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(Solved): This is an Individual Challenge. You must work alone to solv...

(0)   In java <3 tysm This is an Individual Challenge. Yo This is an Individual Challenge. You must work alone to solve this problem. You may not collaborate or share work with other students. Everything you need to know to solve this problem has been covered in the course materials prior to this challenge. Review those materials to refresh your memory and to find things you might have missed. Do not use any language or library features that have not been specifically covered in the prior course materials. Problem Description and Given Info Write (define) a public static method named getSmallest, that takes three arguments (all arguments will be ints). When this method is called, it should return (as an int) the smallest of the three arguments passed to it. Examples: get Smallest(0, 0, 0) will return getSmallest(2, 1, 3) will return 1 getSmallest(100, 13, 7) will return 7 You may wish to write some additional code to test your method. 266606.2215050.qx3zqy7 LAB ACTIVITY 10.1.1: Smallest (Java) Individual Challenge 0/10 Main.java Load default template... 1 public class Main { public static void main(String[] args) { // you may wish to write some code in this main method // to test your method. } 9) 10.2 Longest(Java) Individual Challenge This is an Individual Challenge. You must work alone to solve this problem. You may not collaborate or share work with other students. Everything you need to know to solve this problem has been covered in the course materials prior to this challenge. Review those materials to refresh your memory and to find things you might have missed. Do not use any language or library features that have not been specifically covered in the prior course materials. Problem Description and Given Info Write (define) a public static method named longest that takes two arguments (all arguments will be strings). When this method is called, it should determine which string is longer, and return that string. If both arguments are the same length, then this method should return the first argument string. Examples: longest("abc", "ab") longest ("hello", "goodbye") longest ("thursday", "12345678") will return will return will return "abc" "goodbye" "thursday" You may wish to write some additional code to test your method. Hints: Remember that you can call the length method on a string object, to get the number of characters in that string. For example, given the following declaration and initialization String name = "Bob Smith"; int charCount = name.length(); the above line would store the value 9 in the variable charCount, because there are 9 characters in the string "Bob Smith". 2666062215050.qx3zay7 LAB ACTIVITY 10.2.1: Longest(Java) Individual Challenge 0/10 Main.java Load default template... nmin 000) 2 3 4 5 6 7 8 1 public class Main { public static void main(String[] args) { // you may wish to write some code in this main method // to test your method. } 9) 10.3 Is Sorted (Java) Individual Challenge This is an Individual Challenge. You must work alone to solve this problem. You may not collaborate or share work with other students. Everything you need to know to solve this problem has been covered in the course materials prior to this challenge. Review those materials to refresh your memory and to find things you might have missed. Do not use any language or library features that have not been specifically covered in the prior course materials. Problem Description and Given Info Write (define) a public static method named issorted that takes three arguments (all arguments will be ints). This method should determine if the three argument values are in ascending order. The method should return the boolean value true if the argument values are in ascending order, otherwise it should return false. Examples: issorted(1, 2, 3) issorted (2, 3, 1) issorted (2, 3, 3) will return will return true false true will return You may wish to write some additional code to test your method. 266606.2215050.qx3zQy7 LAB ACTIVITY 10.3.1: Is Sorted (Java) Individual Challenge 0/10 Main.java Load default template... 2 3 4 min 00 0 1 public class Main { public static void main(String[] args) { // you may wish to write some code in this main method // to test your method. 5 } 6 7 

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(Solved): -Algorithmic class-i have pseudo codes and i want to convert...

-Algorithmic class-i have pseudo codes and i want to convert them into java, some words are in french but i can translate if needed.There's like 4-5 pseudo codes.-#1Varibles :nbHeures,tauxHoraire,SalaireDÉBUT1 Afficher "Nomb

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(Solved): -1-NYU Schack - Real Estate Capital Markets – ASSIGNMENT #...

-1-NYU Schack - Real Estate Capital Markets – ASSIGNMENT #1 Professor Meie Frankel• FOLLOW INSTRUCTIONS!! • Due by TUESDAY, OCTOBER 15 AT 6 PM; submit to Classes website- Assignments • NO LATE PAPERS WILL BE ACCEPTED

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(Solved): BUNDLE PAYMENT MODEL HEALTHCARE ECONOMICS:This paper is writ...

