mark is 16 plus 19 upon 2 which is 17.5 with the corresponding frequency f100 and sigma f832 is equal to equal to 8.32. Now we will find the modal sign the modal class maximum frequency lower limit of the modal class 16 and h is equal to 3. So minus f is values 3 minus 30 upon 2 into 40 minus 30 minus 16 equal to 7 plus now 30 upon the modal size of the surnames 7.88 column for cumulative frequency as 1 to 4 the frequency of the class 4 to 7 is 6 plus 30 that is 36 as it is 36 plus 40 which is our cumulative frequency for the class 16 is 92 and see of the class 13 to 16 is 92 plus 4 which is 6 plus 4 that is 100 equal to 36 as 40 and h is equal to 3 is equal to 21 upon 20 is 1.0 so median is equal to 105. Now question is the limit is equal to


As Salaamu Alaikum, welcome to lecture number 12 of the course on statistics and probability. You will recall that in the last lecture, I was discussing with you the concept of dispersion. In particular, I discussed with you the mean deviation and the standard deviation also towards the end of the lecture, we discussed the relative measure called the coefficient of variation. Today, I will continue with the concept of the standard deviation and I will convey to you a very interesting and important inequality called the Chebyshev's inequality. Students, this inequality and the empirical rule, another important rule that I will discuss, this will help us understand the significance and the role of the standard deviation in interpreting properly the dispersion or the spread of our data set. You will recall that last time, we discussed this with a lot of detail about the standard deviation and the coefficient of variation, what is the role of the standard deviation is in this case, if we want to compare two or more data sets, but students, we have not focused as much on the question, how do we interpret the standard deviation in the case of one single data set? The Chebyshev's inequality and the empirical rule, these are two different ways of answering this particular question. To understand this point properly, students, aise ke ek particular data set ko apne zehen melaye and try to answer the following questions. Question one, how many data values fall within one standard deviation of the mean? Question two, how many data values fall within two standard deviations of the mean? And question three, how many data values fall within three standard deviations of the mean? Students yeh me ne aapse kya question puchehen, aapko yaad hai ke last time me ne badi tafseel ke saath aapko yeh convey kia tha, ke range, quartile deviation, mean deviation or standard deviation. Sab ke sab, they can be represented as a horizontal distance that we draw below the x-axis, a distance which enables us to understand the spread of our distribution. Agar aap iss point ko zehen me rakhein, toh in questions ka jawab koi asa muskil nahin. Pela question tha, how many data values fall within one standard deviation of the mean? Iska kya matlab hai? Very simply, I just want you to think that there would be a certain number and a certain proportion of the data values that will be lying between x bar minus s and x bar plus s. Ussi frequency distribution ko aur uski jo curve hai usko zehen me laaye. x bar is in the middle, x bar minus s is to the left. Kyuke jab aap s distance x bar me se minus karenge, toh obviously you will, as if you will travel backward and you will travel by a distance of one standard deviation. Toh x bar minus s aapki distribution ke hoga, not in the very beginning, but towards the left side or x bar plus s towards the right side and there is a certain amount of data that lies in this range. Similarly, a certain amount of data will lie between x bar minus 2 s and x bar plus 2 s and similarly, for x bar minus 3 s to x bar plus 3 s. Aap sabali beda hota hai, ke ham kistra ye determine karenge ke in ranges ke darmean kitna amount of data lie kartha hai? Well, it is obvious that if we have a particular data set, all we have to do is to first of all compute x bar and s and then of course, to find all these values x bar minus s, x bar plus s, x bar minus 2 s and so on. Aap uske baad ham count karenge, actually we will count the number of values that are lying in the inside these ranges, but students the theorem that I am wanting to convey to you, which is called the Shebyshev's theorem or the Shebyshev's inequality. This is a theorem that provides a general answer to this question and it is obvious that if we have a general answer, which is valid in every situation that is much better. So, as you now see on the screen, the Shebyshev's theorem states that for any number k greater than 1, at least 1 minus 1 over k square of the data values fall within k standard deviations of the mean, that is within the interval x bar minus ks to x bar plus ks. Ab iss