Reviewerly/exHarmony huggingface dataset:
Productivity Metric Estimation: Comprehensive Examine of Efficiency, Effectiveness and Value Based Metrics

The successful software project estimation is critically dependent upon measurement of productivity. The overall goal of productivity metric is to improve the ability and performance of information system evaluation as well as maintenance, moreover determine the performance of the information technology (IT) performance in business applications. The activities corresponding to productivity metrics vary at distinct management levels. The activities used within project management leads to dynamic framework that could be opted in changing or dynamic environments. At the project management level, productivities activities concentrates on effectiveness. For instance, during estimation of effort required to reproduce a system, assumption must be manufacture regarding the ability that could lead to successful development of software project and this is fetched from past projects. This paper focuses on identifying the productivity metrics that are essential and appropriate for project management process.
Pengembangan Aplikasi Pencarian Wisata Kuliner Kota Bogor Berbasis Range Harga Dan Metode Lbs (Location Base Service) Pada Android

&lt;p&gt;&lt;em&gt;People interested in culinary are increase in line with application development on smartphone. Recently, developers has developed new application to find culinary places based on prices quickly and easily. This study aims to develop smartphone application to find culinary places with suitable budget for consumers. Application development method used in waterfall that consists of planning, analysis, implementation, and testing. The conclusion of this study is that the application can help consumers to find culinary places with suitable budget &lt;/em&gt;&lt;/p&gt;
High-speed Integration of Kinect V2 Data for Identification of Hand Gesture in Real time Movements

Hand gesture recognition is extremely critical for human-PC connection. This manuscript presents a narrative constant strategy for human-hand gesture recognition. Here a framework for the discovery of quick gesture movement by utilizing a direct indicator of hand developments utilizing information combination technique. In our system, the hand area is removed from the foundation with the foundation subtraction strategy. At long last, the framework has been approved by methods for the Kinect v2 application actualized. The time requirement is recognized and the recognition is quick contrasted with other ongoing minutes. The timing analysis is compared , and the average time using data fusion method [1] is 63ms. By using fast integrating of data the average time is 45ms. The time taken for recognition of hand gesture is been improved. The experimental results are performed using Matlab tool.
Data Selection Strategy from Database for increasing availability in Cloud Hosted Database

Cloud is service-oriented computing emerged as a cost-effective paradigm for distributed applications because of its unique features. Distributed Datacenters of the cloud service provider allowed researchers to do their research in Cloud environment with the factors like increasing availability, reducing response time, Fault tolerance, performance etc. This paper aims at Problem of data selection from database for partitioning, Partitioning the databases relations, placing the partition in different data centers of the cloud with respect to Cloud Hosted Database. Scope of this work will focus on read intensive data operations/queries. In this paper, we focused on data selection and data partitioning technique so as to reduce overall network latency on cloud hosted database. General log is for finding the frequently accessed rows from the database. Experiment is carried on Amazon RDS.
Automatic Question Generation using Sequence to Sequence RNN Model

Automatic Question Generation (AQG) has recently received growing focus in the processing of natural language (NLP). This attempts to create questions from a text paragraph, where certain sub-spans of the passage in question will answer the questions produced.. Traditional methods predominantly use rigid heuristic rules to turn a sentence into related questions. In this research, we suggest using the neural encoder-decoder model to produce substantive and complex questions from the sentences of natural language. We apply a attention-based sequence to sequence learning paradigm for the task and analyze the impact of encoding sentence vs. knowledge at paragraph level. Information retrieval and NLP are the core components of AQG. It incorporates the application of production rules; recurrent neural network (RNN) based encoder-decoder sequence to sequence (seq2seq) models, and other intelligent techniques. RNN is used because of its long short term memory power (LSTM).The proposed system focus on generating factual WH type questions.
A Classified Medical Infertility Dataset using High Utility Item Set Mining

The most modern technological innovations led towards generating lots of data, which is either redundant or of imperative use. To mine the meaningful information from this huge repository, Data mining techniques will be of vital importance. This article aims at mining the useful patterns from this enormous repository and presents some possible solutions while treating the patients suffering with various problems of infertility. A Classified High utility item set mining with Naïve Bayes classification (CHUIM-NB) is proposed for classifying the data, which will be of productive usage to the Medical Practitioners during the treatment of the patients. The proposed model has three stages: the stage1 aims at generating the training data, the second stage aims at proposing a two phase algorithm for producing high utility item set and also the rules for association mining (CHUIM) and in the third stage, the Naives classification model (CHUIM-NB) is considered for the effective diagnoisis/ treatment.
Virtual Reality Language Lab of Second Language Learning Based on J Bruner’s Discovery Learning and Self-Efficacy Theory—Literature Review and Solution Improvement

