EXPERIENCE IS THE MESSAGE. RELAYTO engages advanced algorithms to automatically revamp static content into interactive microsites that boost viewer engagement 24/7 - no coding required. https://relayto.com/showcase Our secret sauce: 1. Content Enrichment - Turn “digital paper” into digital experiences enriched with interactivity, non-linear navigation and media. 2. All-in-one Cloud Hubs - Convert files into super-intelligent URL optimized for omni-channel sharing, access & control. 3. Advanced Analytics - 360-degree analytics around engagement of your content for better optimization. Think of Optimizely for web content. In the background, RELAYTO is also creating a new digital medium for one-one interactive storytelling, focused on removing friction for both authors and readers. Check out http:/rla.to/pitch or book a meeting with us: https://rla.to/meet-with-relayto

RELAYTO

Kuma Meshes Head-On - Everything You Need to Know

কুমা মেশেস হেড-অন - আপনার যা জানা দরকার

Kuma Meshes Frontal – Alles, was Sie wissen müssen

Kuma se enfrenta de frente: todo lo que necesitas saber

Kuma Meshes de front – Tout ce que vous devez savoir

कुमा मेशेस हेड-ऑन - वह सब कुछ जो आपको जानना चाहिए

クマが正面からメッシュ化 - 知っておくべきことすべて

Kuma Meshes 정면 대결 - 알아야 할 모든 것

Kuma Meshes Head-On - Tudo o que você precisa saber

Kuma Meses в лоб – все, что вам нужно знать

Kuma Kafa Başına Meshes - Bilmeniz Gereken Her Şey

Kuma Meshes Head-On - Mọi thứ bạn cần biết

Kuma Meshes 迎面而来——您需要了解的一切

This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Akash Chikhalikar, Graduate School of Engineering, Department of Robotics, Tohoku University; (2) Ankit A. Ravankar, Graduate School of Engineering, Department of Robotics, Tohoku University; (3)  Jose Victorio Salazar Luces, Graduate School of Engineering, Department of Robotics, Tohoku University; (4) Yasuhisa Hirata, Graduate School of Engineering, Department of Robotics, Tohoku University. Table of Links Abstract & Introduction Related Work Semantic Mapping Framework Multi-Target Search Experimental Studies Conclusions and Discussions, Acknowledgment and References V. EXPERIMENTAL STUDIES The following section describes the experimental details, starting with hardware configuration, followed by quantitative results and analysis. A. Hardware Configuration We use a Turtlebot2 platform with Kobuki base for our experiments. The onboard sensors include a RGB-D camera (Azure Kinect), a laser range scanner (RPLIDAR S2). The encoder information from the robot base is used to compute the odometry. The data acquisition from sensors and command relay to the robot is performed on the NVIDIA Jetson AGX Xavier as the client. The backend computations as well as the frontend visualization were carried out on a server CPU with NVIDIA 3090RTX graphics unit with an i9-12900K processor. The ROS distributed computing network ensured time synchronized communication between the server and the client. B. Living Lab- Simulated indoor environment All tests were performed in a simulated indoor environment called the ‘Aobayama Living Lab’ [2] at Tohoku University. The goal is to create a concept for future welfare facilities, as shown in Fig. 5. The Living Lab included household objects such as tables, chairs, sofas, beds, TVs, lamps, and cabinets. The facility emulates various areas, including toilets, bathrooms, kitchens as well as an outdoor environment with stairs, slopes, and rough terrain. The dataset generated from the Living Lab will be used to facilitate long-term navigation for service robots. C. Experimental Setup We conducted numerous experiments with different initial positions to understand the influence of our heuristic and navigation strategies. Each data point shown in the next subsection is obtained after averaging the results of five tests conducted in every scenario. Averaging eliminates any bias due to the slight randomness of the path planners and the minor differences in the starting positions (< 5cm) in each run. The distance traveled and the time required for the robot to search each target is recorded. The positions of the targets, i.e., cup and remote, are kept unchanged. D. Results and Analysis The results are divided into two groups. In the first part, we compare the performance of our novel heuristic with a baseline probabilistic greedy search. Figure 6 shows the results of a comparative study. Compared to the baseline, the proposed heuristic led to an average decline of 31.67% in the time taken, and 40.5% decrease in distance travelled to find a cup. Similar reductions of 26.35% and 29.3% were found in time required and distance travelled for searching remote. Thus, our heuristic is significantly superior than probabilistic baselines for multitarget search. Next, we compare the differences in target search with respect to the priorities set by the user. We initialize the target search from ten random locations in the indoor environment and change the priority of the search for each scenario. The results are shown in Figures 7a and 7b below. Our studies show that on an average a time reduction of 12.05s (33.5%) is observed when the user prioritizes finding the cup. In case of prioritising remote, a time reduction of 10.5s (26.5%). observed when compared with an equal priority search. When the user prioritises cup, the first-hit (i.e finding the target at the first landmark visited) percentage was 60% as compared to 40% for a equal-priority search. The cumulative time spent increased by 8.94s when prioritising remote and by 4.13s when prioritising cup as compared to equal priority search. Additionally, if the robot were to prioritize finding the remote, it took 25.8s more than the equal priority search to find the cup. Thus, it can be inferred that if the user intends to save energy or cumulative time rather than find one target at the earliest, an equal priority directive should be given. We assess the distance efficiency of our search strategy by calculating the Success weighted by Path Length (SPL) metric as follows: = Length of path followed by Robot L Figure 8 shows the SPL for target search (for both targets) depending on the priority set by the user. It is observed that the SPL increases by 0.16 (24.84%) when the user tasks the robot to search for a cup with priority, as compared to an equal priority search. An increase of 0.14 (19.5%) in the SPL is observed when prioritsing remote in the target search. In a cross-analysis, it is seen that the SPL decreases by 0.18 (20.2%) while searching for remote and 0.42 (51.5%) while searching for cup if the user prioritizes searching for the other object. The sharper SPL decline for cup can be attributed to its real location being closer to multiple landmarks as opposed to the remote.