theorem mein 2, 3 baathe bohot important hai. Peheli chee je note kee je that I said that the number k is a number, which is greater than 1 or dosri bohot important baat ye bhi note kee je that I said that for any number k greater than 1, at least 1 minus 1 over k square of the data values fall between x bar minus ks to x bar plus ks. Yani ye jo do alfaz hai at least that is very important. Aayi iss theorem ko zara detail mein samajnegi koshish karte hain. Jaisa mein hain kaha ks a number greater than 1. So, let me take a very very simple simplest case and let me take k equal to 2. Agar aap k equal to 2 apne us expression mein substituted kare 1 minus 1 over k square to zahire k 1 minus 1 over 2 square that is 1 minus 1 over 4 and that is equal to 3 over 4 iss ka matlab ye hoa k ham shebhi chef's theorem ko k equal to 2 ke case mein iss tara se pahenge that at least three fourth of the data values fall between x bar minus 2s and x bar plus 2s. Similarly, if I put k equal to 3, 1 minus 1 over 3 square is equal to 1 minus 1 over 9 and that is 8 over 9. And what I am saying is that for any data set at least 8 over 9 of the values 8 over 9 proportion of the values falls between x bar minus 3s and x bar plus 3s. Students ye jo shebhi chef's theorem hai this is valid for any data set may it be a sample drawn from a population or may it be an entire population iss ki jo limitation hai wo ye hai ke it does not provide any information for the case k equal to 1 iss liye ke agar aap us expression 1 minus 1 over k square mein k ko 1 ke baraabar put karein to saab zahere k 1 minus 1 over 1 square will be equal to 1 minus 1 and that is 0. And we are saying that at least 0 percent of the data lies between x bar minus s and x bar plus s and this obviously does not make much sense. Ye jo mein aap ko abhi values aap ke saath calculate ki 3 over 4, us case mein when k is equal to 2 and 8 over 9 in the case when k is equal to 3, zahere hai ke haam isko percentage form mein bhi apne zahen mein betha sakte hai and it is easy to remember that at least 75 percent of the data values will always lie between x bar minus 2 s and x bar plus 2 s and similarly at least 89 percent of the values will fall between x bar minus 3 s and x bar plus 3 s ye jo 89 percent mein kaha ye mein a round karke kaha, warna 8 over 9 is actually a little less or students issi tara aap ke ki koi bhi value put karenge greater than 1 and you will get the corresponding figure of the minimum amount of the data that lies in that range. Lekin ek point bada interesting or important iss marhalai par hai or wo ye ke in many situations the Shevychevs inequality provides weak information regarding the amount of data values that fall between these ranges. For many data sets the ones which would lead to mound shaped approximately symmetrical distributions students the actual proportion of data values that lies between x bar minus 2 s and x bar plus 2 s for example, is much greater than 75 percent and similarly the actual proportion of data values which would lie between x bar minus 3 s and x bar plus 3 s for a mound shaped symmetric distribution again that would be much greater than 89 percent. So, this means ke bas situations to definitely assi hain jab Shevychevs inequality or Shevychevs theorem comes to our rescue because un data sets ki jo distributions hain wo mound shaped symmetric distributions nahi hain or wo case me Shevychevs inequality ke zariye immediately we are able to ascertain that at least this much data lies in this particular range. Lekin bohat se ase data sets gin main hame approximately symmetric hum shaped distribution available hoti hai we need to do better than the Shevychevs inequality and in this regard I will now convey to you the other rule that I mentioned the empirical rule students the empirical rule is a kind of a rule of thumb which is valid in the case of symmetric or approximately symmetric hum shaped distributions as I just mentioned. According to this rule approximately 68 percent of the measurements will fall within one standard deviation of the mean that is within the interval x bar minus s to x bar plus s. Also approximately 95 percent of the measurements will fall within two standard deviations of the mean that is within the interval x bar minus 2 s to x bar plus 2 s. Similarly approximately 100 percent of the measurements that is practically all the measurements fall within three standard deviations of the mean that is within the interval x bar minus 3 s to x bar plus 3 s. Ye jo main haf se aakhir mein baat kahe that practically all the data lies between x bar minus 3 s and x bar plus 3 s. Iski bhaja se students ek bada interesting relation milta hain hame between the range and the standard deviation of a approximately symmetric hump shaped distribution the case that we are discussing at this