Project: 500-Word Summary Phase 2

Continuing from the assignment last week, we will begin narrowing down your list of potential scientific or technical journal articles for the 500-word summary project. In that assignment, I asked you to find 5 potential articles and write APA-formatted bibliographic citations for those. We’re going to use those with this assignment.

Of the 5 articles that you found, choose the one with an appropriate length and one that has the most relevant content that you would like to write about.

With this selection made, create a new Word or Google doc. Format it as a memo addressed to Professor Ellis. Write an introductory paragraph stating that this memo includes your selected article, a reverse outline of it, and a list of the four articles that you decided against choosing for this project.

 

17 thoughts on “Project: 500-Word Summary Phase 2”

  1. From: Karmoko Sillah

    To: Professor Ellis

    09/06/2019

    Subject:
    This memo is intended to summarize and analyze an article on the importance of cloud computing/ cloud storage to organizations and facilities around the world. Cloud storage is a much needed resource because it allows for data to be securely stored while at the same time maintaining the integrity of data. This article focuses on cloud computing in medical facilities, and how it has become an integral part of hospitals.

    Fang, L. (2019, August 9). A physiological and behavioral feature authentication scheme for medical cloud based on fuzzy-rough core vector machine. Retrieved from https://www.sciencedirect.com/science/article/pii/S0020025519307546?via=ihub

    Body #1: Cloud storage & security problems
    -This paragraph will focus on data storage, data collection, and data analysis in medical facilities. It will also focus on the importance of identity recognition, fingerprint recognition, etc. The improvements to these things will in turn strengthen security and ensure the security of client info.
    Body #2: Fuzzy rough approach
    -This paragraph will focus on how the fuzzy rough approach is used to ensure that data system storage only accepts the authorized doctor access data.
    Body #3: Security risks, proxy re encryption
    -This paragraph will focus on the security risks, and on the new implementation of proxy re encryption

    Articles not chosen
    1.Hu, L. (2019, July 27). SuperMC cloud for nuclear design and safety evaluation. Retrieved from https://www.sciencedirect.com/science/article/pii/S0306454919304049
    2.HU, X. (2019, February 5). Biomass pyrolysis: A review of the process development and challenges from initial researches up to the commercialisation stage. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S209549561830901X?via=ihub
    3.Rong, Y. (2019, July 22). A real-time data-driven collaborative mechanism in fixed-position assembly systems for smart manufacturing. Retrieved from https://www.sciencedirect.com/science/article/pii/S0736584519300213?via=ihub

  2. To: Prof. Ellis
    From: Jeremy Corona
    Date: 09/09/2019
    Subject: This memo includes my article for the 500 word summary. Also included in this memo is a reverse outline of the article that will aid me in doing the summary. Out of the five articles this one appealed to me the most. It about the new phenom on in tech called “DevOps”. The following four articles were filtered out and will not be used for the 500 word summary.
    Select article: Wiedemann A., Forsgren N., Wiesche M., Gewald H. & Krcmar H. (2019).Research for Practice: The DevOps Phenomenon. Communications Of The ACM, 62(8), 44-49.
    Articles not chosen:
    Wadhwa A. & Arora N. (2017). A Review on Cyber Crime: Major Threats and Solutions. International Journal Of Advances Research In Computer Science, 8(5), 2217 – 2221.
    Sanchez F. C., Lin W. & Korunka K. (2019). Apply Irregular Warfare Principles to Cyber Warfare. Joint Force Quartely, 92, 15-22.
    Padalidi N. & Christain Gerhmann. (2017). Bootstrapping Trust In Software Defined Networks. EAI Endorsed Transactions On Security And Safety, 4(1), 1-15.
    Cisar P. & Cisar M. S. (2018). Ethical Hacking Of Wireless Networks In Kali Linux Environment. International Journal of Engineering, 16(3), 181-186.

    Reverse Outline for “Research for Practice: The DevOps Phenomenon”
    Paragraph 1.
    Introduction begins with a story of the traditional way companies delivered software products. The frustrations and disadvantages it has.
    Paragraph 2.
    This paragraph introduces a solution to the issues in the traditional software development life cycle. Method called “DevOps”
    Paragraph 3.
    DevOps promise both speed and stability to software products throughout their life cycle. Defines DevOps as combining both operations and development to smoothen out delivery.
    Paragraph 4.
    Implementing a DevOps team isn’t without challenges. You cannot just install a piece of technology and expect it to work. There are success stories of DevOps being implemented.
    Paragraph 5.
    There are many moving parts to implementing DevOps such as new tools, and culture collaboration of teams. These challenges can make it difficult but good leadership is needed and will make the transition easier.
    Paragraph 6.
    The traditional way of delivering software offloads the product to operations after it has been released. This creates a gap between the software developers and the operations team.
    Paragraph 7.
    Developers aren’t responsible for running or maintaining the system they built.
    Paragraph 8.
    The operations team has to deal with the stability of the product and are hesitant to change because of possible instability issue with each new feature released.
    Paragraph 9.
    Developers aren’t able to receive feedback until after the release of the software, which causes a waste of time and features that do not bring value to the product.
    Paragraph 10.
    There is no formal definition of DevOps. This allows organizations to take the concept and make it their own and implement it in way that fits their goals. Sometimes the lack of definition can cause misunderstanding and confusion.
    Paragraph 11.
    There are different definitions but the main point of DevOps culture is to focus of outcome through speed and stability of the product.
    Paragraph 12.
    CALMS acronym Culture Automation Lean Measurement
    Paragraph 13.
    Callaboration between teams is very important in DevOps. They can include job swaps or shadowing of colleagues in different departments for a look into their perspective.
    Paragraph 14
    This leads into better outcomes of software/feed back in the software delivery lifecycle
    Paragaph 15.
    There are some companies that have implemented this way of delivery product but not until recently is it gaining a lot of traction in companies today.
    Paragraph 16.
    Research conducted on places who have implemented in DevOps and their outcomes have been overall positive.
    Paragraph 17.
    There are many challenges especially the cultural aspect. Implementing new technology to facilitate DevOps is easy. But changing the people and how they think is not. Good leadership is needed in order for a DevOps focused lifecycle to be successful.
    Paragraph 18.
    DevOps is not one size fits all for every organization. It is important that a organization take the principles of the concept and implement them in way that fits their organization. The goal is make delivering the product faster, efficient and stable.
    Paragraph 19.
    Teams can implement this concept and be able to find success in DevOps.