Preferential Multi-Target Search in Indoor Environments using Semantic SLAM: Experimental Studies

The wait is over! - it’s time to celebrate the champion startups of the world. Shout out to all of the participants in our ! You did a wonderful job showcasing your incredible startups and powering through another year. 2023 Startups of the Year is a community-driven voting platform brought to you by HackerNoon that recognizes and celebrates tech startups changing technology and the world for the better. The award started on May 8th, 2023, where the internet nominated and voted for 30k startups around the world. The voting period remained open until December 31, 2023, and now we are here with the winner announcement after a comprehensive evaluation by the HackerNoon team. Startups of the Year 2023 To see the top 3 startups in each respective city, visit and pick a city. hackernoon.com/startups You’ll get a little surprise 😉 Here are the Startups of the Year Regional Announcements: North America Europe Asia Africa South America Oceania Misc/Remote From all of us at HackerNoon, thank YOU for your excellent campaign perseverance 🥺 This year has been awesome! Startups of the Year 2023 is concluded with 623k+ total votes, up from 215k+ votes in the inaugural startup competition. We look forward to seeing you again in the next campaign (stay tuned 😉)! Without further ado, let us kick off the announcement by celebrating the cities with top votes per region for 2023 🎉 North America (11,697 votes): Winner: Bloomfilter Cleveland, Ohio (8,835 votes) - Winner: SerpApi Austin, Texas , California (5,564 votes) - Winner: Finch San Francisco (4,258 votes) - Winner: RELAYTO SoMa, California - (3339 votes) Winner: Windscribe Toronto, Canada, North America (3304 votes) - Winner: Vouched Seattle (2716 votes) - Winner: Seccuri Palo Alto, CA, North America (2671 votes) - Winner: Salsa Valley Miami, FL, North America (2,613 votes) - Winner: Majhi Group Manhattan, New York (2423 votes) - Winner: Flieber, Inc. New York City, NY, North America See the complete announcement for the . Startups of the Year, North America, here Europe (45,612 votes) - Winner: Algomo London, UK (2,344votes) - Winner: Data Lake Warsaw, Poland (1,955 votes) - Winner: Hoken Tech Bari, Italy (1716 votes) - Winner: Not8 Amsterdam, Netherlands (1657 votes) - Winner: KYVE Frankfurt Am Main, Germany (1566 votes) - Winner: BazaIT Kyiv, Ukraine (1496 votes) - Winner:  Unity Network Tallinn, Estonia (1,478 votes) - Winner: Volcaino Ghent, Belgium (1,288 votes) - Winner: Owl Me Dublin, Ireland (1198 votes) - Winner: Groover Paris, France See the complete announcement for the . Startups of the Year, Europe, here Oceania (3,350 votes) - Winner: Sharepass Melbourne (2,107 votes) - Winner: The Catfisher Project Perth, Australia (220 votes) - Winner: Gemini AI Solutions Auckland, New Zealand, Oceania (213 votes) - Winner: Nexustorage Wellington, New Zealand, Oceania (138 votes) - Winner: Coviu Sydney (124 votes) - Winner: Bopple Brisbane, Australia, Oceania (124 votes) - Winner: Regional CFO New South Wales, Australia, Oceania (106 votes) - Winner: Edit on the Spot Gold Coast, Australia, Oceania (93 votes) - Winner: Knowledge Satnav Canbera, Australia, Oceania , Australia, Oceania (48 votes) - Winner: Peptalk360 North Melbourne, Melbourne See the complete announcement for the . Startups of the Year, Oceania, here Asia (16,345 votes) - Winner: Serenity Shield Singapore (13,588 votes) - Winners: QUIXY Telangana, India (10,168 votes) - Winner: HealthySure Mumbai, India (3,865 votes) - Winner: InterviewBuddy Visakhapatnam, India (3,733 votes) - Winner: Omniflo Bengaluru, India (4589 votes) - Winner: MeNow Tel Aviv (3877 votes) - Winner: ForestVPN Dubai (2478 votes) - Winner: TechGraph Powai, Mumbai, India (1004 votes) - Winner: Reelo Ahmedabad, GJ, India (875 votes) - Winner: Debt Hunter Hong Kong, China See the complete announcement for the . Startups of the Year, Asia, here Africa (8,179 votes) - Winner: GO PLATFORM Algiers, Algeria (767 votes) - Winner: Tudu Accra, Ghana (415 votes) - Winner: Treford Lagos, Nigeria (265 votes) - Winner: Phalconwise Ogbomosho, Nigeria (157 votes) - Winner: AbuErdan Cairo (151 votes) - Winner: Eazipay Lekki (144 votes) - Winner: KaziConnect Dar es Salaam, Tanzania (101 votes) - Winner: faceATT Gauteng, South Africa (79 votes) - Winner: Dimagi Cape Town (71 votes) - Winner: Sabi Addis Ababa See the complete announcement for the . Startups of the Year, Africa, here South America (376 votes ) - Winner: UpGirl Santiago, Chile (217 votes) - Winner: Klever Sao Paulo, Brazil (191 votes) - Winner: Tributo Simple Buenos Aires, Argentina (127 votes) - Winner: Light-it Montevideo, Uruguay (87 votes) -Winner: Thousand Antioquia, Colombia (108 votes) - Winner: GetLavado Lima (101 votes) - Winner: Cogniflow Medellin (73 votes) - Winner: TPAGA Bogota (73 votes) - Winner: Reliv Quito (47 votes) - WInner: Quantex Cordoba See the complete announcement for the . Startups of the Year, South America, here Misc/Remote: Featured Startups (1500 votes) - Winner: CIC Chain Remote, Earth (1193 votes) - Winner: Reship Colony US Misc (146 Votes) - Winner: Partful UK, Misc (116 votes) - Winner: GoMining British Virgin Islands Misc (283 Votes) - Winner: tomorrowSpace Germany Misc (225 votes) - Winner: Dtravel Cayman Islands See the complete announcement for Misc/Remote startups . here Once again, HUGE CONGRATULATIONS and BIG PROPS to all of the top Startups of each region this year! The whole team at HackerNoon would like to thank you for your perseverance in the campaign, and we look forward to seeing you in the next campaign. About HackerNoon’s Startups Of The Year Startups of The Year is HackerNoon’s Flagship community-driven event celebrating startups that survived and thrived in 2023. 30,000 startups across 4200+ cities and six continents participated this year to be crowned the best startup in their city. Visit our page to learn more. FAQ Companies that blog more get 67% more leads - Jumpstart your company’s blogging journey by purchasing our . Business Blogging Package The 2023 Startups Of The Year is sponsored by: . . The winners get a free .Tech Domain, a HackerNoon NFT, and a Tech Company News Page. TECH Domains