Language learning has gradually involved innovative technology such as the use of 3D virtual worlds, which can enhance learners’ immersion through improved engagement with the help of their motivational components. Immersion in the target language environment for example English, Spanish, French and German environment provides maximum exposure to the communicative use, offering the opportunity to learners’ active creativity. Since real travel is expensive and impractical, virtual travel in the virtual reality language lab provides them a brand new opportunity. Adopting the literature research method, this paper aims to figure out the optimum time duration and time frequency for most language learners to spend in the virtual world. Based on Discovery Learning and Self-efficacy Theory, we tend to focus on the behaviors of the learner in the virtual world, such as how they express themselves in second language and acquire daily expressions with the help of Unity3D to design and develop 3D virtual worlds and the EEG (electroencephalogram) equipment to reflect changes in the neural representation of the task environment. In order to find a possible relationship between communicative activities and the learning theories of Discovery Learning and Self-efficacy Theory, correlative analysis and principal component analysis were performed. According to this research, we can effectively limit the time and frequency of the immersion in the second language environment and promote the efficiency.
JPR volume 58 issue 1 Cover and Back matter

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Data Security Measures using Hybrid Encryption Technique

Data security is a process of enhancing the data privacy measures to filebase, database, websites while preventing unauthorized access to the datasets and data-streams. Encryption is the key data security technique that prevents the access of digital data from unauthorized person or hackers. This research work proposes a novel approach using data transformation and encapsulation techniques namely Hadamard Transform along with DNA Cryptography and Amino Acid for enhancing data security.
Optimal Management of the Multimedia Application

The need for multimedia applications has increased over the years. Due to this issue, image and video compression becoming an essential problem in reducing time and data storage. Fractal Image Compression (FIC) is a compression technique which results in loss, and we can have large amounts of compression. This scheme works by classifying an image into blocks and uses Contractive Mapping. Some of FICs advantages can be expressed as follows: comparing with other standard compression techniques, it has a good interchange between PNSR and compression ratio and it zooms the image without reducing the quality due to its resolution independent nature. The main FICs drawback, is its complexity in encoding and lack of speed.
A Network Forensic Framework for Port Scan Attack based on Efficient Packet Capturing

In the last two decades the networks become larger in scale, more complex in structure and more diversified in traffic. Which generate huge amount of network packets such as TCP, UDP and HTTP etc. Log files are repository for captured packets and play a vital role in investigation. However, a significant and obvious limitation of current packet logging is that, data storage volume increases rapidly depending on factors such as network bandwidth and the number of points in the network that need to be tapped. Forensic investigator needs to back up these recorded data to free up recording media and to preserve the data for future analysis. The objective of the proposed work is to build a network forensics framework that precisely scrutinizes only the relevant packets .In this work, a network forensic framework is developed subjected to port scanning attack to mitigate evidence gathering challenges faced by forensic investigator. It captures and processes only fine-grained evidences present in the network traffic stream. Moreover, in the captured relevant log, attack specific discovery is carried out to mine the exact packets utilized to execute the network attack. Hypotheses being developed to validate each machine against attack specific criteria’s. Only those machine who full fill the criteria will be scrutinizes for further analysis. To test and validate the effectiveness of the proposed framework two scenario have been developed, It is observed that developed system preciously securitizes the attack patterns and improved decrement in the log size is observed for both scenario developed that is about 93.12% and 95.65% respectively. It is also observed that only 6.09% and 1.93% of total traffic being scrutinized for NULL, FIN and XMAS attack in scenario 1 and 2 respectively. Similarly 19.88% and 13.42% packets of total packets are scrutinized for TCP Connect and SYN (Half open) scanning variant in scenario 1 and 2 respectively.
The portrait of the student of University

Discussed are positions in international ratings of quality of education of “Big seven” countries and the Russian Federation, and also defined are principal conditions of raising creativity of 15th years Russian school persons and students of universities, incl. on the base of results of sociological research.
Evaluasi Pemanfaatan Fitur Perpanjangan Mandiri SLiMS Menggunakan Metode Debugging