  3. To: Jason Ellis
    From: Daniel Lawrence
    Date 9/9/19
    Subject: 500 word Reverse outline

    Opening: Finding an article or news piece of what has been done already is one thing, but what’s more interesting is the news stories on what is to come. Members from Harvard University report on their status and hopes for creating a network hive of robotic bees.

    Wood.R , Nagpal.R , Wei.G. (Mar 2013). Flight of the RoboBees. Scientific American, Vol. 308 Issue 3, p60-65.

    P1: Purpose of robotic bees.(colony at work)

    P2: Complications on creating a larger scale of a hive network(colony and communication)

    P3: How it works(brain and navigation)

    These citations were not selected:
    Maxwell.I. (Aug2016) Drones,Droids and Robots. Chemistry in Australia. P32-33
    KODITSCHEK.D, KUMSUOGLU.H (2010) Studying Animals TO BUILD A BETTER ROBOT. Research at Penn. Vol. 8, p15-15

    Maharbiz.M, Sato.H (Dec2010) Cyborg Beetles. Scientific American. , Vol. 303 Issue 6, p94-99.

    JEREMY.S (May/Jun2016) Three Projects That Reinvent Breakfast. Popular Science. Vol. 288 p82-82

  4. TO: Professor Ellis
    FROM: Dominick Denis
    DATE: 9/8/19
    SUBJECT: Article on solar energy storage

    Reverse Outline:
    Gourdo, L., Fatnassi, H. (15 February 2019). Solar energy storing rock-bed to heat an agricultural greenhouse. Energy, Volume 169, Pages 206-212. Retrieved from ARTICLE1 solar energy store.pdf or https://pdf.sciencedirectassets.com/271090/1-s2.0-S0360544218X00267/1-s2.0-

    Opening:
    During the coldest periods of the year, maintaining agriculture is important in sustaining good land for a people. The Faculty of Science, in Morocco, research the effectiveness of a solar greenhouse heating system in order to make it suitable for agricultural purposes.

    Paragraph 1: In certain areas, there still seems to be major concerns of quality of production during the winter seasons, despite there being an increase in crop production over some decades.
    Paragraph 2: Farmers are forced with a solution.
    Paragraph 3: Alternative methods created to heating greenhouses led to a study of an underground rock-bed, etc.
    Paragraph 4: Experiments are being had between the experimental greenhouse and the conventional greenhouse.
    Paragraph 5: Rock-bed heating systems are being implemented into the greenhouses.
    Paragraph 6: The measurements of different climate parameters are taken.
    Paragraph 7: There is a detailed description of the process and tests within the greenhouses.
    Paragraph 8: Temperatures of the greenhouse affect the rock-bed accumulator providing benefits.
    Paragraph 9: Rocks are the most optimal as heat storage materials.
    Paragraph 10: The results of the system are compared.
    Paragraph 11: Greenhouse solar heating system is profitable and easy to install.

    These citations were not included:
    Sharma, H. (November 2019). Maximization of wireless sensor network lifetime using solar energy harvesting for smart agriculture monitoring. Ad Hoc Networks, Volume 94, Article 101966. Retrieved from https://pdf.sciencedirectassets.com/272922/1-s2.0-S1570870519X00098

    Kumar, L. Hasanuzzaman, M. (1 September 2019). Global advancement of solar thermal energy technologies for industrial process heat and its future prospects: A review. Energy Conversion and Management, Volume 195, Pages 885-908. Retrieved from https://pdf.sciencedirectassets.com/271098/1-s2.0-S0196890419

    Ayres, Robert. (1998) Toward a nonpolluting energy system. Environmental Science & Technology, 32 (17) pg:408A. Retrieved from https://pubs-acs-org.citytech.ezproxy.cuny.edu/doi/pdf/10.1021/es983675z?rand=o9mji491

    McCulloch, W. S. (June 1949). Brain as a computing machine. Electrical Engineering. Vol. 68, p492-497, 6p. Retrieved from https://ieeexplore-ieee-org.citytech.ezproxy.cuny.edu/stamp/stamp.jsp?tp=&arnumber=6444817

  5. TO: PROFESSOR ELLIS
    FROM: ALAIN PALMER
    DATE: 9/8/19
    SUBJECT: Design of Cloud Based Robots using Big data Analytics and Neuromorphic Computing.

    I. INTRODUCTION
    In this first paragraph, the focus is understanding the human brain so that we can develop robots that will be able to interact with its environment by combining gene expression. Three major factors in this are Neuromorphic Computing, Cloud Based Robotic, and Big Data Analytics.
    Second paragraph focusses on Neuromorphic Computing and its association with very-large-scale integration systems and its mission focuses on the imitation of the neuro-biological architecture in the nervous system.
    Third paragraph focuses on Cloud Robotics using cloud computing as the essential resource to bring forth success in better management and understanding especially when linked with service robots that serves as human assistants; capabilities of robots will improve when using the cloud.
    The fourth paragraph focuses on data management. Because of the amount of data that is now being generated is just too much now for traditional data processing. Big Data Analytic will operate with predictive tools, natural language processing, and machine learning to improve many pf the data processing challenges.

    II. NEUROMOPHIC COMPUTING
    In this introduction of Neuromorphic Computing, it talks about the neuromorphic engineering attempts to develop computing devices that are brain-like. This creation is to mimic biological nervous system so that computing methods and human abilities can be combined.

    A. Architectures using Neuromorphic Computing
    With the advantages of the neuromorphic chips, they are projected to push growth in the robotic industry with the help of cognitive computing, optimum memory usage, high-speed performance, and low power consumption. Introduced was Zeroth processor; which uses electrical impulses to mock the behavior of the brain and allows robots to learn with training and feedbacks instead of using hard-coded instructions.
    B. Neuromorphic based Robotics
    It is understood that neuromorphic Robots will have the power to simulate thousands od neurons in real-time with computing onboard sensory and motor system which will apply procedures for learning sensorimotor capabilities. This is followed by data mining task where clustering and classification plays a big role especially in the robot neuromorphic vision where the algorithms use clustering space-time events to help bring success.

    III. Cloud-Based Robotics
    This section talks about the brain centered cloud for robots. Which basically acts as a database for robot brains. For example; when a robot interpret data and successfully uploads it to the cloud, other robots will have access to that data. This shortens processing time.
    RoboBrain and RoboEarth develops an interconnected system of knowledge that acts as a shared robotic brain. Rapyuta is the online data base of RoboEarth.