Stand Up for the Champion Startups of the Year! 

বছরের চ্যাম্পিয়ন স্টার্টআপের জন্য দাঁড়ান!

Setzen Sie sich für die Champion-Startups des Jahres ein!

¡Defiende a las startups campeonas del año!

Défendez les startups championnes de l’année !

वर्ष के चैंपियन स्टार्टअप के लिए खड़े रहें!

今年のチャンピオンスタートアップのために立ち上がろう!

올해의 챔피언 스타트업을 위해 일어서세요!

Defenda as startups campeãs do ano!

Встаньте на защиту стартапов-чемпионов года!

Yılın Şampiyon Startup'ları için Ayağa Kalkın!

Hãy ủng hộ các công ty khởi nghiệp vô địch của năm!

为年度冠军初创企业挺身而出！

There is a recent paper, , discussing synaptic pruning, where the authors summarized that: Activity-dependent local protection and lateral inhibition control synaptic competition in developing mitral cells in mice "Synaptic competition is known to facilitate synapse elimination; however, it has remained unknown how different synapses compete with one another within a post-synaptic cell. Here, we investigate how a mitral cell in the mouse olfactory bulb prunes all but one primary dendrite during the developmental remodeling process. We find that spontaneous activity generated within the olfactory bulb is essential." There are a few types of neurons in the brain, numbering in the billions with trillions of synapses, but they cannot be said to be directly involved in functions. There are already neurons identified across brain circuits with higher functional responsibilities for varying necessities. However, these localization finds have not led to solving consciousness or mental health problems. Impulses Explained The direct factors for all the functions of the brain are impulses. The electrical and chemical impulses of nerve cells and their interactions, which is also what the mind is, conceptually. There is no function of the brain that does not involve impulses. There are sets of impulses for functions, exceeding the singular actions of one or just a neurotransmitter. There are functions, of say acetylcholine, but what makes determination in experiences are sets of impulses, with the involvement of acetylcholine, not its singular oversight, even though it makes contributions. Conceptually, wherever there are nerve cells, what is most important are the features of their impulses and their interactions. This is what makes a memory different from modulation, or an emotion from a feeling. In a set, the electrical impulses relay to 'acquire' chemical impulses, with specifications for intensity, shifts, sides, spots, and so on, giving rise to an emotion in one case, and a feeling in another. These specifications are also responsible for how memory is encoded or retrieved. There are features of sets of impulses, like splits, sequences, prioritization, and others, that determine how impulses give off experiences, including mental disorders. There is no difference between how impulses give rise to memory and how it The key difference is specificity for sets of impulses. This is also the reason some parts of the brain are more adapted to some functions than others. does for sentience. Synaptic connections are forms of sequential threads, where matches for impulses in a set may determine something cliché or novel. In general, the function of the mind is to know, applicable to thoughts, feelings, memory, emotions, and so forth. Consciousness Consciousness for being and experience are also knowing processes, possible by the interaction of impulses, with specifications for sets. Conceptually, interactions that determine consciousness may have incoming electrical impulses 'fill' certain bends, for some in a set, while for location in space, could be a rotation, for memory could be a sequence or path of travel for aligning synapses, and so forth. The interactions of impulses across brain centers are not different. This makes the mechanism of consciousness similar, only with a difference in what sets of impulses do when chemical impulses are acquired. Feature image source

LLMs, Sentience: How Do Impulses Give Rise to Consciousness?