time. Aapku yaad hai ke range ko hame define kiya tha as the distance between x naught the smallest value and x m the largest. Aap agar ham yeh kahe rahe hain ke x bar minus 3 s or x bar plus 3 s ke darmean takhrivan saara data lie krta hain. So, iska matlab to yahi nikalta hain hain ke x naught corresponds approximately with x bar minus 3 s and x m corresponds approximately with x bar plus 3 s. Iska matlab yeh hua ke x naught se le ke x m tak kitni standard deviations ham travel karein ke 3 s to the left of x bar and 3 s to the right of x bar in other words 6 standard deviations. And so the relationship that I am referring to is that for a symmetric or approximately symmetric mound shaped distribution the range is approximately 6 times the standard deviation. Let us apply this empirical rule to an example. As you now see on the screen suppose that we have data regarding the percentages of revenues spent on research and development that is R&D by 50 different companies. And suppose that the figures are 13.5 percent, 9.5 percent, 8.2, 6.5 and so on. Suppose that we wish to calculate the proportions of these measurements the proportions that lie within the intervals x bar plus minus s, x bar plus minus 2 s and x bar plus minus 3 s. In order to do this of course the first step will be to find the mean and the standard deviation of this data set. And if we apply the formulae that I have discussed with you in the previous lectures the mean of this data set comes out to be 8.49 and the standard deviation comes out to be 1.98. Accordingly x bar minus s comes out to be 6.51 and x bar plus s is 10.47. Now if we count the number of data values that lie inside this interval we find that 34 of the 50 measurements in other words 68 percent of the measurements fall between 6.51 and 10.47. Similarly the interval from x bar minus 2 s to x bar plus 2 s comes out to be 4.53 to 12.45 and when we count the number of data values that fall in this range we find that 47 of the 50 measurements that is 94 percent of the data values lie in this interval. Finally the three standard deviation interval around x bar comes out to be 2.55 to 14.43 and we find that 100 percent of the values lie in this interval. Students, agar aap in values say frequency distribution banai, histogram draw kare or frequency curve uske upar superimpose kare, to aap dekhenge ke this distribution is somewhat positively skewed, yani it is not totally symmetric. In spite of this asymmetry students you have noticed that the proportion of data that lies within one standard deviation of the mean is 68 percent. The proportion of data that lies within two standard deviations is 94 percent and the proportion of data that lies within three standard deviations is 100 percent. And isn't it interesting that these proportions are remarkably close to the proportions that I mentioned to you a short while ago as the empirical rule for the case of symmetric distributions. To kahine ka maksad ye hai ke slight departure from symmetry does not matter and this empirical rule gives us a very good way of judging the amounts of data that would lie within specified intervals of our data set. Aur aaye ab ek defa phir shebi-shebs inequality ki baat karthe hain aap ko yaad hain that according to this theorem at least 75 percent of the data values will fall between x bar minus 2 s and x bar plus 2 s for any data set. Aur iss data set me 94 percent of the values are falling in this interval. So, there is no contradiction obviously 94 percent is much greater than 75 percent. Isitara shebi-shebs inequality ki ru se at least 89 percent of the data values should have fallen between x bar minus 3 s and x bar plus 3 s. Aur iss data set kender 100 percent of the values are falling in this interval. So, there is no contradiction, but you will realize that the fact that this particular data set is approximately symmetric rather I should say slightly positively skewed, but not extremely skewed. The information that we are getting from the empirical rule in this situation is more than what we get from the shebi-shebs inequality. Lekin main ek defa phir repeat karungi ke un data sets me jaha pe approximate symmetry aap ko nahi mil rahi shebi-shebs inequality is a useful tool to establish the proportions of our data set that lie in specified intervals. Let us define this one more time. As you now see on the screen, the shebi-shebs theorem states that given a set of n observations x 1, x 2, so on up to x n on the variable x, the probability is 0. At least 1 minus 1 over k square that x will take on a value within k standard deviations of the mean of the set of observations where k is greater than 1. Ab yaha pe ek aur baat note karne ki hai. Aap ne dekhah ke iss mertwa maine iss theorem ko iss tarah se state kia that the probability is at least 1 minus 1 over k square