    IV. Big Data in Robotics
    This section talks about the reason why Big Data (BD) was created and the usage of it. It will use BD to evolve the robot’s Sense, Plan, and Act (SPA) in an advance way by 3 steps. (i) Descriptive analytics to see why some things happen, (ii) Predictive analytics to predict what could happen, and (iii) prescriptive analytics to suggest what a robot should do in a complex situation.

    V. Challenges
    In this section, discussed the challenges in the interdisciplinary approach that bring together the methodologies of Neuromorphic Computing, Cloud Robot, and Big Data control to have flexibility, cost effective, and a responsive robot system.

    VI. Proposed Infrastructure
    This talks about the system that is proposed. The proposed system is a dual architecture and combining unique advantages of both neuromorphic and traditional chips for each robot. The cloud system and a command center are what the robots will be relying on.

    VII. Conclusion
    This summary is to highlight the attempt to cover cloud computing, big data analytics, and neuromorphic computing to enhance the control architecture of robotics. In short, to use a very advanced cloud systems to operate robots and decrease the use of the command center.

  6. TO: Professor Ellis

    FROM: Julia Shin

    DATE: 9/7/19

    SUBJECT: 500 Word Summary Outline

    This journal article describes the inner-workings to develop Smart Cities by implementing IoT systems and explains the benefits from doing so.

    Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of Things for
    Smart Cities. IEEE Internet of Things Journal, 1(1), 22–32.

    I Introduction

    Introduction of IoT and how it works as well as its role in today’s society in different applications.

    Some problems include the complexity of the IoT system because it can have several distinct applications and the lack of a clear business model discourage investments required.

    The idea of urban IoT is established to help realize the concept of a “Smart City” whose ultimate goal is to be more efficient with the current resources available and to provide better service to the citizens all while reducing costs.

    The objective of this paper is formed and the Padova Smart City project is introduced where reports from the project will be collected.

    A brief overview of the paper is presented.

    II Smart City Concept and Services

    The Smart City market is comprised of different industries such as Smart Governance, Smart Mobility, Smart Utility, Smart Buildings, and Smart Environment and is estimated to be hundreds of billions of dollars by the year 2020.

    One of the problems of the Smart City market is who will make the decisions and a proposed solution is to create a single department that will dictate the planning and management of the smart cities.

    Another problem is that various technologies/systems used in cities are unable to work with one another, but this is where IoT can come to play and help realize the potential of the Smart City.

    A final problem is the lack of business model, mentioned before, discouraging investments. A potential solution was to start with services like smart parking that has a clear return on investments.

    A table is shown that demonstrates different services specifications for the Padova Smart City project.

    In order to measure the structural health of buildings, sensors will be used like vibration and deformation sensors then collected by the urban IoT system which will reduce the need for pricey structural testing.

    In order to manage waste, smart waste containers will be utilized which the IoT will connect to a control center that will process the information and release an appropriate number of collector trucks.

    In order to improve air quality, the IoT will be used to aid the 20-20-20 Renewable Energy Directive by monitoring the air quality in densely populated areas.

    In order to monitor noise, the urban IoT will monitor noise levels which not only helps to reduce the amount of noise but can also help enforce public security. However there are privacy concerns that come with this implementation.

    IoT systems can also be used to report traffic congestions to citizens.

    Urban IoT can provide a service that monitors energy consumption which can help pinpoint what the source of the main power consumption is making it easier to tackle the problem.

    Smart parking caan have many benefits such as reducing traffic congestion and allowing citizens to quickly find a parking spot thus reducing the amount of CO emission from the vehicle.

    Smart lighting is important because a more efficient lighting system, one that is able to provide optimal lighting according to time of day, weather conditions, and amount of foot traffic, will support the 20-20-20 directive.

    Using IoT technologies to control different parameters of public buildings like temperature and humidity will help reduce the cost of heating/cooling and improve the comfort of the citizens.

    III Urban IoT Architecture
    Introduces a centralized architecture that is responsible for storing and processing data.

    Key characteristics of urban IoT infrastructure is easy accessibility for both citizens and authorities as well as its capability to integrate different technologies.

    Introduces an overview of what is to come in the section.

    The web service approach for the IoT service architecture is introduced.

    A table is shown to demonstrate a protocol architecture for the IoT system, showing both a constrained and unconstrained protocol stack.

    In terms of data format, the XML, though most common, has some downsides making the EXI format more ideal.

    Describes the two different types of encoding: schema-less and schema-informed.

    The process of integrating multiple XML/EXI data sources into the IoT system is explained.

    In terms of the application and transport layer, the application layer by HTTP is not suitable for constrained IoT devices and is very limiting.

    The CoAP protocol, on the other hand, is much more suitable by use of binary format transported over UDP.

    The HTTP-CoAP intermediary, aka cross proxy, is able to translate requests from either protocols making communication between HTTP devices transparent.

    In terms of the network layer, the IANA announced the exhaustion of the IPv4 address blocks and a solution can be found in the IPv6 standard.

    There are some problems with IPv6 regarding compatibility which can be solved by adopting 6LoWPAN.

    The problem with 6LoWPAN is that interaction between the IoT nodes and the IPv4 host is not transparent.

    One solution can be v4/v6 port address translation and its process is explained.

    Another solution is the v4/v6 domain name conversion and its process is explained.

    One final solution proposed is URI mapping and its process is explained.

    Introduces link layer technologies which are categorized into unconstrained and constrained technologies.

    Describes the difference between the two categories in terms of energy consumption, transfer rates, and other parameters.

    Introduces different devices that are fundamental to the IoT system.

    Backend servers will serve as the root of the system and will be located at the control center where the data is to be collected, stored, and processed.

    The database management system will be in charge of storing large quantities of information that come from IoT peripheral nodes.

    Websites will act as the primary communication option between the system and its consumers.

    The enterprise resource planning systems are a vital tool because they support different business functions.

    The role of the gateway devices is explained as an interconnection between the end device and the main communication infrastructure.

    The IoT nodes, such as sensors, are what is responsible for producing the data that will be collected to the control center.

    IV An Experimental Study: Padova Smart City

    The section will go into detail about the Padova Smart City Project.

    The goal of the project is introduced: promote the adoption of the ICT solutions in public administration.

    In the next several paragraphs a detailed explanation regarding how all the different components and parameters of the system were implemented in the project.

    The data collected from the project is introduced and explained specifically the temperature, humidity, light, and benzene.

    V Conclusion

    A brief recap is provided as a concluding paragraph.