Introduction. The Self-service Extension feature is one of the innovations developed by SLiMS community since 2015. Its function is to facilitate users in extending the loan period of borrowed books by themselves. Purpose and Method. This study aims to evaluate the performance of the Self-service Extension feature using debugging(error tracking) method by connecting symptoms and causes of errors. Results and Discussion. The results found several weaknesses.This module cannot run properly if the number of loan extensions is set more than once, and information on the amount of fines displayed does not count Sundays as holidays, so the penalty rate displayed exceeds the amount that should be paid. From this study it can be concludedthat the use of the debugging method is quite effective in tracking errors (bugs) on modules with simple program code, such as the Self-service Extension feature. After repairs, the feature can run as it should according to the rules set by its parent application, SLiMS. Its function can be maximized in helping facilitate library users to extend the period of borrowed books online, as well as to see information on the amount of fines to be paid.
A Stylistic Analysis of Imperative Mood on Hannah Baker’s Monologue - 13 Reasons Why (Season 1)

The appearance of a sentence that is continuously uttered by the speaker becomes a style or characteristic of the speaker. This can be seen in a series entitled 13 Reasons Why in which the main character, Hannah Baker, uttered many imperative moods. This research focuses on how the use of one form of sentences, namely imperative or what is called as imperative mood, can give a stylistic effect that appears on the utterances of Hannah Baker in a monologue. This research uses a qualitative method that aims 1) to find out the forms of the imperative mood; and 2) to find out the functions of the form of the imperative mood using the theory of Aikhenvald (2010). By observing and transcribing, the data can be found, which then can be identified to find out the imperative sentence, what form and function of it. Through these things, a conclusion can be drawn about how the character of Hannah Baker's is seen from the imperative mood that she utters and what meaning she wants to convey through the imperative mood. This research uses purposive sampling in collecting the data. Based on the results of the study, 54 imperatives mood were found in the monologue. The findings reveal two forms of imperatives namely canonical imperative as many as 77.78% and non-canonical imperative as many as 22.22%. The functions of imperatives found include: 1. Orders, commands, demands (only commands), 2. Requests, pleas, entreaties, 3. Advice, recommendations, warnings, 4. Instructions and expository directives, 5. Invitations, 6. Permission, 7. Acceptance, 8. Incredulous rejection, and 9. Self-deliberation. From the results obtained, it can be seen that the most dominant function is instruction, which is 16.67%. From this result, it can be known that Hannah Baker wanted to show each incident in detail that caused her suicide through her monologue in 13 Reasons Why (Season 1).
Mosquito ZeroTM

Mosquito Zero is an application that is designed to demonstrate the efficiency and effectiveness of information, education and communication between public authorities and citizens regarding Aedes aegypti, the diseases this mosquito transmits and the health impacts, providing citizens with a smooth and accessible channel of communication about the mosquito and arboviruses through the application and virtual robots.
NONLINEAR DYNAMIC MOTIVATION-ORIENTED TAXONOMY OF L2 STRATEGIES BASED ON COMPLEX DYNAMICS SYSTEMS THEORY

The need for a revisited framework of strategies in keeping with the nonlinear dynamic nature of motivational factors in L2 teaching led to the introduction of a taxonomy of nonlinear dynamic motivation-based strategies (NDMSs). This psycho-socio-cultural template suggests discovering dynamic motivational factors at individual level and integrating them into multiple parallel groups within a learner group instead of creating them which is a traditionally established function of motivational strategies to impose superficial cohesion on a learner group without catering for chaotic, emergent and dynamic individual motivational factors. Given the heterogeneity, dynamicity, and nonlinearity of the motivational factors at individual level, the first implication of the study is that NDMSs have the potential to activate identified motivational factors toward an adaptive and autonomous L2 motivation state regardless of their homogeneity or heterogeneity. Secondly, NDMSs have the potential to enable teachers to recruit the learning energy (i.e. motivation) from every member of the group via a dynamic and nonlinear set of motivational strategies instead of imposing a preset set of motivational strategies to all members of the group to elicit/facilitate/encourage equal performance from a motivationally heterogeneous learner group under the pretext of generating a cohesive learner group. Keywords: L2 motivation, nonlinear dynamic motivation-based strategies (NDMSs), complex dynamics systems theory (CDST)
A Novel Technique for Copy Move Forgery Detection using Grey Level Co-occurrence Matrix

In this paper we have studied the GLCM approach as an improvement over SWT-DCT method for feature extraction for CMFD. We have carefully studied the previously used methods and also studied the SWT-DCT method for improvement in features. We have proposed a method for the use of GLCM instead of SWT-DCT method for feature extraction which will improve the results of CMFD method used in the base work framework.
Big Data&amp;Open Data in journalism: role, meaning, trends