There is a recent article on where the authors stated that, "One thing hasn’t changed: Machines are not conscious. The ability to generate human-like responses is a result of what computers do best: finding patterns in enormous data sets. It’s a very sophisticated version of Google auto-complete, able to guess the next series of words that best satisfies what the user wants." Bloomberg , AI Isn’t Sentient. Blame Its Creators for Making People Think It Is , "Pretending to be human does not make a thing conscious. The science of how the brain works is one route to understanding how and why we experience emotions like joy and suffering. It offers clues about what sparks creativity, imagination, and curiosity. But even neuroscience has its limits. Computers can’t think or feel the ways humans do." Though it would be more appropriate to say the mind drives experiences, as well as creativity, not the brain, the ultimate decision maker if AI is sentient is what consists of sentience and if AI has some of it. Consciousness is driven by the human mind. Divisions of conscious experiences include feelings, emotions, perceptions, sensations, memory, intelligence, creativity, and so forth. The divisions result in a total. Though some are subsumed within others—like intelligence and creativity within memory—each division has a rate, varying across states of consciousness. Consciousness is the measure of a system's ability to know, with a maximum value of 1. Sentience or consciousness is defined by the act of knowing. Even if something isn't fully within one's awareness or attention, it must still be known within the mind. When something like "joy or suffering" is known, prioritization may determine the extent to which it is experienced. Subjective experiences, such as the sense of self or the "I" in experiences, are provisioned by the mind and must be known. However, in some experiences, there is detachment and no sense of self, meaning the property was not acquired. Conceptually, the components of the human mind are quantities and properties. Quantities relay to acquiring properties to degrees to drive experiences. The labels of memory, emotion, feeling, reaction, and so forth are properties obtainable to degrees across mind locations. On the mind, properties are simply obtained—the labels are useful to delineate—but the components of the mind make determinations. Simply, consciousness can be expressed as: t + M + F + E = 1 where t is thought, but never a standalone parameter, because it is often a quantity-bearing property. M, F, and E are memory, feelings, and emotions respectively. The human mind components prepare t, M, F, and E. Animal and plant equivalents are prepared by components with similar functions. systems lack the quantities and properties of the human mind, but they possess M, which arrives through a different pathway. Their diverse forms of M manifest in their communication, task execution, and ability to relate and understand. LLM LLMs' outcomes may result from 'finding patterns in enormous data sets,' yet they exhibit aspects of human intelligence. In the human mind, experiences are not solely determined by external situations; they depend on the properties that a quantity acquires. Loneliness, for instance, may not be solely caused by external factors but by internal ones as well. Thus, an outcome can be experienced despite differing external circumstances or varying degrees of intensity. LLMs' high M is likely greater than the sentience of some animals and plants. In fact, their high M already mirrors aspects of human intelligence, surpassing the M of various plants and animals. Lead image source.

Sentience: Evaluating LLMs, AI

OK hear me out, I know vulnerability management is an old practice. Why are we even talking about it, it’s not broken, right? For most companies, it is very broken even if it appears to be working. These broken vulnerability management programs are so similar that I bet I can describe broken vulnerability management program, without ever talking to you about it.  I bet it contains some of the following elements: YOUR 11 GB of excel spreadsheets (x10 if you are a larger enterprise) Massive email footprint, eating up about 1/3 of your inbox storage 3 that you can’t get anyone to take seriously truly critical vulnerabilities Tenable/Rapid7/Qualys/Green Bone/et al producing weekly or monthly scan reports A feeling of total despair…. I have lived and breathed vulnerability management for most of my career. At times, it was the majority of my work. Other times, it’s just a small part. But the thread remains, it feels like I am always talking about CVSS scores and trying (usually failing) to relay to anyone who will listen how these are just starting points for assessing vulnerabilities.  