    These citations were not selected:

    Ahmad, A. S. (2017). Brain inspired cognitive artificial intelligence for knowledge extraction
    and intelligent instrumentation system. 2017 International Symposium on Electronics and
    Smart Devices (ISESD).
    Howard, J. (2019). Artificial intelligence: Implications for the future of work. American Journal
    of Industrial Medicine.
    Jeong, J. H., Byun, G. S., & Park, K. (2019). Tunnel lane‐positioning system for autonomous
    driving cars using LED chromaticity and fuzzy logic system. ETRI Journal, 41(4),
    506–514.
    Rao, S. K., & Prasad, R. (2018). Impact of 5G Technologies on Smart City Implementation.
    Wireless Personal Communications, 100(1), 161–176.

  7. TO: PROFESSOR ELLIS
    FROM: ALAIN PALMER
    DATE: 9/8/19
    SUBJECT: Design of Cloud Based Robots using Big data Analytics and Neuromorphic Computing.

    Satyanarayana A., Kusyk, J., Chen, Y. (2018) CUNY New York City College of Technology

    I. INTRODUCTION
    In this first paragraph, the focus is understanding the human brain so that we can develop robots that will be able to interact with its environment by combining gene expression. Three major factors in this are Neuromorphic Computing, Cloud Based Robotic, and Big Data Analytics.
    Second paragraph focusses on Neuromorphic Computing and its association with very-large-scale integration systems and its mission focuses on the imitation of the neuro-biological architecture in the nervous system.
    Third paragraph focuses on Cloud Robotics using cloud computing as the essential resource to bring forth success in better management and understanding especially when linked with service robots that serves as human assistants; capabilities of robots will improve when using the cloud.
    The fourth paragraph focuses on data management. Because of the amount of data that is now being generated is just too much now for traditional data processing. Big Data Analytic will operate with predictive tools, natural language processing, and machine learning to improve many pf the data processing challenges.

    II. NEUROMOPHIC COMPUTING
    In this introduction of Neuromorphic Computing, it talks about the neuromorphic engineering attempts to develop computing devices that are brain-like. This creation is to mimic biological nervous system so that computing methods and human abilities can be combined.

    A. Architectures using Neuromorphic Computing
    With the advantages of the neuromorphic chips, they are projected to push growth in the robotic industry with the help of cognitive computing, optimum memory usage, high-speed performance, and low power consumption. Introduced was Zeroth processor; which uses electrical impulses to mock the behavior of the brain and allows robots to learn with training and feedbacks instead of using hard-coded instructions.
    B. Neuromorphic based Robotics
    It is understood that neuromorphic Robots will have the power to simulate thousands od neurons in real-time with computing onboard sensory and motor system which will apply procedures for learning sensorimotor capabilities. This is followed by data mining task where clustering and classification plays a big role especially in the robot neuromorphic vision where the algorithms use clustering space-time events to help bring success.

    III. Cloud-Based Robotics
    This section talks about the brain centered cloud for robots. Which basically acts as a database for robot brains. For example; when a robot interpret data and successfully uploads it to the cloud, other robots will have access to that data. This shortens processing time.
    RoboBrain and RoboEarth develops an interconnected system of knowledge that acts as a shared robotic brain. Rapyuta is the online data base of RoboEarth.

    IV. Big Data in Robotics
    This section talks about the reason why Big Data (BD) was created and the usage of it. It will use BD to evolve the robot’s Sense, Plan, and Act (SPA) in an advance way by 3 steps. (i) Descriptive analytics to see why some things happen, (ii) Predictive analytics to predict what could happen, and (iii) prescriptive analytics to suggest what a robot should do in a complex situation.

    V. Challenges
    In this section, discussed the challenges in the interdisciplinary approach that bring together the methodologies of Neuromorphic Computing, Cloud Robot, and Big Data control to have flexibility, cost effective, and a responsive robot system.

    VI. Proposed Infrastructure
    This talks about the system that is proposed. The proposed system is a dual architecture and combining unique advantages of both neuromorphic and traditional chips for each robot. The cloud system and a command center are what the robots will be relying on.

    VII. Conclusion
    This summary is to highlight the attempt to cover cloud computing, big data analytics, and neuromorphic computing to enhance the control architecture of robotics. In short, to use a very advanced cloud systems to operate robots and decrease the use of the command center.

    H. Markram, “Understanding the brain: Organizational and scientific
    challenges,” From Physics to Daily Life, pp. 179–190, 2014.
    S. Furber, “Large-scale neuromorphic computing systems,” Journal of
    Neural Engineering, vol. 13, no. 5, pp. 1–14, 2016.
    D. Monroe, “Neuromorphic computing gets ready for the (really) big
    time,” Comm. of the ACM Mag., vol. 57, no. 6, pp. 13–15, 2014.
    W. Zhao and et al., “Nanotube devices-based crossbar architecture:
    toward neuromorphic computing,” Nanotechnology, vol. 21, no. 17, pp.
    175–202, 2010.

  8. TO: Professor Ellis
    FROM: Fernando
    DATE: 9/8/19
    SUBJECT: Biometrics

    [This memo is a reverse outline for the article I have selected on biometrics below are the APA citations of the rest of the articles.]

    People being citizen or noncitizen should be able to carry around IDs with biometric info. to check if they match & be easier to apply for jobs. (P1)

    India plans to use unique ID numbers that contain an individual’s biometric data to push this idea for banking purposes, voting, making it mandatory under government policies. (P2)

    The idea would have a database with features to automatically identify the physical person be able to checks things from work, ATM, and clinic information which India have spent about 50 billion rupees to complete the project. (P3)

    In the U.S noncitizen or people that are in the country illegally have been granted to work but, to find out for sure Biometric would be useful to prevent any fraud. (P4)

    Pakistan was able to use biometrics for donating, voting, and payments to uncover what things were being done secretly. (P5)

    Biometric would allow government to know who they are dealing with have satisfactory proof of identity or residency to allow them to provide accurate transactions. (P6)

    There are many places that have birth registration but, other places unfortunately do not have same luck that’s why introducing biometric would solve that problem. (P7)

    If the U.S would to imply the biometrics then it would create an issue just like the Civil War & 1892 events. (P8)

    In 1952, U.S. implemented “Green cards” for those who were not citizens and would worry those outsiders, very much like how biometrics would be like. (P9)

    As mention with these events, biometric would create a problem opposing fear for those who can get detained or deported since biometric would have all the info. on one individual. (P10)