BUNDLE PAYMENT MODEL HEALTHCARE ECONOMICS:This paper is written in a team, it’s a 10 pages paper of healthcare economics, each section is allotted to someone to write, my part is IIII, I think this part can be written without needing the rest of the paper, I will away the rest of parts as my team starts putting their share. Look at the highlighted section, this is what you are supposed to write about, one and half page should be good, provide legit references. You can use web or book but has to be valid. Make sure no grammar eors and this is masters level paper so no unprofessional writing please.Paper Outline:Intro – Background - What are bundled payments? – team memember 1 · One of several new payment alternatives in Medicare and Medicaid· Designed to hold health providers accountable for the cost and quality of care· Encourage and reward better healthcare value· Single payment is made for all the services associated with an episode of care Part I - Potential Advantages/Disadvantages -team member 2Advantages: · Gives providers strong incentives to keep their costs down · Encourages collaboration across diverse providers and institutions · Encourages the development and implementation of care pathways that follow evidence-based guidelines Disadvantages: · Bundles could inhibit certain types of care coordination, even as it encourages other types· It can be complicated to define and track the type of care that should be included in the bundled payments· Bundled payments could encourage destructive competition for patients with profitable bundles Part II – Bundled Payment Models for Care Improvement (BPCI) Initiative – team member 3CMS took the lead in developing several bundled payment models, such as the Medicare Bundled Payment for Care Improvement (BPCI) and Comprehensive Care for Joint Placement programs · Bundled Payment Models for Care Improvement (BPCI) Initiative· The program cuently reimburses participants for 48 different types of episodes of care, but this is expected to increase under MACRA. · Providers can participate in four tracks of the BCPI (4 models) · Comprehensive Care for Joint Placement programs  Part III – Bree Collaborative Bundled Payment Examples (maybe pick 2-3 and elaborate on how they have been effective?) – team member 4· Bariatric· Hip/Joint· Lumbar· Coronary Artery Bypass Part IIII - How do providers succeed in the bundled payments model? – YOUR TASK!!· Key successes· Increasing provider communication· Execute efficient care coordination strategies Increasing provider communication· Execute efficient care coordination strategies Conclusion – Summary/Key Takeaways – Team member 6 · Wrap up qfile_636870659203815210_124887_1.docx

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(Solved): -Download a Vulnerability scanner-Conduct a scan on a server...

-Download a Vulnerability scanner-Conduct a scan on a server-Write a one- to two-page summary of your findings to include (a) number of items passed and (b) number of compliance items failed.-Provide a minimum of two screenshots of the scan

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(Solved): -Create a new .Net Core MVC web application. Use one of the ...

-Create a new .Net Core MVC web application. Use one of the Visual Studio Bower Package Manager to add the JQuery Mobile-Bower liary to the project. Build a clock with an alarm sized to whatever device the application is displayed on. Use JQuery Mobi

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(Solved): PYTHON (JUPYTER NOTEBOOK) PROJECT - GENERAL DESCRIPTION· Th...