that so and so will happen. Yani shebi-shebs theorem ko aap probabilistic terms me bhi define kar sakte hain aur state kar sakte hain. Since pandhar me lecture ke baad jab hum probability theory ka aagas karenge to uswakth hum iss theorem ko bhi probabilistic terms me define karenge. Phil haal aap isshi baat pe concentrate karen jis tarah se maine aapko aaj iss ki interpretation dehe. Let us consolidate this idea by considering one more example. Suppose that a set of data has a mean of 150 and standard deviation of 25. Now multiplying 25 by 2 we get 50 and hence we can say that we expect at least 75 percent of the data values to lie between 150 minus 50 that is 100 and 150 plus 50 that is 200. By similar calculations we find that we can expect at least 89 percent of the values to lie between 75 and 225 and at least 96 percent to lie between 25 and 275. Ye to hua hamara 8 data set. Now suppose we have another data set whose mean is exactly the same as before that is 150 but whose standard deviation is not 25 but 10. Applying Shebyshev's theorem for this particular set of data we can expect at least 75 percent of the values to lie between 130 and 170. At least 89 percent to lie between 100 and 20 and 180 and at least 96 percent to lie between 100 and 200. Ye jo 96 persent ka figure hai, this is obtained by substituting the value k equal to 5 in the expression 1 minus 1 over k square. Students agar ham in dono data sets ko compare kane to that will enable us to understand the difference in the two data sets with respect to dispersion. As you now see on the screen the comparison of the two data sets is that for the percentage of the data at least 75 percent, at least 75 percent of the data values of the data set number 1 lie between 100 and 200 whereas at least 75 percent of the data values of data set number 2 lie between 130 and 170. Ab in dono intervals ko visualize kane ki koshish kiji. Pehle data set ke liye 100 to 200, dusre data set ke liye 130 to 170. So, you find that the interval for the second data set is narrower than the interval for the first data set. Aur shebi-shev's theorem ki roo se ham ye karein hai, ke at least 75 percent of the data values lie in a narrower interval for that data set whose standard deviation was only 10 and compared with the interval that we have for that data set whose standard deviation was 25 which is much more than 10. I hope that you have understood the point. If your standard deviation is a smaller number, your interval is going to be narrower and if your standard deviation is bigger, your interval will naturally be wider. The graph that you now see on the screen illustrates this point for the case of the symmetric distribution. Agar aapka aapki mean value 150 hai for both the distributions, lekin standard deviation for one distribution is much more than the standard deviation for the other, then the interval for the first one that will contain a certain proportion of the values is much longer than the corresponding interval for the second one. Hence, we discussed the standard deviation with great detail and the discussion of all the two aspects is that we should talk according to the shebi-shev rule and we should talk according to the empirical rule which is valid only in that situation when our distribution hump-shaped approximately symmetric ho, dono hawalo se baat ka jo jist hai wo yehi hai that if the standard deviation is small, our interval containing a certain proportion of the data values will be a smaller interval compared with the situation when the standard deviation is large. I would like to encourage you to study this particular concept in further detail. Aap jitna jyada iska mutaleya karenge or jitne jyada questions karenge or practice karenge, students you will feel at home with this concept and the most important point that you will be able to understand much better the role and the significance of the standard deviation as a measure of dispersion. By the way yeh laabs dispersion, maine bhiis pachchis pachahas mirtabhaisthi maal kiya hoega, aapne gaur kiya ke in saare measures ko measure of dispersion kyun kite hain? The answer is very simple.  