    Social security is the only card that can uniquely identify you but, doesn’t have enough to show though driver’s license would be illegal if had ssn so there are issue there. (P11)

    Biometric seems to be a good way to go but, would the government be able to have that information very secured since security is an issue. (P12)

    Another issue that can possible happen is the government limiting us to things even with biometric cards that they would have for us. (P13)

    It explains that a good idea for biometric card is to have all information to be inside the card instead of the government having that valuable information. (P14)

    Another solution would be to have biometric information not all for government and limit the possession they have on us. (P15)

    Biometric is not a bad thing it may be create some issues but, at the same time it benefits us the people since things will be much easier. (P16)

    Hopkins, R. (1999). An Introduction to Biometrics and Large Scale Civilian Identification. International Review of Law, Computers & Technology, 13(3), 337–363. https://doi-org.citytech.ezproxy.cuny.edu/10.1080/13600869955017

    Smilansky, O. (2017). There’s Untapped Value in Voice Biometrics: Identification and verification technologies can help companies improve customer experience and mitigate security threats. CRM Magazine, 21(12), 14. Retrieved from http://search.ebscohost.com.citytech.ezproxy.cuny.edu/login.aspx?direct=true&db=a9h&AN=126503524&site=ehost-live&scope=site

    Walter, C. M. (2005). How biometrics keep sensitive information secure. Nursing, 35(5), 76. https://doi-org.citytech.ezproxy.cuny.edu/10.1097/00152193-200505000-00058

    Zhang, L., Tang, S., & Zhu, S. (2017). Privacy-preserving authenticated key agreement scheme based on biometrics for session initiation protocol. Wireless Networks (10220038), 23(6), 1901–1916. https://doi-org.citytech.ezproxy.cuny.edu/10.1007/s11276-016-1267-2

  9. To: Professor Ellis
    From: Huzaifa Anas
    Date: September 10, 2019
    Subject: Neuroscience-Inspired Artificial Intelligence
    In this journal article, the fracture of the interdisciplinary study of intelligence is being studied. Initially, artificial intelligence and neuroscience had close intertwined relationship with lots of communication and collaboration, but nowadays this is being seen less and less. The article argues to understand neuroscience and artificial intelligence understanding the other help, because the former provides some feasible models for the latter, while the latter can provide results of the theories and models in neuroscience. Overall these two fields are closely related and the gains that have been made to this day have been in a large part due to the collaborations of these two disciplines, so this fracturing relationship doesn’t bode well for development and needs to be countered.

    Rough Outline

    1. The fields of neuroscience and artificial intelligence have a long-intertwined history, but collaborations are getting rarer over time.
    2. Recently these fields have made rapid progress, and both have grown enormously complex and mature, but at the beginning, these two fields were intrinsically linked.
    3. The premise of building turning powerful intelligent system has a vast number of possibilities, but probably only a few will work, so studying the human brain will make us have an easier time finding the accurate solution.
    4. There are two main benefits of developing these two fields together: neuroscience provides inspiration and validation, which is independent of the mathematically dominant ai field.
    5. From a practical perspective though building based on biological models isn’t a requirement, just a helpful tool which can provide models which can be reversed engineering to find principles or ideas to make better artificial intelligence.
    6. The following parts of the article will unpack these claims made before in the article about ai-neuroscience past, present, and future.
    7. We begin by considering the origin of these two fields, that’s pivotal for ai research which is deep learning and reinforcement learning, both coming from neuroscience,
    8. AI has been revolutionized by dramatic advances in neural networks or “deep learning” methods, which originate from neuroscience works starting in the 1940s.
    9. The research from these times laid the groundwork for the backpropagation algorithms, which allowed learning to occur in networks composed of multiple layers.
    10. Though the PDP approach originally was applied to relatively small-scale problems it eventually has been used more problems like machine translation.
    11. The field of deep learning became a core area of ai through the PDP approach it added new ideas like deep belief networks and continued to draw key ideas from neuroscience.
    12. Reinforcement learning is the second pillar of ai and was inspired through animal training.
    13. Reinforcement learning has provided the core technology to robotic control to expert play in backgammon.
    14. Even right now we see many advances in ai driven by neuroscience.
    15. The brain doesn’t learn through one single way, but multiple different ways and different functions favor different ways, which has been implemented into ai.
    16. One of the recent developments is the focus on attention, where no longer everything is given equal value, but now different parts of a video or picture are given different amount of resources.
    17. This technique has also been used for machine translation and led to many advances in memory and reasoning tasks.
    18. Another interesting development is allowing ai to produce images incrementally based on deep generative models.
    19. A core idea in neuroscience is that intelligent behavior relies on different memory systems.
    20. A recent breakthrough has lead successful integration of RL with deep learning, which allows the network to learn a viable value function even in complex, highly structured sequential environments such as video games.
    21. “Critically, experience replay was directly inspired by theories that seek to understand how the multiple memory systems in the mammalian brain might interact.” Direct quote
    22. Experience can also be used to rapidly change ai behavior to adapt to situations while simultaneously keeping the general behavior intact.
    23. AI research through multi-memory systems has been able to overcome the slow learning process of some ai systems, which allows the rapid implementation of ai systems.
    24. Human intelligence is characterized by a remarkable ability to maintain and manipulate information within an active store, known as working memory and classic cognitive theories suggest that this functionality depends on interactions between a central controller (‘‘executive’’) and separate, domain-specific memory buffers (e.g., visuospatial sketchpad), which AI research has drawn inspiration from these models, by building architectures that explicitly maintain information over time. I edited parts of the paragraph into one sentence because I don’t know how to make this sentence better on my own.
    25. In ordinary LSTM networks, the functions of sequence control and memory are closely linked, but in human memory, they’re separate, and this being implemented into ai has led to more complex ai architecture.
    26. AI suffers from the problem of learning and remembering many different tasks over different time scales, which isn’t an issue for mammals, but for ai it is, which can be solved through inspiration from nature possibly.
    27. Though advanced imaging techniques we can see accurate images of brains and derive more accurate models, which might eventually be implemented into ai.
    28. Through the advances in neuroscience, the development of continuous learning has made progress.
    29. The progress of AI is increasing over time and we are seeing AI now outperform humans in certain environments like GO.
    30. Though there has been a lot of historical interaction between AI and neuroscience, there is still work needed to create effective collaboration.
    31. Recent research shows that AI lacks a lot of the learning systems human infants has, which can be the next development battlefield for AI.
    32. A lot of research currently address this issue like novel neural network architecture, which interpret information in a human-like way.
    33. Human learning stands out because it can rapidly learn from a few examples, unlike ai which relies typically on a massive amount of data.
    34. Recently AI algorithms have begun to make progress on tasks like character challenge through the DRAW model.
    35. Humans also excel at transfer learning, which is transferring generalized knowledge from one context to novel, previously unseen domains.
    36. At the level of neural coding, this kind of transfer of abstract structured knowledge may rely on the formation of conceptual representations that are invariant to the objects, individuals, or scene elements that populate a sensory domain but code instead for abstract, relational information among patterns of inputs. (I don’t think I can summarize this better)
    37. Despite the good performance of AI they lack imagination, which humans present, and are only stuck in reactively learning.
    38. AI research is now focusing on planning for the future like humans or more independent actions.
    39. Some initially good results are being seen from the deep generative model.
    40. Insights from neuroscience may provide guidance that facilitates the integration of simulation with control for AI, which is another challenge for AI currently.
    41. Research into human imagination can show how to make ai creative instead of starting from scratch, which is one of the goals of creating artificial intelligence.
    42. Another idea is to create virtual brains, which will not only help AI research but also neuroscience.
    43. It has shown some good results recently, and neural networks have become better and better over time.
    44. While the initial research shows promising results, a lot more work is needed, because creating these virtual brains requires a huge amount of resources like computing power, so things like more accurate models are needed.
    45. Most of the article has focused on Neuroscience donating to AI, but the works are a two-way street and AI has also contributed to neuroscience.
    46. A key example is RL learning which initially donated to Ai but eventually provided many gains to neuroscience.
    47. Another example is work focused on enhancing the performance of CNNs which also yielded new insights to neuroscience in high visual areas.
    48. Neural networks with external memory and meta-reinforcement learning might also give back to the neuroscience community, which originated from AI.
    49. Insights from AI also give a novel perspective to neuroscience, because it focuses more on mathematical models, while the other observes biological models usually to create results.
    50. AI might provide insights about the brain through backpropagation algorithms.
    51. AI research and neuroscience have both developed the other and there is a need for there to be more collaboration instead of the ever-increasing distance the two fields have currently.
    52. One of the ways to increase collaboration is by making a better common language between and hopefully in the future we see more work done together.
    Article Cited APA format
    Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95(2), 245-258.