PYTHON (JUPYTER NOTEBOOK) PROJECT - GENERAL DESCRIPTION· This assignment needs to be delivered in a Jupyter Python Notebook (.ipynb)· Deep understanding and knowledge of Clustering Algorithms is required· Delivery Date: end of Sunday 2nd June (CET time)Aim is to cluster 51 objects (cases) according to a set of “clustering variables” through the implementation of various unsupervised clustering algorithms. Being an unsupervised learning problem, number of clusters in the data (if any) is unknown.For the found ´clusters´ by the various clustering algorithms, it´ll be of interest to compare them according to · the clustering variables and · to an additional set of variables not used in the clustering (the “profiling variables”).Some basic references are included at the end of this document to facilitate problem understanding and what is required to deliver. These are denoted as [xxx] in the following. No need to read in full such references. Usually by scrolling through relevant pages, formulas, images is enough to understand what is required.I highlight in this format, those observations that require great attention to ensure that this Python project delivers what it is required-asked.For any doubts, please contact me by email at XXXXXXXXXX. It´s expect that the coder in charge of this assignment may have questions for the various tasks. Hence, I´d expect to be contacted as the project advances.DATASETIn Excel File “Clustering Dataset clean”. · Number of cases (objects) = 51 (rows 3:53, 51 objects or cases in total)· Clustering Variables Set 1 (“CVS”) (cols B:U, 20 variables or features in total)· These are the used to cluster the data· Profiling Variables Set (“PVS”) (cols V:CG, 64 variables or features in total)· these variables are NOT used by the clustering algorithms. Instead, they´re used to further characterize the clusters.PART IINITIAL DATA EXPLORATION AND DATA-PREPROCESSING· Obtain basic statistical information for ALL the variables in CVS and PVS: mean, max, min, median, std dev, skew, kurtosis, Kolmogorov-Smirnov test for normality …· For CVS, PVS and CVS+PVS obtain Pearson coelation and the Spearman coelation matrices.· Normalize variables according to these two Normalization Methods (“NM”)· NM1 – Z-score: subtract mean and divide by standard deviation· NM2 – Min-Max Method: subtract minimum and divide by absolute difference between minimum and maximumIn what follows, all calculations related to clustering will be done using BOTH normalization methods.PRINCIPAL COMPONENT ANALYSIS (PCA)Using both normalization methods:· Perform standard PCA on CVS· Show factor loadings, order factors by % variance explained and show variance explained (by each factor and cumulative)· Show plots of CVS data on the two most important factorsPART IIUsing both normalization methods, implement for Dataset CVS the following 8 Clustering Methods (“CM”).Before specifying such clustering algorithms, a common definition of standard performance and valuation metrics. Note that specific nuances should be considered depending on the type of clustering algorithm (partitional, hierarchical, density-based). For example, in Partitional-type algos, clustering structure well depend on the chosen number of clusters (k), whereas in Hierarchical algos, the clustering structure will be determined by the ´height´ at which the coesponding dendrogram is cut.ERROR MEASURES· For the overall clustering structure (see slides XXXXXXXXXXin [TAN04] or slide #8 & slide #20 in [RICCO])· TSS (SSE) Total Sum of Squares· WSS Within Clusters Sum of squares · BSS Between Clusters Sum of squaresTSS (SSE) = WSS + BSSSILHOUETTE WIDTH (COEFFICIENT) AND PLOT· See slide #10 in [RICCO2] or slides #19/#46 in [UMASS1]. · Preferably, I´d like Silhouette plots as that one in [DATANOVIA]DENDROGRAM PLOTS· Preferably, I´d like Silhouette plots as that one in [DATANOVIA]DISTANCE MEASURES· Although main distance metric that will be used is the Euclidean distance, set up the Python project by also accepting the Manhattan and Mahalanobis distance metrics. See pages 1-2 in [NELSON12]PARTITIONAL CLUSTERING ALGORITHMS· CM1 - Standard K-means· CM2 - K-medoids as in [MAIONE18] – also known as “Partitioning around medoids (PAM)”. See reference [TAN04]· CM3 - Bisecting K-means algorithm. See reference [TAN04]As these 3 algorithms are susceptible to initialization issues (i.e. the chosen initial clusters´ centers), run n=200 iterations for different initializations of random cluster centers.For each run, consider k = 1, 2, 3, 4, 5 number of clusters. Averaging across the n = 200 runs, · Compute TSS, WSS and BSS for k = 1, 2, 3, 4, 5· Compute Overall Average Shilouette Width for k = 1, 2, 3, 4, 5· Compute Shilouette Width for each cluster for k = 1, 2, 3, 4, 5 (e.g. for k=4, 4 Silhouette coefficients)· Plot Histogram distribution of TSS, WSS and BSS for k = 1, 2, 3, 4, 5 · Plot Histogram distribution of Overall Average Shilouette for k = 1, 2, 3, 4, 5· On same plot, taking k (number of clusters) as x-axis, show in y-axis both · Average (across number of clusters) of within-cluster dissimilarities WSS (as in slide #19 in [UMASS], or slide #94 in [TAN04]), and · Average Silhouette Width (as in slide #19 in [UMASS] or slide #10 in [RICCO2])For following sections, performance or otherwise metrics from these algorithms should be taken with respect their average (across the n=200 runs) valuesHierarchical Clustering Algorithms· 