Reviewerly/exHarmony huggingface dataset:
Scrum based scaling using agile method to test software projects and its future solutions using in artificial neural networks

Nowadays the software development steps are evident and unavoidable in developing software projects. Every day software demands have has been growing in this field, provides new innovative ideas and support to incorporate the customer needs in software development. In this paper Agile methods with scalability have been focused which are very important to pre-planning software development process and business cost estimation. It has not provided an optimal solution to all projects in past history. So, in this paper, scrum procedure is applied which is based on Agile methods with scalability projects, and are estimated by some of the criteria such as function point, use case point, object point, and storyboard points based effort estimation parameters similar to the waterfall model, spiral model, and rapid development model. But none of them gives an accurate result. The main reason for most of the projects failure is because of inaccurate estimation. So scrum-based agile method with extended version providing reasonable accurate result in developed software projects is considered which is estimated using various metrics. Scrum procedure with Agile method is used on different projects. It is constructed based on an agile framework. Its categories are estimated in the machine learning procedure, whose results are meted based on different types such as small projects, medium projects, and large projects which are estimated in extended versions of scrum based Agile methods. They construe 70% of software based on agile methods. Its estimation results are justified in the machine learning processes such as Bayesian regression using back propagation neural network.
An Advanced Relevance Feedback Method to Improve Performance of CBIR using Convolutional Neural Network and Comprehensive Values

Content-Based Image Retrieval (CBIR) is extensively used technique for image retrieval from large image databases. However, users are not satisfied with the conventional image retrieval techniques. In addition, the advent of web development and transmission networks, the number of images available to users continues to increase. Therefore, a permanent and considerable digital image production in many areas takes place. Quick access to the similar images of a given query image from this extensive collection of images pose great challenges and require proficient techniques. From query by image to retrieval of relevant images, CBIR has key phases such as feature extraction, similarity measurement, and retrieval of relevant images. However, extracting the features of the images is one of the important steps. Recently Convolutional Neural Network (CNN) shows good results in the field of computer vision due to the ability of feature extraction from the images. Alex Net is a classical Deep CNN for image feature extraction. We have modified the Alex Net Architecture with a few changes and proposed a novel framework to improve its ability for feature extraction and for similarity measurement. The proposal approach optimizes Alex Net in the aspect of pooling layer. In particular, average pooling is replaced by max-avg pooling and the non-linear activation function Maxout is used after every Convolution layer for better feature extraction. This paper introduces CNN for features extraction from images in CBIR system and also presents Euclidean distance along with the Comprehensive Values for better results. The proposed framework goes beyond image retrieval, including the large-scale database. The performance of the proposed work is evaluated using precision. The proposed work show better results than existing works.
The Impact of the Adjustment of China’s Industrial Structure on the Employment of College Graduates in 2016

The year 2016 witnessed a stabilization and recovery of new employment in urban areas. In September, a total of 10.67 million new jobs were created in urban areas, and the rate of registered urban unemployment was 4.04% across the country, indicating that the annual employment target was achieved ahead of schedule. The increasing pressure on employment in the process of cutting overcapacity called for more efforts from the government on its employment policies. So far, the government has introduced three employment-related policies. Now, the employment situation remains stable, which is mainly attributable to the following four factors, namely, the rate of economic growth within a reasonable range, the continuous optimization of the industrial structure, the release of the bonus from reforms, and the implementation of employment policies. The regional transfer of industry has exerted an impact on the distribution in the employment of college graduates to some extent. Against the backdrop of industrial transformation and upgrading, graduates have the highest proportion of employment in the tertiary industry, and the proportion of graduates engaged in education, medical care and information occupations continues to increase. It is recommended that more emphasis should be put on the employment of college graduates, attention should be paid to the employment stability of graduates, the entrepreneurial services for college graduates should be optimized and more diverse, and effective and flexible services should be provided; it is also recommended that the statistics and forecast of talent demands should be strengthened, the degree of conformity between college talent cultivation and market demand should be improved and importance should be given to the quality of employment for graduates.
We Seek and Use Visual Structure

People use visual structure to help them extract information from what they see. Therefore, interactive systems that display information in structured ways allow people to extract the desired information more easily and quickly. This chapter gives examples of structured vs. nonstructured information displays. For example, an important goal in presenting information is to provide a visual hierarchy—an arrangement of the information that breaks it into distinct sections and subsections, labels sections prominently to clearly identify their content, and presents higher-level sections more strongly than lower-level ones. This allows people, when scanning information, to separate what is relevant to their goals from what is irrelevant instantly and focus on the relevant information.
New Encryption technique for improving time and speed for Embedded Applications 