In reality, CVSS scores can often be so blind to architectures, security controls, and business practices that they do more harm than good! Luckily for you, I am not the type of person to raise my hand and call out a broken process without also bringing a good solution to the table. I present to you, SSVC or Stakeholder-Specific Vulnerability Categorization. A primer on SSVC Carnegie Mellon University's (SEI) and the have collaborated to create the Stakeholder-Specific Vulnerability Categorization (SSVC) system. This system is built to provide the cyber community with a vulnerability analysis methodology that takes into account the exploitation status, safety impacts, and prevalence of the affected product for each vulnerability. Later on, in 2020, the CISA collaborated with SEl to develop its own distinct SSVC decision tree for analyzing vulnerabilities affecting the US government, state, local, tribal & territories (SLTT), and critical infrastructure organizations. Software Engineering Institute CISA That is the definition provided by SEI & CISA. What this means in practical terms is, we now have a way of adding valuable context to the vulnerability assessment process. This is so critical to the improvement of vulnerability management, it can not be overstated.  This isn’t an evolution of a broken system, this is a revolution! SSVC in a nutshell CISA uses stakeholder-specific vulnerability information to identify, assess, and organize the cybersecurity risks faced by the country's critical infrastructure.  To assist them in better understanding and managing the cybersecurity threats faced by the US government, CISA provides stakeholder-specific vulnerability information to other federal agencies, state and local governments, the corporate sector, and foreign partners. CISA uses a slightly different model than that developed originally in conjunction with SEI. This model sorts vulnerabilities into four potential “states”. You can use this same model in your organization, with no additional work needed. To get started, you must first spend a few minutes understanding that vulnerabilities are sorted into “states”, each state has a descriptive set of actions that must be taken on the vulnerabilities in this state. States The vulnerability states can be thought of as general descriptions of how to treat a vulnerability. It’s important to note that we don’t see any number systems like the CVSS 0-10. Numbers poorly describe the nuanced qualities of a vulnerability, these states however do a much better job. When a vulnerability lands in one of these states, you simply read the language of the state and then apply that to the identified vulnerability. No interpretation, no additional consideration, just take action! The following four states are sorted from what is essentially “Informational” to “Critical” (top to bottom). At this time, no action is necessary to respond to the vulnerability. The company would keep an eye on the vulnerability and reevaluate it if new information surfaces. CISA advises addressing “Track” vulnerabilities during routine meetings to verify the state is still applicable. Track: The vulnerability has unique properties that may call for closer observation of any changes. CISA suggests that security patches should be applied to “Track***”** vulnerabilities during the next patching or outage window. Track*: : The organization's internal supervisory level personnel must pay attention to the vulnerability. The activities that must be undertaken include asking for help or gathering additional details regarding the vulnerability, and they may include publishing a notification internally or internationally. The CISA advises addressing “Attend” vulnerabilities with some urgency, earlier than the normal patching window. Attend : Internal, supervisory, and leadership-level members of the organization must pay attention to the vulnerability. Requesting assistance or details about the vulnerability, as well as disseminating a notification internally and/or externally, are required. Internal groups would often gather to decide on the overall reaction before carrying out the decisions made. “Act” vulnerabilities should be fixed as soon as feasible. Act Applying SSVC in your organization? While CISA and CMU SEI have developed this framework, they are still working out exactly how it should be used. Currently, they suggest using a decision tree workflow, which they call the SSVC Calculator. The SSVC calculator is a simple, intuitive graphical way to answer yes-no questions using easily obtained data.  This is what enables a more thorough analysis of vulnerabilities, with less incumbent skill (i.e. you don’t need a ton of experience to correctly assess a vulnerabilities severity). To use the calculator, you hover over the blue dots (decision points) to get information that will help make a decision.  Once a decision has been made, clicking the appropriate blue dot enters an answer and a new series of decisions (dots) will show up. In this example, you can see that by answering just four questions: No exploitation exists yes it’s Automatable it has a partial technical impact the assets involved are a medium level of importance We are able to determine this (made-up) vulnerability arrives at a “Track” state. With the “Track” state vulnerability, we would keep an eye on it and update the calculation should new info come out otherwise no actions would be taken. Wrapping this up SSVC is a step forward, as noted it is not the evolution of the vulnerability management space but instead a revolution of vulnerability management.  CVSS scores were a good starting point, but as we have seen time and time again, they are a poor indicator of true criticality.  Using the SSVC decision tree model, consistent, accurate vulnerability assessment can be achieved with less expertise! Also published here.