4 clustering algorithms: all 4 are of the Agglomerative type· Use the following approaches to measure the distance between clusters. See reference [TAN04]· CM4 - Single Link· CM5 - Complete Link· CM6 - Average Link· CM7 - Ward´s MethodFor each of these ´hierarchical´ clustering methods, obtain SSE (WSE), BSE, and display coesponding DendrogramsDENSITY-BASED CLUSTERING ALGORITHMS· CM8 - DBSCAN· Use various combinations of the two parameters in this method (See reference [TAN04])· Eps · MinPoints PART IIIPOST-PROCESSINGFor all the clustering structures obtained by the 8 clustering algorithms, it´ll be calculated (see slides #99-100 in [TAN04])· For each cluster in each clustering structure, the Within-Cluster Sum of Squares (WSS) as a measure of Cluster Cohesion· For the overall clustering structure (see slide #99 in [TAN], or slides #8/#20 in [RICCO])· TSS Total Sum of Squares· WSS Within Clusters Sum of Squares · BSS Between Clusters Sum of squares For all of them, it´ll be shown the (2-dimensional) plot of the 51 objects with respect to the two most important principal components obtained in previous section, with different colourings/markers representing different clusters. See slides #22-23 in [RICCO].For all of them, it´ll calculated the Silhouette coefficient for each cluster and the average Silhouette coefficient for the overall clustering structure (see slide #102 in [TAN04]) and display typical graph as in slide #22 in [UMASS]). Also show similar graph with respect to number of clusters as in slide #10 in [RICCO2].In addition, following [RICCO], perform the following and show similar tables and graphs:UNIVARIATE CHARACTERIZATION· Characterizing the partition (see slides #8-11 in [RICCO])· Characterizing the clusters / Quantitative variables V-test (see slides #12-14 in [RICCO])· Characterizing the clusters / One group vs. the others – Effect size (see slides #15-17 in [RICCO])· Characterizing the clusters / Categorical variables V-test (see slides #18 in [RICCO])MULTIVARIATE CHARATERIZATION· Characterizing the partition / Percentage of variance explained (see slide #20 in [RICCO]). Already calculated (TSS, WSS, BSS)· Characterizing the partition / Evaluating the proximity between the clusters (see slide #21 in [RICCO]).· Characterizing the clusters / In combination with factor analysis (see slides #22-23 in [RICCO])· Characterizing the clusters / Using supervised approach – E.g. Discriminant Analysis (see slide #24 in [RICCO])PROFILING VARIABLESLast, compute basic statistics for the clusters obtained in each clustering structure with respect the “Profiling Variables”.PART IIICLUSTERING EVALUATIONAs there´s no external information to validate the goodness of the various clustering structures, following [TAN04], calculate and display as applicable (some have already been calculated):· TSS, BSS, WSS· coelation between the “Proximity/Similarity” and “Incidence” matrices (see slide #87 in [TAN04])· Similarity matrix as in slide #89 in [TAN04]· Cophenetic coelation (see slides #49-51 in [UMASS]) as in slide #51 in [UMASS]· Silhouette plot as in slide #22 in [UMASS1] (with Silhouette coefficients for each cluster and the average for the whole clustering structure)Also, as per slide #97 in [TAN04], generate n=500 sets of random data, spanning the same ranges as the features of DataSet CVS, and · Obtain average SSE and display same histogram as in slide #97 of [TAN04]. · Do the same as per slide #98 of [TAN04] but for Coelation between incidence and proximity matrices· Do the same but with average Silhouette Coefficient · Do the same but with average Cophenetic CoelationGiven the (total) SSE, (average) Coelation between incidence and proximity matrices, (average) Cophenetic Coelation, and (average) Silhouette Coefficient obtained by each clustering method, obtain the likelihood of such values (obtained by each clustering algorithm) given these random runs (some sort of p-value). REFERENCES[DATANOVIA] Cluster Validation Statistics. Available at: https:www.datanovia.com/en/lessons/cluster-validation-statistics-must-know-methods/ [NELSON12] Nelson, J.D XXXXXXXXXXON K-MEANS CLUSTERING USING MAHALANOBIS DISTANCE. Available at: https:liary.ndsu.edu/iitstream/handle/10365/26766/On%20K-Means%20Clustering%20Using%20Mahalanobis%20Distance.pdf?sequence=1 [MAIONE18] Maione, C. Nelson, D.R., and Melgaço Baosa, R XXXXXXXXXXResearch on social data by means of cluster analysis. Applied Computing and Informatics. https:doi.org/10.1016/j.aci XXXXXXXXXX. [RICCO] Rakotomalala, R. Interpreting Cluster Analysis Results. Available at: http:eric.univ-lyon2.f~ricco/cours/slides/en/classif_interpretation.pdf [RICCO2] Rakotomalala, R. Cluster analysis with Python - HAC and K-Means. Available at: https:eric.univ-lyon2.f~ricco/cours/didacticiels/Python/en/cah_kmeans_avec_python.pdf [RICCO3] Rakotomalala, R. K-Means Clustering. Available at: https:eric.univ-lyon2.f~ricco/cours/didacticiels/Python/en/cah_kmeans_avec_python.pdf [TAN04] Tan, Steinbach and Kumar XXXXXXXXXXData Mining Cluster Analysis: Basic Concepts and Algorithms. Available at https:www-users.cs.umn.edu/~kumar001/dmbook/dmslides/chap8_basic_cluster_analysis.pdf[UMASS] UMASS Landscape Ecology Lab. Finding groups -- cluster analysis. Part 1. Available at https:www.umass.edu/landeco/teaching/multivariate/schedule/cluster1.pdf clustering-calculation-clean-lt2kn23o.docx dataset-clustering-clean-x0ybwvkd.xlsx