Lightweight cryptography is an interesting fieldthat strikes the perfect balance in providing security, higher throughput, lowpower consumption, and compactness. In recent years, many compact algorithms like PRESENT, CLEFIA, SEA, TEA, LED, ZORRO, Hummingbird, and KANTAN have made the mark to be used as lightweight crypto engines. In this paper, we present the design of a new lightweight compact encryption system based on bit permutation instruction group operation (GRP), which is widely studied and extensively researched. Using the S-box of PRESENT, we have added the confusion property for GRP, because all the existing algorithms using bit permutation instructions do not have this confusion property. By comparing the existing S-boxes of compact algorithms and its cryptanalysis, a new hybrid system is proposed in this paper that provides more compact results in terms of both memory space and gate equivalents. A hybrid cryptosystem, which consists of GRP and S-box of PRESENT, is designed and implemented on a 32-bit processor. This fusion has resulted in a lightweight cipher that is the most compact implementation, till now, in terms of memory requirement. We have tested and verified this on an LPC2129 processor. Various S-boxes of recently used lightweight algorithms, such as PRESENT and CLEFIA, are designed and analyzed to create a perfect fusion that should be resistant to attacks. Using the S-box of PRESENT, it helps in further reducing the gate complexity. This hybrid model results in 2125 gate equivalents, which is better than other light variant models like DESXL, CLEFIA, and AES. Moreover, GRP properties are very helpful not only to attain the desired avalanche effect, but also as it results in a compact implementation in hardware. This paper proposes a novel approach that will have a positive impact in the field of lightweight encryption protocols.
Résumés en Français

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Résumés en Français. Am J Intellect Dev Disabil 1 September 2020; 125 (5): 408–410. doi: https://doi.org/10.1352/1944-7558-125.5.408 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search
A Different Approach for Using LZW Dictionary Codes to Increase the Text Compression Ratio

Text compression techniques are essential for better data storage.The data transmission from one location to another location can be done securely using the following technique.LZW is a dictionary based lossless text compression technique which has been used widely.In this paper we proposes a new technique to make use of dictionary even and odd codes for storing reverse strings of the existing string in the dictionary to increase the compression ratio, thus we can compress more data at a time.
PCHEC: A Private Coded Computation Scheme For Heterogeneous Edge Computing

Recently, edge computing (EC) has attracted wide attention as a novel and promising computing mode with high real-time and low-latency characteristics. However, users' privacy and the limited resources have become major concerns in the implementation of EC because edge devices are usually heterogeneous and untrustworthy. Although many related works have protected the user's privacy, they did not take the storage resource limitation of heterogeneous edge devices into consideration and their schemes may cause high communication load. In this paper, we propose PCHEC, a Private Coded computation scheme for Heterogeneous Edge Computing, to protect the user's privacy and minimize the communication load. Specifically, PCHEC first gives a storage allocation scheme to minimize the communication load in EC where the heterogeneous edge devices have different storage limits. Secondly, PCHEC utilizes linear coding to mix the target data with other information for the protection of the user's privacy. To evaluate the efficiency of PCHEC, we make theoretically analysis and conduct extensive simulations. The experiments show PCHEC effectively reduces the communication load by up to 70% compared with other schemes.
Overloaded Functions and Operators

Exploration 25 introduced the notion of overloaded functions. Exploration 31 continued the journey with overloaded operators. Since then, we’ve managed to get by with a commonsense understanding of overloading. I would be remiss if I did not delve deeper into this subject, so let’s finish the story of overloading by examining the rules of overloaded functions and operators in greater depth. (Operators and functions follow the same rules, so in this Exploration, understand that functions applies equally to functions and user-defined operators.)
Detection of Patterns in Attributed Graph Using Graph Mining