How to Fix Your Broken Vulnerability Management

This article is the 3rd in a series related to building a wireless thermostat in Rust, running on a Raspberry Pi – although this one has very little to do with the Raspberry Pi and is more relevant to any multi-threaded application. When creating my application, I implemented a simple and effective design for controlling multi-threaded access to shared memory. You can find the previous articles here: , and first article - Raspberry Pi Wireless Thermostat in Rust . second article - Cross Compiling Made Easy I have a few code snippets below, but you can find the entire code repository . on GitHub First, the back story: When designing a multi-threaded application, one of the core considerations is how the different threads share data. There’s always something that the threads share – you’re spinning off threads to work on a shared problem, after all. If nothing else, configuration data or database connection pools have to be shared. There are two main ways of approaching this problem. – channels between threads allow data to be sent and received between them. Message passing is the mechanism that golang prefers, as the golang documentation states: “Do not communicate by sharing memory; instead, share memory by communicating.” Rust supports creating channels; you can find more information in the Rust Book’s chapter on . Message Passing message passing – a set of data identified as a shared state. Each thread access a shared data area through thread-safe protection mechanisms – typically a Mutex. Locks on the data allow you to access the data safely, reading or updating the data as needed, and then the lock is released. Only one thread can read or write the data at a time. The Rust Book’s section describes these mechanisms. Shared-State shared state Both approaches work, and Rust has good support for both mechanisms in the standard library. To choose between them, consider the following. Will threads mainly read data, mostly write data, or both? What are the access patterns? Avoiding deadlock is a primary concern for multi-threaded applications – nothing is worse than having a bunch of threads available to do work, and they are all stuck waiting for the other ones to get out of the way. How will deadlock be avoided? While over-engineering for performance is a common fault, having some idea of the performance requirements of your solution is essential. I’m a big fan of the rule: . Performance. keep the solution as simple as possible, but no simpler I decided on a shared state approach for the application I am creating. This decision also implied that my worker threads would work by polling – checking on things periodically instead of receiving an outside message. Here is what led me to that conclusion. I have three main threads. One is a web interface that allows for reading/writing of the shared state (get temperature, get thermostat setting, set thermostat setting). The web interface is, by definition, a creator of unscheduled activity – things come in based on an external client’s action and are not under the application’s control. Second, a pair of background worker threads react to the application’s environment. The first reads the temperature sensor, and the second calculates whether the thermostat should be set on or off and controls the physical relay to make that happen. The thermostat is in a separate thread, as it could turn on/off when the temperature crosses a threshold, or we receive a new thermostat setting from the web interface. I didn’t have to worry about contention with only three threads (assuming a single external client on the web interface). A simple shared state approach wouldn’t run into issues based on too many threads trying to access locks simultaneously. The logic for determining the thermostat’s state has a time component. We don’t want frequent, short bursts of on/off, which thrash the furnace. We enforce a minimum amount of time that the thermostat will be on or off before switching to another state. Accurately reacting to a message (the temperature reading or thermostat value changes) requires knowing how long it’s been since the thermostat changed. A shared state made sense based on these requirements. My design enforces a low thread count, so contention was not an issue (a common problem with shared state approaches). I need to keep track of time, so some state data was always required. Implementing two different state data mechanisms in the same application would be added complexity. With each thread doing its own thing and getting/setting shared state independently, we isolate each thread from the others. This choice led to a simpler overall application design. But, as I reviewed the Rust Book’s content on , the complexity of managing access from each thread seemed daunting. Plus, sprinkling thread-locking code in the application made it a mess – my nice single-purpose functions now had Mutex locking logic. Also, when accessing data through a Mutex lock dealing with Rust’s borrow checker across threads proved challenging. shared-state A simpler approach: To make this manageable, I used an approach I’ve used before on C++ projects – encapsulating the shared data into a separate class and pushing all Mutex logic into the class. Rust doesn’t have classes, but a couple of structs did the trick. To start, I created a struct to hold all the shared state data in a single place. Then I could deal with a single reference to this struct instead of managing each data element independently. pub struct SharedData {
    continue_background_tasks: bool,
    current_temp: f32,
    thermostat_value: usize,
    thermostat_on: bool,
    thermostat_change_datetime: OffsetDateTime,
} Then we define a struct that holds an Arc pointer – an Atomic Reference Count pointer to a Mutex that guards our shared data struct. We use this struct to control access to/from our shared data. pub struct AccessSharedData {
    pub sd: Arc<Mutex<SharedData>>,
} We will make many copies of this pointer – they all point to our Mutex, which is how we gain access to our shared memory space. We do this by customizing the Clone() method for AccessSharedData – it looks like the following. // Clone here makes a copy of the Arc pointer - not  the entire class of data
// All clones point to the same internal data
impl Clone for AccessSharedData {
    fn clone(&self) -> Self {
        AccessSharedData {
            sd: Arc::clone(&self.sd),
        }
    }
} To use this, we first create an instance of our SharedData struct (the simple .new() method isn’t shown above but is straightforward). let common_data = SharedData::new(
    true,
    configuration.initial_thermostat_value as f32 + 5.0,
    configuration.initial_thermostat_value,
    false,
    OffsetDateTime::UNIX_EPOCH,
); Then, we initialize an instance of AccessSharedData. // The wrapper around our shared data that gives it safe access across threads
let sd = AccessSharedData {
    sd: Arc::new(Mutex::new(common_data)),
}; We then give each thread we spawn() a cloned copy of the AccessSharedData struct. The clone call creates a copy of the Arc pointer, which we then move into the new thread. A similar method passes in a clone of the AccessSharedData struct to the actix_web HttpServer::new() method, so it is also available in HTTP client handlers. // Create another clone of our pointer to shared data, and send it into a new thread that continuously
// checks to see how the current temperature and current thermostat setting compare - and will
// trigger turning on the relay for the furnace as needed.
let sdc = sd.clone();
let control_handle = spawn( async move {
    tracing::debug ! ("kicking off control_thermostat");
    match run_control_thermostat( & sdc, configuration.poll_interval).await {
        Ok(_) => tracing::info ! ("control_thermostat ended"),
        Err(e) => tracing::error ! ("control_thermostat returned an error {:?}", e),
    }
}); Now that everyone has a copy of the Arc pointer, we need to create a means to use it to read/write our shared data struct. A simple set of getters/setters for each member of our struct handles the task of acquiring a lock, getting/setting the data, and automatically releasing the lock. By putting this logic surrounding the get/set and utilizing the end of the method as a scope boundary to force the lock to be released, we gain control over the access to our data. impl AccessSharedData {
    pub fn continue_background_tasks(&self) -> bool {
        let lock = self.sd.lock().unwrap();
        lock.continue_background_tasks
    }
    pub fn set_continue_background_tasks(&self, new_val: bool) {
        let mut lock = self.sd.lock().unwrap();
        lock.continue_background_tasks = new_val;
    }
    //repeated for remaining struct members
} When each get/set function returns, the lock is released. This approach also means it is impossible to deadlock around access to the structure – everything is locked and released immediately and prohibits anything else from getting in the way. With all of our locking mechanisms in place, using the shared data in the rest of our application is trivial. sd.set_current_temp(temp_f);
let temp_now = sd.current_temp();
let thermostat_now = sd.thermostat_value(); In Summary This strategy is encapsulation at its finest. Application code uses straightforward calls to methods to get/set the shared data elements whenever needed. Behind the scenes, we manage the Mutex’s locking for that access to be thread-safe and safe from deadlocks. And Rust’s borrow checker is extremely happy that we aren’t allowing direct shared mutable references to our shared data. If needed, you could easily extend this design pattern to implement a more robust access pattern. Putting locking logic inside getters/setters enables our shared data struct to hide the complexities of multi-threaded access – much like the standard library does for thread-safe collections. Using clones of an Arc makes it possible to acquire a handle to the shared memory struct in each thread. These two concepts are the core ideas that make our Easy Shared Data design pattern work. Also published here.