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(Solved): -:Assignment Of CCN:-Name College Roll No University Roll N...

-:Assignment Of CCN:-Name College Roll No University Roll No Class BS(CS)Subject Computer Communication & NetworkSubmitted to Semester 4thGroup Evening Q1: Token Ring:Token ring is also a LAN technology. It allows network devices to access the network by passing a special signal called token.FDDI: FDDI (Fiber Distributed Data Interface) is a set of ANSI and ISO standards for data transmission on fiber optic lines in a local area network (LAN) that can extend in range up to 200 km (124 miles). The FDDI protocol is based on the token ring protocol. FDDI is frequently used on the backbone for a wide area network (WAN).Q2: ARCNET:Attached Resource Computer Network (abbreviated ARCNET or ARCnet) is a communications protocol for local area networks. ARCNET is a widely-installed local area network (LAN) technology that uses a token-bus scheme for managing line sharing among the workstations and other devices connected on the LAN.Q3: Address Resolution Protocol (ARP):The address resolution protocol (ARP) is a protocol used by the Internet Protocol (IP), specifically IPv4, to map IP network addresses to the hardware addresses used by a data link protocol. The protocol operates below the network layer as a part of the interface between the OSI network and OSI link layer.Q4: Asynchronous transfer mode (ATM):Asynchronous transfer mode (ATM) is a switching technique used by telecommunication networks that uses asynchronous time-division multiplexing to encode data into small, fixed-sized cells. This is different from Ethernet or Internet, which use variable-sized packet for data or frames.Q5: Broadband: It is a technique to transmit large amount of data such as voice and video over a long distance. It is faster than baseband.Baseband:It is a communication technique in which digital signals are placed on the transmission line without change in modulation. Digital signals are commonly called baseband signals.Q6: Bus:A bus is a communication system that transfers data between components inside a computer, or between computers. This expression covers all related hardware components (wire, optical fiber, etc.) and software, including communication protocols.All buses consist of two parts. A data bus and an address bus. The data bus transfers actual data whereas the address bus transfers information about where the data should go.Q7: Checksum:A checksum or hash sum is used for the purpose of detecting errors which may have been introduced during its transmission or storage. It is usually applied to an installation file after it is received from the download server.Q8: Cyclic redundancy check (CRC):A cyclic redundancy check (CRC) is a method of detecting errors in the transmission of data. Before data is sent, a CRC number is calculated by running the data through an algorithm and producing a unique number. At the receiving end of the transmission, the data is run through the same algorithm again to produce thenumber. If numbers match, the data was sent error free. The unique value generated from the algorithm is called a checksum.Q9: Datagram: A datagram is a basic transfer unit associated with a packet-switched network. The delivery, arrival time, and order of arrival need not be guaranteed by the network.Q10: Electromagnetic interference (EMI):Electromagnetic interference (EMI), also called radio-frequency interference (RFI). When in the radio frequency spectrum, is a disturbance generated by an external source that affects an electrical circuit by electromagnetic induction, electrostatic coupling, or conduction.Q11: Ethernet:Ethernet is a LAN technology. It is based on bus topology but Ethernet network can be wired in star topology also. It is the most popular LAN because it is inexpensive and easy to install and manage. Ethernet network normally uses cables to transmit data.Ethernet is a family of computer networking technologies commonly used in local area networks (LANs) and metropolitan area networks (MANs). It was commercially introduced in 1980 and first standardized in 1983 as IEEE 802.3.Q12: Ethernet Types:­• Standard Ethernet (10 Mbps) can be configured with cables, hubs, or switches. CSMA/CD (Carrier sense multiple access with collision detection) uses this Ethernet.• Fast Ethernet (100 Mbps) was designed to compete with LAN protocols such as FDDI (Fiber Distributed Data Interface) or Fiber Channel.• The need for higher data rate resulted in the design of the Gigabit Ethernet (1000 Mbps or 1Gbps).• Ten Gigabit Ethernet (10GbE) is a group of computer networking technologies for transmitting Ethernet frames at a rate of 10Gbps (gigabits per second). Ten Gigabit Ethernet defines only full duplex. 