    Other four articles APA Citation
    1. Li, D., & Du, Y. (2017). Artificial intelligence with uncertainty. CRC press.
    2. Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452.
    3. Lu, H., Li, Y., Chen, M., Kim, H., & Serikawa, S. (2018). Brain intelligence: go beyond artificial intelligence. Mobile Networks and Applications, 23(2), 368-375.
    4. Gunning, D. (2017). Explainable artificial intelligence (xai). Defense Advanced Research Projects Agency (DARPA), nd Web, 2.

  10. TO: Prof. Ellis

    FROM: Liuming Chen

    DATE: 09/10/2019

    SUBJECT: 500 words summary reverse outline

    This memo is the reverse outline for the 500 words summary project. “Cellular architecture and key technologies for 5G wireless communication networks” is selected article for this project.

    Reverse outline:

    ¶1: There are challenges that 4G cannot accommodated and 5G will be the next generation wireless communication system that solve the challenges.

    ¶2: Wireless communication technology is a significant element to global economy.

    ¶3: The phenomenal success of wireless mobile communications is mirrored by a rapid pace of technology innovation.

    ¶4: Innovation of wireless communication technology is causing dramatic increase in number of users of mobile network and increase of wireless mobile devices.

    ¶5: Two key challenges of advanced wireless technology are the physical scarcity of radio frequency (RF) spectra and energy efficiency.

    ¶6: Facing continuously increasing demand for better wireless communication technology by new wireless applications, countries are starting to invest and research on the next generation wireless communication technology.

    ¶7: People expect on 2020, 5G will build a far better wireless mobile network than 4G.

    ¶8: The remainder of this article will propose a potential 5G cellular architecture.

    ¶9: Outdoor base stations have high penetration loss when go through building walls.

    ¶10: To avoid penetration loss though building walls, the one key idea of designing the 5G cellular architecture is to separate outdoor and indoor wireless access points.

    ¶11: This type of cellular architecture, many short-range communications with high data rates technologies can be use because indoor users need to connect to access points inside the building.

    ¶12: The MFemtocell concept, which combines the concepts of mobile relay and femtocell, is proposed to accommodate high-mobility uses such as users in vehicles and highspeed trains.

    ¶13: Base on the Shannon theory, increase of network coverage, number of subchannels, bandwidth and power can increase total system capacity in the 5G network.

    ¶14: By adding more antennas to Multiple Input Multiple Output (MIMO) systems can be accommodate more information data in wireless channels and performance improvement in terms of reliability, spectral efficiency, and energy efficiency.

    ¶15: A novel MIMO technique, Spatial modulation (SM) has been proposed by Hass et al., for low-complexity implementation of MIMO systems without degrading system performance.

    ¶16: Spatial modulation can mitigate interchannel interference, interantenna synchronization, and multiple RF chains in conventional MIMO systems and allow to be used in MIMO system with any number of transmit and receive antennas, even unbalanced MIMO systems.

    ¶17: Cognitive Radio (CR) network is an innovative software technology to improve the utilization of the congested RF spectrum because a large portion of the radio spectrum is underutilized most of the time.

    ¶18: MFemtocell is proposed to be a potential candidate technology in next generation intelligent transportation systems that can increase the spectral efficiency and power efficiency.

    ¶19: Visible Light Communication (VLC) can uses LED light as signal transmitter is a viable technique to help mitigate spectrum bottlenecks in RF communication and can be developed by using existing lighting infrastructures.

    ¶20: Technologies that have mentioned in this article can be utilized to build a more power efficient and greener 5G wireless system.

    ¶21: There are still challenges in 5G wireless technology development that need to be discussed.

    ¶22: For a complete and fair assessment of 5G wireless systems, more performance metrics should be considered.

    ¶23: Realistic channel models with proper accuracy-complexity trade-off are indispensable for some typical 5G scenarios, such as massive MIMO.

    ¶24: Characterizing non-stationary high-mobility channels is challenging, also.

    ¶25: Spatial modulation concept can be use in massive MIMO system development to solve signal processing complexity problem.