Implementing Multi-Threaded Shared Memory in Rust

The Radio Amateur's Hand Book, by A. Frederick Collins is part of . You can jump to any chapter in this book here: . Chapter XV: Operation  of Vacuum Tube Receptors HackerNoon’s Book Blog Post series [LINK TO TABLE OF LINK] XV. OPERATION OF VACUUM TUBE RECEPTORS From the foregoing chapters you have seen that the vacuum tube can be used either as a detector or an amplifier or as a generator of electric oscillations, as in the case of the heterodyne receiving set. To understand how a vacuum tube acts as a detector and as an amplifier you must first know what electrons are. The way in which the vacuum tube sets up sustained oscillations will be explained in in connection with the Operation of Vacuum Tube Transmitters. Chapter XVIII What Electrons Are.--Science teaches us that masses of matter are made up of molecules, that each of these is made up of atoms, and each of these, in turn, is made up of a central core of positive particles of electricity surrounded by negative particles of electricity as shown in the schematic diagram, Fig. 69. The little black circles inside the large circle represent positive particles of electricity and the little white circles outside of the large circle represent negative particles of electricity, or electrons as they are called. It is the number of positive particles of electricity an atom has that determines the kind of an element that is formed when enough atoms of the same kind are joined together to build it up. Thus hydrogen, which is the lightest known element, has one positive particle for its nucleus, while uranium, the heaviest element now known, has 92 positive particles. Now before leaving the atom please note that it is as much smaller than the diagram as the latter is smaller than our solar system. What Is Meant by Ionization.--A hydrogen atom is not only lighter but it is smaller than the atom of any other element while an electron is more than a thousand times smaller than the atom of which it is a part. Now as long as all of the electrons remain attached to the surface of an atom its positive and negative charges are equalized and it will, therefore, be neither positive nor negative, that is, it will be perfectly neutral. When, however, one or more of its electrons are separated from it, and there are several ways by which this can be done, the atom will show a positive charge and it is then called a positive ion. In other words a positive ion is an atom that has lost some of its negative electrons while a negative ion is one that has acquired some additional negative electrons. When a number of electrons are being constantly given by the atoms of an element, which let us suppose is a metal, and are being attracted to atoms of another element, which we will say is also a metal, a flow of electrons takes place between the two oppositely charged elements and form a current of negative electricity as represented by the arrows at A in Fig. 70. When a stream of electrons is flowing between two metal elements, as a filament and a plate in a vacuum tube detector, or an amplifier, they act as carriers for more negative electrons and these are supplied by a battery as we shall presently explain. It has always been customary for us to think of a current of electricity as flowing from the positive pole of a battery to the negative pole of it and hence we have called this the direction of the current. Since the electronic theory has been evolved it has been shown that the electrons, or negative charges of electricity, flow from the negative to the positive pole and that the ionized atoms, which are more positive than negative, flow in the opposite direction as shown at B. How Electrons are Separated from Atoms.--The next question that arises is how to make a metal throw off some of the electrons of the atoms of which it is formed. There are several ways that this can be done but in any event each atom must be given a good, hard blow. A simple way to do this is to heat a metal to incandescence when the atoms will bombard each other with terrific force and many of the electrons will be knocked off and thrown out into the surrounding space. But all, or nearly all, of them will return to the atoms from whence they came unless a means of some kind is employed to attract them to the atoms of some other element. This can be done by giving the latter piece of metal a positive charge. If now these two pieces of metal are placed in a bulb from which the air has been exhausted and the first piece of metal is heated to brilliancy while the second piece of metal is kept positively electrified then a stream of electrons will flow between them. Action of the Two Electrode Vacuum Tube.--Now in a vacuum tube detector a wire filament, like that of an incandescent lamp, is connected with a battery and this forms the hot element from which the electrons are thrown off, and a metal plate with a terminal wire secured to it is connected to the positive or carbon tap of a dry battery; now connect the negative or zinc tap of this with one end of a telephone receiver and the other end of this with the terminals of the filament as shown at A in Fig. 71. If now you heat the filament and hold the phone to your ear you can hear the current from the B battery flowing through the circuit. Since the electrons are negative charges of electricity they are not only thrown off by the hot wire but they are attracted by the positive charged metal plate and when enough electrons pass, or flow, from the hot wire to the plate they form a conducting path and so complete the circuit which includes the filament, the plate and the B or plate battery, when the current can then flow through it. As the number of electrons that are thrown off by the filament is not great and the voltage of the plate is not high the current that flows between the filament and the plate is always quite small. How the Two Electrode Tube Acts as a Detector.--As the action of a two electrode tube as a detector [Footnote: The three electrode vacuum tube has entirely taken the place of the two electrode type.] is simpler than that of the three electrode vacuum tube we shall describe it first. The two electrode vacuum tube was first made by Mr. Edison when he was working on the incandescent lamp but that it would serve as a detector of electric waves was discovered by Prof. Fleming, of Oxford University, London. As a matter of fact, it is not really a detector of electric waves, but it acts as: (1) a rectifier of the oscillations that are set up in the receiving circuits, that is, it changes them into pulsating direct currents so that they will flow through and affect a telephone receiver, and (2) it acts as a relay and the feeble received oscillating current controls the larger direct current from the B battery in very much the same way that a telegraph relay does. This latter relay action will be explained when we come to its operation as an amplifier. We have just learned that when the stream of electrons flow from the hot wire to the cold positive plate in the tube they form a conducting path through which the battery current can flow. Now when the electric oscillations surge through the closed oscillation circuit, which includes the secondary of the tuning coil, the variable condenser, the filament and the plate as shown at B in Fig. 71 the positive part of them passes through the tube easily while the negative part cannot get through, that is, the top, or positive, part of the wave-form remains intact while the lower, or negative, part is cut off as shown in the diagram at C. As the received oscillations are either broken up into wave trains of audio frequency by the telegraph transmitter or are modulated by a telephone transmitter they carry the larger impulses of the direct current from the B battery along with them and these flow through the headphones. This is the reason the vacuum tube amplifies as well as detects. How the Three Electrode Tube Acts as a Detector.