10GbE can use either copper or fiber cabling.Q13: Gateway:Gateway is a device that connects two or more networks with different types of protocols. For example: The computers on a LAN requires gateway to access the internet.Bridges:Bridges is a device that connects two network segments. It is used to connect similar types of networks. Bridges is a Data link layer device.Q14: HDLC (High-level Data Link Control): HDLC (High-level Data Link Control) is a group of protocols or rules for transmitting data between network points (sometimes called nodes). In HDLC, data is organized into a unit (called a frame) and sent across a network to a destination that verifies its successful arrival.Point-to-Point Protocol (PPP):In computer networking, Point-to-Point Protocol (PPP) is a data link (layer 2) protocol used to establish a direct connection between two nodes. It can provide connection authentication, transmission encryption, and compression.Q15: Intermediate Devices:The Network layer decides what path data will take if the destination device is located on another network. Data passes through the network by devices called Intermediate devices.Q16: Internet Protocol (IP):The Internet Protocol (IP) is the protocol by which data is sent from one computer to another on the Internet. Each computer (known as a host) on the Internet has at least one IP address that uniquely identifies it from all other computers on the Internet.IPX (Internetwork Packet Exchange):IPX (Internetwork Packet Exchange) is a networking protocol from Novell that interconnects networks that use Novell's NetWare clients and servers. IPX is a datagram or packet protocol. IPX works at the Network layer of communication protocols and is connectionless. It may act as a transport layer protocol as well.Q17: SMTP (Simple Mail Transfer Protocol):SMTP (Simple Mail Transfer Protocol) is a TCP/IP protocol used in sending and receiving e-mail. Users typically use a program that uses SMTP for sending e-mail and either POP3 or IMAP for receiving e-mail.Simple Network Management Protocol (SNMP):Simple Network Management Protocol (SNMP) is a popular protocol for network management. It is used for collecting information from, and configuring, network devices, such as servers, printers, hubs, switches, and routers on an Internet Protocol (IP) network.Q18: Transmission Control Protocol (TCP): Transmission Control Protocol (TCP) is one of the main protocols in TCP/IP networks. Whereas the IP protocol deals only with packets, TCP enables two hosts to establish a connection and exchange streams of data. TCP guarantees delivery of data and also guarantees that packets will be delivered in the same order in which they were sent.User Datagram Protocol (UDP): UDP (User Datagram Protocol) is an alternative communications protocol to Transmission Control Protocol (TCP) used primarily for establishing low-latency and loss tolerating connections between applications on the Internet. Both UDP and TCP run on top of the Internet Protocol (IP) and are sometimes referred to as UDP/IP or TCP/IP. Both protocols send short packets of data, called datagrams.Q: IP Addressing:ClassFirst Octet RangeMax HostsA1-12616MB128-19164KC192-223254D224-239N/AE240-255N/A Q: What are Straight and Crossover cable:Pin IDStraight cableCrosssover cable1Orange - WhiteGreen – White2OrangeGreen3Green – WhiteOrange – White4BlueBrown – White5Blue-WhiteBrown6GreenOrange7Brown – WhiteBlue8BrownBlue - White Q: Network security issues:Hardware or Physical Security issues involve four types of issues:1) Physical2) Electrical3) Environmental4) Maintenance· Physical security is the protection of personal,hardware,software,networks and date from physical action and events that could cause serious loss or damage to an enterprise,agency or institution.· A short circuit is an electrical circuit that allows a current to travel along an unintended path with no or very low electrical impendance.· Environmental issues are defined as problems with the plant systems that have developed as a result of human interference or mistreatment of the plantet.· The act of maintaining or the state of being maintained nutrients essential to the maintenance of good health.Other types of network security issues or attacks:a) Active Attack:b) Distributed Attack:c) Phishing Attack:d) Password attack:e) Hijack attack:· An active attact is a network exploit in which a hacker attempts to make changes to data on the target or data en route to the target.· A distributed attack is an attack in which multiple compromised computer systems atteck a target ,such as a server,website or other network resource.· Phishing is a way of fraudulently acquiring sensitive information using social engineering and technical subterfuge.· In cryptanalysis and computer security,password cracking is the process of recovering passwords from data that have been stored in or transmitted by a computer system.· Hijacking is a type of network security attack in which the attacker takes control of communication – just as an airplane hijacker takes control of a flight – between two entities and masquerades as one of them.