The pattern or sub-graph detection in a graph has large areas of applications such as biology, Computer Vision, CAD, Electronics, Intelligence Analysis, and Social Networks. So the patterns or sub-graphs are detected either by comparing the ID of nodes or edge of the weight with the graph’s ID of the node or the edge’s weight. Sometimes the pattern detection is essential in an attributed graph—is a graph having n-nodes and m-attributes. In this scenario, how are the patterns or sub-graphs detected? The detection of pattern or sub-graphs in the attributed graph is carried out by comparing the attribute of the given pattern or sub-graph. Here the author proposes University Graph as Social Attributed Graph. The proposed University Graph consists of 20 nodes. Here a node is considered an employee. Each employee has a proper designation. Here the author considers four numbers of designations as the attribute of the node such as “Dean,” “Associate Dean,” “Professor,” and “Associate Professor,” respectively. So according to the definition of the attributed graph, the proposed University Attributed Graph has 20 nodes, and 4 attributes. From this University Attributed Graph, the author wants to detect the different form of patterns or sub-graphs such as “Line,” “Loop,” “Star,” and “Elongated Star” which comprise three, four, and five numbers of nodes, respectively. So the author proposes an algorithm which able to detect Line Pattern with 3 and 4 numbers of nodes, Loop Pattern with 3 and 4 numbers of nodes, Star Pattern with 4 numbers of nodes, and Elongated Star Pattern with 5 numbers of nodes respectively. The proposed algorithm has the following procedures: (i) NodePairGeneration, (ii) CreatePatterns3, (iii) DisplayPatterns3, (iv) CreatePatterns4, (v) DisplayPatterns4, (vi) CreatePatterns5, (vii) DisplayPatterns5, (viii) CreatePatterns6, and (ix) DisplayPatterns6, respectively. Procedure-(i) is for node-pair creation where the actual relation between the nodes. Procedure-(ii) and Procedure-(iii) for creation and display of line and loop pattern with 3 nodes. Procedure-(iv) and Procedure-(v) for creation and display of line and loop pattern with 4 nodes. The star pattern is created and displayed by Procedure-(vi) and Procedure-(vii). Finally, the elongated star pattern is created and displayed Procedure-(viii) and Procedure-(ix), respectively. The author has created two datasets namely (i) University Attributed Graph Dataset and (ii) Node-Attribute Dataset. The first dataset comprises the total numbers of nodes and the node-pairs where the node edge is formed in the University Attributed Graph. The second dataset comprises the Node-Attribute pairs which are the actual relationship between the node and its attribute. The algorithm has been implemented in C++ and Python programming and the result has been satisfactory.
The Java Story

This chapter introduces Java by describing how it has become a mature and popular language that is used across the world for all kinds of applications. It explains why to program successfully in Java it is necessary to understand object-oriented concepts and then apply them to Java objects. The chapter outlines how Java’s rich syntax and wide-ranging APIs mean that it can be used for all kinds of programming, from writing a command line utility to building a distributed client-server system or a complex multithreaded real-time system. It describes the history of Java and how it has matured into a major programming language supporting many aspects of the current software industry. It concludes by discussing how, despite becoming to some extent a legacy language, Java will continue to evolve and be providing programmers with the tools for coding a host of applications in all kinds of contexts for many years to come. It also explains how Java’s influence is such that a knowledge of Java can be extremely useful in learning the new generations of languages that have followed it.
Digital Forensics: Repurposing Google Analytics IDs

This chapter describes a network discovery technique on the basis of websites sharing the same Google Analytics and/or AdSense IDs.
Histogram Methods

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Improving User Identification Accuracy in Facial and Voice Based Mood Analytics using Fused Feature Extraction

User identification involves a lot of complex procedures including image processing, voice processing, biometric data processing and other user specific parameters. This can be applied to various fields including but not limited to smartphone authentication, bank transactions, location based identity access and various others areas. In this work, we present a novel approach for uniquely identifying users based on their facial and voice data. Our approach uses an intelligent and adaptive combination of facial geometry and mel frequency analysis (via Mel Frequency Cepstral Co-efficient or MFCC) of user voice data, in order to generate a mood based personality profile which is almost unique for each user. Combination of these features is given to a machine learning based classifier, which has proven to produce more than 90% accuracy with a false positive rate of less than 7%. We have also compared the proposed approach with various other standard implementations and observed that our implementation produces better results than most of them under real time conditions.
A Crash Course in Python

The purpose of this book is to challenge you to build a simple robot that is expanded over time. It is intended to be difficult. It is intended to provide a hands-on experience to help you get past the most difficult part of learning robotics: being intimidated by the technology. I’m going to teach you some of the basics of robotics the same way that I learned how to swim—by being thrown into the deep end while someone more experienced watches over to make sure that you don’t drown.
A Strong Standing Management Apparatus in the Confederate Threat

In the Facilities as a Service (IaaS) elegant of cloud pc, device assets square degree on hand for apartment rate. in spite of the fact that it gives a cost practical desires to on-line machine requirements, low recollect at the leased system sources keeps human beings from exploitation it. to reduce the cost, device assets square diploma shared, i.e., there exists multi-occupancy. for the reason that correspondence systems and furthermore one of a kind machine property rectangular approach shared, it creates fitness and safety simply as protection troubles. A patron in all likelihood may not build up a legitimate co-occupant for the motive that customers square hobby mystery. The client is based upon at the Cloud provider (CP) to assign reliable co-inhabitants. but, it's in the CP's pace of intrigue that it receives most use of its assets. in this way, it lets in most co-occupancy despite the acts of clients. at some point of this paper, we often will in standard prescribe a stable call the executives system that dreams the cycle in a genuinely combine cloud to cut up within the middle of practical and furthermore dangerous customers just as allot assets in such a few way that they're doing no longer proportion assets. we frequently will in widespread show the rightness simply because the adequacy of the decided name the board framework exploitation regular and theoretical exam.
Design of Cooling and Air Flow System Using NDLC Method Based on TIA-942 Standards in Data Center CV Media Smart Semarang