New digital data formats — Big &amp; Open Data — are transforming the modern model of professional social communication and changing the parameters of communication. The emergence of new formats of digital information, including big data, provides new ways to search, process, analyze, present and visualize it in journalism. These changes should be reflected in the texts of journalistic materials. However, there is reason to believe that the impact of large and open data on the structure of journalistic materials in the leading domestic media remains minimal. Data journalism is still in its infancy, being studied based on observation and interviewing techniques. Comprehensive studies of data sources of data journalism publications are still lacking. In leading publications, the number of materials based on open data and published on a regular basis as separate projects or in specialized sections is growing. However, despite its prevalence, this phenomenon is still controversial both among practicing journalists and academics. The practices of data journalism, which are not sufficiently systematized, are not comprehensively reflected in the scientific literature. Existing research in this area is at the intersection of different scientific fields and concepts and is interdisciplinary. However, many media outlets are already starting to work with numbers and databases, literally finding stories in them for publication. It can be stated that today a community of people is emerging who call themselves data journalists, which is significantly different from the community of experts in the field of computer journalism. This new community has more innovative ways of providing data, storytelling, and final reporting, combining the deeply analytical and critical approaches of the computer and visual journalism community.
Proactive Fault Tolerance Policy for Virtual Machine Management in Private Cloud Environment

Cloud computing being a new delivery model has many research challenges. It opens the door to great amount of innovative methods and practices. Many researchers have come-up with novel and efficient fault tolerant solutions for the cloud. With the rapid advancement in internet technology, usage of smart devices and social networking are giving rise to tremendous amount of data and demands resources like never before. Cloud computing delivery model provides solution to the need of the day. The recent advancement in IoT, Edge computing etc, has expanded the scope of visualizing cloud computing with a different perspective. There is a need for re-provisioning the existing components of the cloud model. Most of the research on fault tolerant algorithms, mechanisms and techniques are focused on datacenters. In this paper we propose fault detection and prevention policies for VM creation lifecycle derived from cloud computing patterns.
Marketing Models of Assortment Planning–Applicable to Serials?

SUMMARY. Marketing models designed to optimize retail product assortments can inform the evaluation of journal collections in the noncommercial library setting. This tactical session presented marketing research in three key areas: consumer perceptions of reduced choice, efficient allocation of limited shelf space, and formulas to find the most efficient variety of products that satisfy consumers. Steve Black invited participants to apply the marketing theories to their practical experience within the library environment. Many correspondences and some divergences between retail consumers and library users were noted. Chiefly, undergraduate and graduate library user groups, like retail consumers, behave somewhat predictably when confronted with large or small assortments of journals. Also, the presence or absence of a favorite journal, like a favorite product, is significant to users/consumers. Library users differ from consumers in that an acceptable substitute is not always readily available. The effects of the physical arrangement of journal collections, 328such as interfiling and type of classification, are noteworthy. The importance of developing unique items within a library collection was emphasized. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: &lt;docdelivery@haworthpress.com&gt; Website: &lt;https://www.HaworthPress.com&gt;]
Testing of Image Steganography with use of LSB and DCT Techniques

In this growing internet world, secret data communication is increasing day by day. There are various methods to communicate secretly. Steganography is one of those techniques in which data is concealed within cover data such that it cannot get detected. Steganography is usually used today on pcs where digital data is the high-speed distribution channels for carriers and networks. Steganography is the skill of understanding of unnoticeable activity at intervals. Steganalysis is the science of concealed data detection. Steganography of data which is of any form like images, audio, video or text information is done by various techniques. Image steganography is done by various technique. Least Significant Bit (LSB) with XORing and Discrete Cosine Transform (DCT) are used to test the image steganography. Images are converted to grey scale to get better accuracy. Results are tested with mean square error (MSE) and peak signal-to-noise ratio (PSNR) values.
Extended COCOMO: robust and interpretable neuro-fuzzy modelling

Prediction of software development efforts is one of the crucial activities in software project management. Still, search for the perfect model for software cost estimation has become most difficult task of the organisations dealing in software development. This paper presents the extended version of COCOMO, which is done with the help of two very popular methods, i.e., artificial neural networks (ANN) and fuzzy logic. Firstly, the expert judgement about model is used for validation, and overpowers the common software engineering 'black box' problem that arises widely in ANN-based solutions. Moreover, we choose the best combination of one of the three membership functions for continuous-rating values, which reduce the variance while estimating the cost of similar projects. The validation, using 93 NASA projects dataset, shows that the model significantly improves the estimation accuracy in terms of mean magnitude of relative error (MMRE) by 10.104% relative to other known estimation models.