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(Solved): Interim Report Cover PageTitle of report (This should be a c...

Interim Report Cover PageTitle of report (This should be a clear and unambiguous research question)Author’s name:St ID Number:Date submitted:ASHE Tutor:Introduction XXXXXXXXXXwords)· This should begin with a ief description of the research problem and the importanceenefit of investing time in the research –effects on the community/environment/economy – and crucially the links to sustainability. · The aims of the report should be concisely explained. Define any terms or acronyms used that the reader may not be familiar with.· The main body should include clear information with supporting data from well-sourced references (with citation), and have a clear, logical flow that provides a context for the question chosen. · The main purpose here is to introduce background literature that is relevant to your central research question and illustrate knowledge of the research area.· A very ief overview of what you are going to discuss in each section – this should provide the link to the Methods section.Methodology· Describe the procedure and methods adopted to collect quantitative and qualitative data.· Highlight the samples used and give reasons why you chose this sample set (e.g. number of people interviewed and their demographic makeup). · Briefly justify your approach and methods (e.g. why you chose a questionnaire rather than personal interview). · Use Google Docs/Forms to generate your questionnaire. · The questionnaire should illustrate a clear understanding of survey requirements and provide data suitable for data analysis for the FULL report (due in April 2020).Note: Include a copy of your blank questionnaire in the appendix – not in the methodology sectionReferencesAll sources should be cited in the body of the Interim Report.In addition, you should provide a full reference list – of suitable quality and quantity.Please use the Harvard referencing style, as set out in the MMU Liary Referencing guidelines – this is an important indicator of academic rigour. AppendicesThis should include any information that cannot easily be included in the body of your report such as an example questionnaire you have designed, a transcript of an audio or video interview.4 | Page interim-report-structure-template-uaptdgej.docx

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(Solved): 1ACCOUNTING METHOD II XXXXXXXXXXEQUITY ASSIGNMENT PART B ...