    ¶26: Regulating the transmit power is essential for managing the mutual interference of Cognitive Radio and primary systems reliably and practically in 5G

    ¶27: The article has talked about the performance requirements of 5G wireless communication system, proposed a new heterogeneous 5G cellular architecture, discussed some short-range communication technologies, and some key technologies that can be implement into 5G wireless system to satisfy the expected performance requirement.

    Wang, C. X., Haider, F., Gao, X., You, X. H., Yang, Y., Yuan, D., … & Hepsaydir, E. (2014). Cellular architecture and key technologies for 5G wireless communication networks. IEEE communications magazine, 52(2), 122-130.

    =====================================
    Abandon Articles:

    Agyapong, P. K., Iwamura, M., Staehle, D., Kiess, W., & Benjebbour, A. (2014). Design considerations for a 5G network architecture. IEEE Communications Magazine, 52(11), 65-75.

    Li, Q. C., Niu, H., Papathanassiou, A. T., & Wu, G. (2014). 5G network capacity: Key elements and technologies. IEEE Vehicular Technology Magazine, 9(1), 71-78.

    Peng, M., Li, Y., Zhao, Z., & Wang, C. (2015). System architecture and key technologies for 5G heterogeneous cloud radio access networks. IEEE network, 29(2), 6-14.

    Rost, P., Bernardos, C. J., De Domenico, A., Di Girolamo, M., Lalam, M., Maeder, A., … & Wübben, D. (2014). Cloud technologies for flexible 5G radio access networks. IEEE Communications Magazine, 52(5), 68-76.

  11. TO: Professor Ellis

    FROM: Hector Dextre

    DATE: 09/10/2019

    SUBJECT: The benefits and challenges in the integration of Artificial Intelligence (AI) and Internet of Things (IOT)

    REVERSE OUTLINE

    CITATION

    Katare, G., Padihar, G., & Qureshi, Z. (2018). Challenges in the Integration of Artificial Intelligence and Internet of Things. International Journal of System & Software Engineering, 6(2), 10–15. Retrieved from http://search.ebscohost.com.citytech.ezproxy.cuny.edu/login.aspx?direct=true&db=aci&AN=134633037&site=ehost-live&scope=site

    The purpose of this memo is to summarize the benefits and challenges in the integration of Artificial Intelligence and Internet Of Things. Both of them need to combine because the combination of these two techniques provides the definition to generate new technologies. On the other hand, this technology provides us very smart systems in health, education, financial and environmental areas, among others.

    INTRODUCTION (Main idea/ point):Without the presence of Artificial Intelligence, Internet Of things has little value because AI is changing IOT so much. By consolidation of AI and IOT, we obtain a new set of product functions and capabilities. Businesses all around the world are quickly advancing AI and IOT to make new network of products and services.

    INTERNET OF THINGS (Main idea/point): The head objective of development of Internet Of Things is to connect the internet with physical world and the environment with wireless networks. Also, it is considerably a network of physical devices and a system of machines outfitted with information collecting technologies. It is also known as internet of objects. Its application is given in agriculture, health care, poultry, farming, etc.

    ARTIFICIAL OF THINGS AND ITS USE CASES (Main idea/point): Artificial Intelligence is a process of human intelligence which will be experienced by machines. The applications of AI are Machine learning and deep learning which they have the ability to automatically learn and improve performance from experience. Some use cases in AI are virus detection, image recognition, loan analysis, medical diagnosis, computer games, etc.

    INTEGRATION OF AI AND IOT (Main idea/point): We obtain many technologies in many areas on integrating AI and IOT. The formula is : Artificial Intelligence + Internet Of Things = Integration of AI and IOT.

    AUTOMATION OF AI AND IOT (Main idea/point): Forwarding thinking, Modeling & Data governance strategy, applying advance machine learning and deep learning, image processing, data analytics and visualization and large scale network transformation and migration.
    BENEFITS OF AI AND IOT (Main idea/point): On combining AI with IOT makes our business smarter, we get these systems together at a personal level in devices, will shake the digital world and will produce the tsunami of big data.

    CHALLENGES OF AI AND IOT (Main idea/point): AI and IOT have to ensure that data is secure and in safe hands, a large number of different devices lead to more complex ecosystems, inability of an AI program to perfectly perform basic tasks.

    These citations were not selected:

    Kugler, L. (2019). Being Recognized Everywhere: How facial and voice recognition are reshaping society. Communications of the ACM, 62(2), 17–19. https://doi-org.citytech.ezproxy.cuny.edu/10.1145/3297803

    YUAN QI1, & JING XIAO2. (2018). Fintech: AI Powers Financial Services to Improve People’s Lives. Communications of the ACM, 61(11), 65–69. https://doi-org.citytech.ezproxy.cuny.edu/10.1145/3239550

    O’Sullivan, A., & Thierer, A. (2018). Counterpoint: Regulators should allow the greatest space for AI innovation. Communications of the ACM, 61(12), 33–35. https://doi-org.citytech.ezproxy.cuny.edu/10.1145/3241035

    Lewis, T. G., & Denning, P. J. (2018). Learning machine learning. Communications of the ACM, 61(12), 24–27. https://doi-org.citytech.ezproxy.cuny.edu/10.1145/3286868

  12. TO: Professor Ellis
    FROM: Zhao
    DATE: 9/3/19
    SUBJECT: The 5G Dream
    (2019, September). The 5G Dream. MaximumPC, 44-49.
    The article I selected is about the upcoming 5G network and how it can improve our daily lives.
    1st paragraph sentence: As we see an increase of device connected to the internet, 5G is becoming more and more vital to support them all.
    2nd paragraph sentence: A way the 5G network can improve our lives is by allowing operators faster response time for better and safer traffic control.
    3rd paragraph sentence: Speed, is by itself the most important features of this up and coming network.
    The four other articles you do not choose and cite the sources.
    1. Build a Better Home Server With Docker
    2. Set Up a Secure Shell Honeypot
    3. Build a Blog with Open Live Writter
    4. Synchronize Your Life With Wunderlist