CV Media Smart is a company that involved in the procurement of IT tools in schools and offices. With wide range coverage of schools and companies, CV Media Smart want to add more business process, therefore data center is needed to support existing and added later business process. The focus of this research is on cooling system and air flow. To support this research, NDLC (Network Development Life Cycle) is used as research method. NDLC is a method that depend on development process, like design of business process and infrastructure design. The reason why this research is using NDLC method is because NDLC is method that depend on development process. The standard that used in this research is TIA-942. Result of this research is a design of data center that already meet TIA-942 standard tier 1.
Conducting Digital Product Usability Tests with Children who have Atypical Development

When creating digital products, it is essential to validate design decisions through user testing. Ensuring a digital product meets targeted user groups and personas&#039; needs, all sorts of design decisions need to be carefully evaluated and adjusted, including informational architecture, navigation, selections, control patterns, feedback, colors, typography, iconography, and many more. Every testing session is unique and needs to be personalized according to the testing persona. When working with special needs persons, atypical development, or visual impairments, special care and preparation are required. These circumstances of user testing are even more challenging when the targeted audience is children with said disabilities. In preparation for testing, it is essential to understand the type of disability a child has and inform their legal guardian or medical caretaker. Considering all these things, conducting user testing can still prove challenging because of a child&#039;s unpredictable behavior. They might seem interested; they might lose focus or generally not be in the mood. With research skills, clear set goals, and preparation, a healthy dose of empathy and human understanding must gather valuable testing session’s insights. Insights that will help inform further design decisions.
Secure Blockchain Voting Technology

The n paper-ballot voting system and Electronic voting machines (EVM’s) has provided long term trust among the various places in the world for the purpose of voting. But each of the systems have their own flaw. Introduction of Blockchain for the purpose of Voting can be a remarkable change in the voting system which will be trusted globally. This Paper discusses about casting vote on a blockchain which improves the efficiency of the voting process and also the security of the vote which has been cast by the citizen.
PPE silicone and fluoroelastomer materials are approved by WRAS

Precision Polymer Engineering Ltd (PPE) of Blackburn, UK, has received Water Regulations Advisory Scheme (WRAS) approvals for two of its material grades that already comply with regulations set by the US Food and Drug Administration.
Pythonic Thinking

The thing that sets Python apart from other languages is that it is a simple language with a lot of depth. Because it’s simple, it’s much more important to write code cautiously, especially in a big project, because it’s easy for the code to become complex and bloated. Python has a philosophy called the Zen of Python, which emphasizes simplicity over complexity.
Accessing and Comparing Word Frequency Data

In this chapter, we derive and compare word frequency data. We learn about vector recycling, and the exercises invite you to compare the frequencies of several words in Melville’s Moby Dick to the same words in Jane Austen’s Sense and Sensibility.
Retrieval Effectiveness of Google on Reverse Image Search

This study investigates the reverse image search performance of Google, in terms of Average Precisions (APs) and Average Normalized Recalls (ANRs) at various cut-off points, on finding out similar images by using fresh Image Queries (IQs) from the five categories &#x201C;Fashion,&#x201D; &#x201C;Computer,&#x201D; &#x201C;Home,&#x201D; &#x201C;Sports,&#x201D; and &#x201C;Toys.&#x201D; The aim is to have an insight about retrieval effectiveness of Google on reverse image search and then motivate researchers and inform users. Five fresh IQs with different main concepts were created for each of the five categories. These 25 IQs were run on the search engine, and for each, the first 100 images retrieved were evaluated with binary relevance judgment. At the cut-off points 20, 40, 60, 80, and 100, both APs and ANRs were calculated for each category and for all 25 IQs. The AP range is from 41.60% (Toys&#x2014;cut-off point 100) to 71% (Home&#x2014;cut-off point 20). The ANR range is from 47.21% (Toys&#x2014;cut-off point 20) to 71.31% (Computer&#x2014;cut-off point 100). If the categories are ignored; when more images were evaluated, the performance of displaying relevant images in higher ranks increased, whereas the performance of retrieving relevant images decreased. It seems that the information retrieval effectiveness of Google on reverse image search needs to be improved.