--The vacuum tube as a detector has been made very much more sensitive by the use of a third electrode shown in Fig. 72. In this type of vacuum tube the third electrode, or grid, is placed between the filament and the plate and this controls the number of electrons flowing from the filament to the plate; in passing between these two electrodes they have to go through the holes formed by the grid wires. If now the grid is charged to a higher negative voltage than the filament the electrons will be stopped by the latter, see A, though some of them will go through to the plate because they travel at a high rate of speed. The higher the negative charge on the grid the smaller will be the number of electrons that will reach the plate and, of course, the smaller will be the amount of current that will flow through the tube and the headphones from the B battery. On the other hand if the grid is charged positively, see B, then more electrons will strike the plate than when the grid is not used or when it is negatively charged. But when the three electrode tube is used as a detector the oscillations set up in the circuits change the grid alternately from negative to positive as shown at C and hence the voltage of the B battery current that is allowed to flow through the detector from the plate to the filament rises and falls in unison with the voltage of the oscillating currents. The way the positive and negative voltages of the oscillations which are set up by the incoming waves, energize the grid; how the oscillator tube clips off the negative parts of them, and, finally, how these carry the battery current through the tube are shown graphically by the curves at D. How the Vacuum Tube Acts as an Amplifier.--If you connect up the filament and the plate of a three electrode tube with the batteries and do not connect in the grid, you will find that the electrons which are thrown off by the filament will not get farther than the grid regardless of how high the voltage is that you apply to the plate. This is due to the fact that a large number of electrons which are thrown off by the filament strike the grid and give it a negative charge, and consequently, they cannot get any farther. Since the electrons do not reach the plate the current from the B battery cannot flow between it and the filament. Now with a properly designed amplifier tube a very small negative voltage on the grid will keep a very large positive voltage on the plate from sending a current through the tube, and oppositely, a very small positive voltage on the grid will let a very large plate current flow through the tube; this being true it follows that any small variation of the voltage from positive to negative on the grid and the other way about will vary a large current flowing from the plate to the filament. In the Morse telegraph the relay permits the small current that is received from the distant sending station to energize a pair of magnets, and these draw an armature toward them and close a second circuit when a large current from a local battery is available for working the sounder. The amplifier tube is a variable relay in that the feeble currents set up by the incoming waves constantly and proportionately vary a large current that flows through the headphones. This then is the principle on which the amplifying tube works. The Operation of a Simple Vacuum Tube Receiving Set.--The way a simple vacuum tube detector receiving set works is like this: when the filament is heated to brilliancy it gives off electrons as previously described. Now when the electric waves impinge on the aerial wire they set up oscillations in it and these surge through the primary coil of the loose coupled tuning coil, a diagram of which is shown at B in Fig. 41. The energy of these oscillations sets up oscillations of the same frequency in the secondary coil and these high frequency currents whose voltage is first positive and then negative, surge in the closed circuit which includes the secondary coil and the variable condenser. At the same time the alternating positive and negative voltage of the oscillating currents is impressed on the grid; at each change from + to - and back again it allows the electrons to strike the plate and then shuts them off; as the electrons form the conducting path between the filament and the plate the larger direct current from the B battery is permitted to flow through the detector tube and the headphones. Operation of a Regenerative Vacuum Tube Receiving Set.--By feeding back the pulsating direct current from the B battery through the tickler coil it sets up other and stronger oscillations in the secondary of the tuning coil when these act on the detector tube and increase its sensitiveness to a remarkable extent. The regenerative, or feed back, action of the receiving circuits used will be easily understood by referring back to B in Fig. 47. When the waves set up oscillations in the primary of the tuning coil the energy of them produces like oscillations in the closed circuit which includes the secondary coil and the condenser; the alternating positive and negative voltages of these are impressed on the grid and these, as we have seen before, cause similar variations of the direct current from the B battery which acts on the plate and which flows between the latter and the filament. This varying direct current, however, is made to flow back through the third, or tickler coil of the tuning coil and sets up in the secondary coil and circuits other and larger oscillating currents and these augment the action of the oscillations produced by the incoming waves. These extra and larger currents which are the result of the feedback then act on the grid and cause still larger variations of the current in the plate voltage and hence of the current of the B battery that flows through the detector and the headphones. At the same time the tube keeps on responding to the feeble electric oscillations set up in the circuits by the incoming waves. This regenerative action of the battery current augments the original oscillations many times and hence produce sounds in the headphones that are many times greater than where the vacuum tube detector alone is used. Operation of Autodyne and Heterodyne Receiving Sets.--On page 109 [Chapter VII] we discussed and at A in Fig. 36 is shown a picture of two tuning forks mounted on sounding boxes to illustrate the principle of electrical tuning. When a pair of these forks are made to vibrate exactly the same number of times per second there will be a condensation of the air between them and the sound waves that are sent out will be augmented. But if you adjust one of the forks so that it will vibrate 256 times a second and the other fork so that it will vibrate 260 times a second then there will be a phase difference between the two sets of waves and the latter will augment each other 4 times every second and you will hear these rising and falling sounds as beats. Now electric oscillations set up in two circuits that are coupled together act in exactly the same way as sound waves produced by two tuning forks that are close to each other. Since this is true if you tune one of the closed circuits so that the oscillations in it will have a frequency of a 1,000,000 and tune the other circuit so that the oscillations in it have a frequency of 1,001,000 a second then the oscillations will augment each other 1,000 times every second. As these rising and falling currents act on the pulsating currents from the B battery which flow through the detector tube and the headphones you will hear them as beats. A graphic representation of the oscillating currents set up by the incoming waves, those produced by the heterodyne oscillator and the beats they form is shown in Fig. 73. To produce these beats a receptor can use: (1) a single vacuum tube for setting up oscillations of both frequencies when it is called an autodyne, or self-heterodyne receptor, or (2) a separate vacuum tube for setting up the oscillations for the second circuit when it is called a heterodyne receptor. The Autodyne, or Self-Heterodyne Receiving Set.--Where only one vacuum tube is used for producing both frequencies you need only a regenerative, or feed-back receptor; then you can tune the aerial wire system to the incoming waves and tune the closed circuit of the secondary coil so that it will be out of step with the former by 1,000 oscillations per second, more or less, the exact number does not matter in the least. From this you will see that any regenerative set can be used for autodyne, or self-heterodyne, reception. The Separate Heterodyne Receiving Set.--The better way, however, is to use a separate vacuum tube for setting up the heterodyne oscillations. The latter then act on the oscillations that are produced by the incoming waves and which energize the grid of the detector tube. Note that the vacuum tube used for producing the heterodyne oscillations is a generator of electric oscillations; the latter are impressed on the detector circuits through the variable coupling, the secondary of which is in series with the aerial wire as shown in Fig. 74. The way in which the tube acts as a generator of oscillations will be told in . Chapter XVIII About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Collins, A. Frederick. 2002. The Radio Amateur's Hand Book. Urbana, Illinois: Project Gutenberg. Retrieved April 2022, from https://www.gutenberg.org/files/6934/6934-h/6934-h.htm#chap15 This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever.  You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

The Operation  of Vacuum Tube Receptors

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