  13. TO: Professor Ellis
    FROM: Amir Radoncic
    DATE: 09/10/2019
    SUBJECT: A century-long commitment to assessing artificial intelligence and its impact on society
    This memo is the reverse outline for the 500 words summary project.
    Reverse outline:
    In the first paragraph, it talks about how AI is starting to be used in urban everyday life. It talks about the rising concerns about the potential AI-enabled systems. With some pros and cons, being talked about it argues if having AI systems is worth it or not. The Arthur argues about certain AI systems target certain groups of people in certain societies.
    In the second paragraph it states how certain AIs can be placed in places where there has been a lot of information gathered and how an AI can complement the information gathered. They used public surveys and gathered information like gender, race and nationality.
    “December 2014, the standing committee anticipated that several years would be avail-able for shaping the project, engaging people with expertise across the social sciences and humanities, as well as AI, identifying a focal topic, and recruiting a study panel. Within a few months, however, it was clear that AI was entering daily life and garnering intense public interest at a rate that did not allow such a leisurely pace. The standing commit-tee thus defined a compressed schedule and recruited Peter Stone of The University of Texas at Austin (co-author of this article) as the chair of the report s study panel. Together they assembled a 17-member study panel comprising experts in AI from academia, corporate laboratories, and industry, and AI-savvy scholars in law, political science, policy, and economics”
    j, G. barbara. (2018, December). A century-long commitment to assessing artificial intelligence and its impact on society. Retrieved from http://web.a.ebscohost.com/ehost/detail/detail?vid=9&sid=646938b4-3f3f-48a8-b94c-74c07ca92bb4@sdc-v-sessmgr02&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=134657120&db=aci

  14. From: Mustafa Nagi
    To: Professor Ellis
    09/10/2019
    Subject: 500-Word Summary of Heuston, G & Block, I This memo is intended to summarize and analyze the article “The Computer as a Significant Other.”

    Computers have become more and more important in people’s lives. People around the world need them. This article “The Computer as a Significant Other “, tells us how computers are used and good source to get information. In many parts of our lives we use computers, but we do not realize that all our information we are sharing in the devices, can be recovered or reused in real life. When you have that much knowledge about computers and how to use in professional way, that may make it less hard to hide information or get rid of it. In many places people do not care much about losing information. Others use computers to get people’s personal Information by hacking their computers or phones. It is not really safe; however, some people try to use difficult passwords to keep their information secure.

    Technology and computers are very connected to people, because they store their important things inside as well they use it to get many things done. The police department can use the computer as a valuable source of information, or to collect more evidence about crimes which happen by technology or devices. In addition, that they can do studies on how people behave by the usage of the computers. The computer is like a witness that records many thing you do.

    Computer information can be stolen and sold. People should try their best not to share the most important information in computer. People should not give unlimited trust to the computer because in some cases it is safe and in many is not. FBI and investigators in many cases could find many things are not related to the case they are looking for information about.

    References

    Heuston, G., & Block, J. (2009). The Computer as a Significant Other. PsycEXTRA Dataset. doi: 10.1037/e511552010-003

  15. From: Tariq Hemraj
    To: Professor Ellis
    09/102019
    Subject:

    This memo is to summarize and educate you on self-driving cars. Self-driving is the future of motor vehicles and whilst it loks like a pro they also have their cons.
    Juhász, Á. B. (2018). The Regulatory Framework and Models of Self-Driving Cars. Proceedings of Novi Sad Faculty of Law / Zbornik Radova Pravnog Fakulteta, Novi Sad, 35(3), 1371–1389. Received from https://doi.org/10.5937/zrpfns52-19047
    Body Paragraph 1. Thoughts of Self Driving Cars
    – This 1st body paragraph will go over my thoughts and also the author’s thoughts on self-driving cars. Before we get in depth on the, who what where when why and how, I want to introduce all the thoughts on the topic.
    Body Paragraph 2. Pros
    – This paragraph will go over the pros of self-driving cars.
    Body Paragraph 3. Cons
    – This paragraph will go over the cons of self-driving cars.
    Body Paragraph 4. Road Regulations
    – This Paragraph will go over the regulations set up by the authorities that applies to self-driving cars.
    Body Paragraph 4. Use Cases of Self Driving Cars
    – This paragraph will
    Articles not chosen

    1 : Hamers, L. (2016). The Future of Cars. Science News, 190(13), 34–35. Retrieved from http://citytech.ezproxy.cuny.edu:2048/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=120095897&site=ehost-live&scope=site

    2 : Newcomb, D. (2014). Who Should Be the Self-Driving Car’s Moral Compass? PC Magazine, 44–46. Retrieved from http://citytech.ezproxy.cuny.edu:2048/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=98472576&site=ehost-live&scope=site

    3 : COSTA, D. (2016). Let Go of the Wheel. PC Magazine, 6–7. Retrieved from http://citytech.ezproxy.cuny.edu:2048/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=117743782&site=ehost-live&scope=site

    4 : Hoybjerg, P., & Buck, A. (2018). The Self Driving Car: A Disruptive Innovation on Established Industries and Legal Practices. Utah Bar Journal, 31(6), 32–38. Retrieved from http://citytech.ezproxy.cuny.edu:2048/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=133158732&site=ehost-live&scope=site

  16. TO: Dr. Ellis

    FROM: Marco M

    DATE: 9/8/2019

    SUBJECT: Reverse outline on Cyber Security in Quantum Era

    WALLDEN, P., & KASHEFI, E. (2019). Cyber Security in the Quantum Era. Communications of the ACM, 62(4), 120–129. https://doi-org.citytech.ezproxy.cuny.edu/10.1145/3241037

    I am writing to inform you about how cyber security is affected in the quantum era. With Quantum theory in further development, how it can be applied to daily use and in terms of security on the internet.

    Reverse outline for cyber security I the quantum Era.

    Paragraph 1
    Reviews the initial scientific development of quantum theory in the early days.

    Paragraph 2
    Many countries around the world has nationals’ programs on quantum technologies program including major tech companies like google, IBM, Intel and more.

    Paragraph 3
    Most importantly, quantum technology will still be the development of computation devices that uses quantum phenomena also known as quantum computer.

    Paragraph 4
    Quantum computer means quantum cyber security, which brings in potentially tougher security issues.

    Paragraph 5
    Explains what quantum cyber security is.

    Paragraph 6
    Quantum technology have positive and negative effects and is broken down into 3 groups.

    Paragraph 7
    In cryptography, they assume the worst in what could possibly happen.

    Paragraph 8
    Talks more about the second category that is allow quantum technology access.

    Paragraph 9
    Examines security and privacy protocols.

    Paragraph 10
    Clarified that it’s not an extensive research of all quantum cyber security

    Paragraph 11
    Intention is to clear any misconceptions and organize/categories research.

    Paragraph 12
    Starts myth busting about quantum computer.

    Paragraph 13
    Quantum computer is faster than classic computer rather then they are able to operate different algorithms that are impossible for classic computers.

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