1ACCOUNTING METHOD II XXXXXXXXXXEQUITY ASSIGNMENT PART B STAGE 3 Due date/time Friday 19th October XXXXXXXXXX:00pmTele Strata Ltd (TSL) is an ASX listed company which provides fie to the home oadband connectivity for telecommunication services. The company has always been at the forefront of telecommunications development and, as a result, has been very successful. TSL has a strong record of rewarding its shareholders. The equity section of its Balance Sheet as at 30th June 20X6 presents as follows:EQUITY $ 000s Share Capital Ordinary shares paid to $4.50 40,320 7.5% pa $10.00 Preference shares 50,000 Reserves General Reserve 9,576 Foreign exchange translation 8,545 Retained Profits 11,872 TOTAL EQUITY 120,313NB All Ordinary shares were issued to $4.50.Share issue costs of $1,800,000 have been offset against the Ordinary share capital. The Preference shares are non-participating and dividends on those are paid every quarter on the last day of August, November, Feuary and May.2TSL pays Ordinary share dividends twice a year (ie an interim and final dividend) and also offers its shareholders regular non-renounceable share rights issues. On the 15th December 20X5 TSL offered a Dividend Reinvestment Plan for its Ordinary shareholders.The plan is effective on any Ordinary share dividends paid after the 1st January 20X6 and 50% of ordinary shareholders accepted the offer. Shareholders are issued with fully paid shares based on the value of the ASX share price on the day of the dividend declaration.The following are the ASX closing share prices for TSL on the dates provided.Date Closing Share Price $ Date Closing Share Price $ 1/7/X5 2.1221/1/X6 2.62 31/8/X XXXXXXXXXX/1/X6 2.89 12/9/X XXXXXXXXXX/2/X6 3.90 21/9/X XXXXXXXXXX/2/X6 3.95 1/10/X XXXXXXXXXX/3/X6 3.88 10/10/X XXXXXXXXXX/3/X6 4.00 2/11/X XXXXXXXXXX/4/X6 4.01 15/11/X XXXXXXXXXX/4/X6 3.97 30/11/X XXXXXXXXXX/4/X6 4.10 24/12/X XXXXXXXXXX/5/X6 4.12 2/1/X XXXXXXXXXX/5/X6 4.233STAGE 3 JOURNAL ENTRIES 10 marksOn 1st April 20X7 the Board of Directors decided raise some further capital to assist in the acquisition of another company. As a result it agreed to offer to Ordinary shareholders a non-enounceable share rights issue of 1 share for every 11 held. The rights shares can be taken up at 92% of the ASX share price on the day of the announcement of the issue. On the 30th April 20X7 the announcement was made and the offer was reasonably well received with 80% of shareholders taking it up. Money from the offer was received on the 31st May 20X7.REQUIRED From the primary information together with the information provided above and building on the information from Stages 1 and 2 of Part B of the assignment, record the general journal entries for all transactions for the period 1st April 20X7 to 30th June 20X7. If necessary round numbers to the nearest whole dollar or the nearest number of whole shares.In addition to share prices previously supplied you also have the following information. Date Closing Share Price $ Date Closing Share Price $ 15/6/X6 $4.1024/12/X6 $3.00 30/6/X6 $4.00 2/1/X7 $2.85 15/7/X6 $3.92 15/1/X7 $2.90 31/7/X6 $3.86 6/2/X7 $2.87 12/8/X6 $3.85 28/2/X7 $2.95 10/9/X6 $3.45 15/3/X7 $3.00 21/9/X6 $3.60 1/4/X7 $3.10 16/10/X6 $3.36 15/4/X7 $3.09 23/10/X6 $3.28 30/4/X7 $3.14 2/11/X6 $3.19 18/5/X7 $3.17 30/11/X6 $3.15 31/5/X7 $3.28 1ACCOUNTING METHOD II XXXXXXXXXXEQUITY ASSIGNMENT PART B STAGE 1 JOURNAL ENTRIES 8 marks There are two series of transactions detailed below which need attention in addition to the primary information provided. 1. In the Balance Sheet of PAL at 30/6/X4 there was provision for the payment of a dividend of 15 cents/share on the Ordinary shares. This was paid on the 30th September 20X4. 2. On 1st September 20X4 the Company Board decided to offer to Ordinary shareholders a non-renounceable share rights issue of 1 share for every 10 held. The rights shares can be taken up at 95% of the ASX share price on the day of the announcement of the issue. On the 15th September the announcement was made and monies received on the 15th October 20X4 from 75% of shareholder who accepted the offer.REQUIRED From the primary information together with the information provided above record the general journal entries for all transactions for the period 1st July 20X4 to 31st October 20X4.SOLUTION A Provision for Dividend account FOR THE Ordinary shares would have been created in the Balance Sheet at 30/6/20X4. The number of shares is ($23,046,000 + $3,000,000)/$3.00. The amount would have been 8,682,000*$0.15.Date Particulars DR CR 20X4 Preference Share dividend 101,250Sept 30 Provision for Dividend 1,302,300 Cash at Bank 1,403,550(Pay pref. dividend for 3 months ($6,750,000*6%*/4) and the provision account for ordinary share dividends) Date Particulars DR CR Oct 15 Cash at Bank 2,010,426 Ordinary Share Capital 2,010,426(Cash received on non-renounceable ordinary share rights issues being 8,682,000/10*75%*$3.25*95%) 1ACCOUNTING METHOD II XXXXXXXXXXEQUITY ASSIGNMENT PART B STAGE 2 JOURNAL ENTRIES SUGGESTED SOLUTION 15 marksBonus Shares After the Rights Issue there are now 9,847,500 shares issued of two groups (4,972,500 + 4,875,000). Apply 1:10 to those groups means issuing 497,250 and 487,500 ordinary shares. Bonus share issue value = (497, XXXXXXXXXX,500)*$2.90Date Particulars DR CR 20X7 Jan 15 General Reserve 2,855,775 Ordinary Share capital 2,855,775 (Issue of Bonus Ordinary shares on a 1:10 basis 2 $2.90/share.) Date Particulars DR CR 20X7 Feb 28 Preference share dividend 937,500 Cash at Bank 937,500 (Pay preference share dividend = $50,000,000 * 7.5%pa/4) Interim Dividend Total Shares after Bonus Issue = (4,972,500+497, XXXXXXXXXX,875,000+487,500) Interim dividend total value = (5,469,750+5,362,500)*0.04 = $433,290ENSURE THAT YOU CONTINUE TO TRACK THE SHARE GROUPS Date Particulars DR CR 20X7 March 15 Ordinary share interim dividend 433,290 Cash at Bank 214,500 Ordinary Share Capital 218,790 (Paying interim dividend $0.04/share on Ordinary shares) qfile_636752509255801712_122583_1.pdf qfile_636752509255801712_122583_2.pdf qfile_636752509255801712_122583_3.pdf

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