And after all what is a measure of dispersion? It is a measure of spread or the scatter of your distribution. Students dispersion ke baare me to hamne tabseel ke saath baat karli. The next concept that I am going to discuss with you is called the five number summary. Aap jab ke hamne kisi bhi distribution ke baare me, teen bohot ahem baat hain discuss karli hain aur samaj li hain. The central tendency of our dataset, the spread of our dataset and the shape of our dataset. Then we are in a position to summarize the important features of our dataset through what is called the five number summary. The concept of the five number summary of a dataset comes under the broad topic of exploratory data analysis. And as you now see on the screen, the five number summary of any dataset consists of x naught, q 1, median, n naught, n naught, q 3 and x m. Students aapne gaur kia ke iss five number summary me hamne dono extreme values yani x naught or x m aur teen ho quartiles ko involve kia hain, yani q 1, q 3 and the median. Of course, you will recall that the median and the second quartile are one and the same thing. Students ye jo teen ho quartiles hain, inki jo position hain relative to each other and relative to the end points. This enables us to determine the skewness of our distribution. Iss baat ko samajne ke liye aaye ham step by step do teen baat ko pe gaur karte. If our dataset is perfectly symmetrical, the following would be true. Number 1, the distance from q 1 to the median would be exactly equal to the distance from the median to the third quartile. As you now see on the screen, the distances on both sides of the median are exactly equal. Secondly, the distance from x naught to q 1 would be exactly equal to the distance from q 3 to x m. As you now see on the screen, the distances on the right side and the left side are exactly the same. And the third point to note is that in the case of an absolutely symmetric distribution, the median, the mid quartile range and the mid range, they are all equal to each other and also exactly equal to the arithmetic mean as you now see on the screen. On the other hand, for non-symmetric distributions the rules that I just mentioned are no longer valid. As you now see on the screen, in case of right skewed distributions, the distance from the third quartile to x m greatly exceeds the distance from x naught to q 1. Also, in case of a right skewed distribution, the median is less than the mid quartile range and the mid quartile range is less than the mid range. Or, if we talk about the left skewed distribution, meaning negatively skewed distribution, situation that will be just the opposite of the situation that I just mentioned for the right skewed distribution. So, students, yahi waja hai ke five number summary, which includes the minimum distribution minimum value x naught, the maximum value x m and the three quartiles q 1, q 2 and q 3. It enables us to determine the skewness of our distribution and also the spread of the distribution because after all you do remember that the distance from x naught to x m is the range and the range is the first and foremost measure of dispersion. Let me explain this concept to you with the help of an example. Suppose that a study is being conducted regarding the annual costs incurred by students attending public versus private colleges and universities in the United States of America. In particular, suppose that for exploratory purposes our sample consists of ten universities whose athletic programs are members of the big ten conference. The annual costs incurred for tuition fees, room and board at the ten schools belonging to big ten conference are for Indiana University 15.6 thousand dollars, for Michigan State 17.0, for Ohio State University 15.2 thousand dollars and so on. In order to state the five number summary of this particular data set, students the first step will be to arrange these values in ascending order. So, as you now see on the screen, when we arrange these values the smallest value comes out to be 13.0 and the largest 23.1. Also, when we do the relevant computations we find that the median for this data set is 15.3 thousand dollars, the first quartile is 14.9 thousand dollars and the third quartile comes out to be 16.4 thousand dollars. Therefore, the five number summary of this particular data set comes out to be x naught minus x naught equal to 13.0, q 1 equal to 14.9, x tilde 15.3, q 3 equal to 16.4 and x m equal to 23.1 thousand dollars. If I apply the rules that I mentioned a short while ago, students we find that the distribution of this particular data set is positively skewed. So you find that the five number summary is a simple and yet very effective way of determining the shape of your distribution without actually drawing the graph of your distribution. This brings us to the end of today's lecture. Next time I will continue with the concept of the five number summary and I will proceed to another very interesting concept and that is called the box and whisker plot. Until next time I wish you the best in your studies of the subject and I would like to encourage you to attempt as many exercise questions as you can easily do. Best of luck and Allah Hafiz.


In this lecture, I want to introduce you to the wonderful and powerful world of pandas. Pandas is a Python module that we import into our iPython notebook. With that, we can take our two-dimensional spreadsheet file and turn it into a massively powerful data analysis structure. Have a look.