Reviewerly/exHarmony huggingface dataset:
Assessment of Hydro-potential by using Remote Sensing &amp; GIS Technology

Now a days as the power or electricity is playing very important role in the human life, its create a very ease life for the human, the non-renewable energy such as coal energy, petroleum, natural gas depleting very fast, so we focus on renewable energy sources such as the solar energy, wind energy, thermal energy, hydropower plants etc. The objective of this study to discuss various methodology used for generating the power, hydropower plant is our focus area for the generating electricity and the site selection is done by using GIS (Geographic information system), hydropower plant is one of the most popular pant for the hilly region, it is very less polluting source which generating the energy in efficient manner. The GIS play a crucial role for the hydropower plant site selections; here in this paper we provide comparative study for the review various GIS based applications.
Adapting Green Technology on the Minimization of Carbon Emission in a Higher Education Institution

The study aims to evaluate the contributors to Carbon Dioxide emission considering the operational activities in the Higher Education Institution and use this as a basis for adapting green technology. This research utilized the mixed method to determine the biological and operational contributors, corresponding scope, kilograms of Carbon Dioxide emitted, and awareness of students, faculty members, and non-teaching personnel about the policies on contributors of Carbon Dioxide. Results showed that human respiration, electricity consumption, liquefied petroleum gas consumption in canteen, restaurant, food stalls and laboratories, University-owned vehicles gas combustion, four-wheel vehicle and motorcycles entering and exiting the campus gas combustion, materials and supplies consumption emitted Carbon Dioxide corresponding to 11,672,742.0792; 1,873,456.92352; 342,224.464, 43,063.8; 24,326.155; and 14,458.80155 kilograms with a total of 13,970,272.234 kilograms annually. The perceptions of students, faculty members, and non-teaching personnel about the Carbon Dioxide contributors and policies in the University campus were summarized as follows: The respondents are aware and involve in the Policy on Clean and Green of the University which is being manifested through recycling of plastic, papers and other biodegradable and non-biodegradable wastes; submission or forwarding of reports or memoranda through online; use of water tumbler and food containers which respond to the policy of No Plastics; segregation of solid wastes; planting native and fruit-bearing trees; saving measures were posted in classrooms and laboratories; water conservation; wider dissemination through discussion of topics about climate change, environmental laws and principles, waste management, air and water acts, and green technology in classes; Garbage in Garbage out policy; imbibing discipline in terms of cleanliness and orderliness in the campus; and using solar energy in lighting electric posts.
Performance Improvement of Hand Gesture Recognition By using Sparse Coding With Kinect V2 Sensors

This paper presents an important technique with improvement property for image identification intention. Here the important technique which is sparse coding representation acts as a major ROLE in achiveving One-short learning and real recognition of actions[1]. The implementation method based on mainly 3-D Histogram of prospect flow with Global Histograms of orientated Gradient .The major and most important of this method is to use imprison on major level regions from the given data sets . With this data then suggest a instantaneous to get video segmentation and video gratitude of hand gesture action by using linear SVMs.This paper mainly highlights the major role of sparse coding technique to stand for 3D proceedings [2] .From this paper we obtain very good results in an domestic dataset captured by Kinect V2 sensors together with hand gesture proceedings and complex hand gesture actions differing by small details.
Report on the Second International Workshop on Narrative Extraction from Texts (Text2Story 2019)

The Second International Workshop on Narrative Extraction from Texts (Text2Story'19 [http://text2story19.inesctec.pt/]) was held on the 14th of April 2019, in conjunction with the 41 st European Conference on Information Retrieval (ECIR 2019) in Cologne, Germany. The workshop provided a platform for researchers in IR, NLP, and design and visualization to come together and share the recent advances in extraction and formal representation of narratives. The workshop consisted of two invited talks, ten research paper presentations, and a poster and demo session. The proceedings of the workshop are available online at http://ceur-ws.org/Vol-2342/
Evaluating core competencies in optimising performance of manufacturing industries

Organisations have to emphasis on core competency in order to stay competitive in market. Core competency is quite similar for all manufacturing organisations. Core competency helps the organisation to improve their performance parameter. As per literature, every organisation must spend on improving their core competency in order to gain an extra edge in the market. Core competency can be technical or management related. These core competencies can lead to an improved product, which may be a unique one. In the end every organisation should find their unique products that will help them to stay competitive in the market. Companies are involved in a continuous process of change in order to renew capabilities and achieve a competitive advantage in a hyper competitive setting. The key is to own and nurture the resources and competencies that make up the essence of the business.
ANÁLISE DAS TECNOLOGIAS DE EDUCAÇÃO APLICADA NA SAÚDE

Objective: Analyze scientific content in the face of applied education technologies in health.Method: This is a integrative literature review study that consists of the following steps: Location and selection of studies; critical evaluation of studies; data collect; analysis and presentation of data; and interpretation of results.It used the scientific publications available in the VHL, PubMed and Scielo databases.Results: After analysis, the final sample was 19 articles and there was a great importance of educational technologies to promote health, including: games, videos, applications, courses, websites, mobile devices and booklets.Conclusion: Finally, it was evidenced that such technologies are essential for health education, since educating is not an easy task and requires more didactic means for its elaboration.
The impact of the difficulty level of compromised common items on IRT scaling and equating under the common item equating design

The common item equating design requires two forms of a test which have a set of items in common in order to control for differences in examinee ability. The common set is subject to compromise when it is used repeatedly, which most likely becomes a serious threat to test fairness. If cheating occurs on common items, the equating process produces inaccurate results which might vary as a result of common item difficulty. This simulation study was conducted to evaluate the impact of the difficulty level of compromised common items on the equating process. The recovery of scaling coefficients and equated scores was assessed using bias and RMSE under various cheating conditions. The results indicated that cheating on higher-difficulty common items produced the most overestimation in the scaling coefficients; which, in turn, caused the most inflation in equating true scores for all test takers, whether they engage in cheating or not.
The Impact of Digital Learning on Hygiene Awareness of Children with Down Syndrome

Recent years have witnessed major advances in digital learning to support children diagnosed with Down syndrome.Since DS children suffer from a deficiency in learning and cognitive development problems and social functions.Variety of hygienic skills have compact their daily lives, with the goal of enhancing their hygiene awareness and hygienic skills to practice.Hence, this study was conducted to investigate the impact of digital learning to reinforce hygiene awareness for children with Down syndrome.The participants of the present study were 6 children with DS.The results have discussed the findings.The study targeted on the usability of DL.The sample enclosed DS children who are minimally effective communicators who need activities that are highly structured and sequenced information.The results showed an encouraging impact of the DL in supporting DS children to reinforce hygiene awareness.
Augmented Fuzzing with Promotion on Numerical Dependence

Coverage-guided fuzzing is an effective technique to find software bugs, it is skilled at eliminating the execution on the repeated paths, thus the fuzzing performance is improved.However, its code coverage-centric design is still insufficient in bug detection.On the one hand, the coverage-based schedule tries its best to reduce the execution on the explored paths even if there are some undetected bugs inside.On the other hand, it mutates the input randomly, which makes it inefficient to generate target testcases.As a result, it may miss some subtle bugs despite it has already explored the vulnerable codes.In this paper, we present a prototype, named ADA, to augment bug detection on the executed paths via a promotion on the numerical dependence of triggering the bug.The numerical dependence means some special numerical conditions that need satisfying to trigger the bug.In a nutshell, our tool allows an intended number of executions on the explored paths, and utilizes a novel approximation search algorithm, to produce the testcases that can satisfy the numerical dependence of triggering the bug and crash the program.Moreover, we leverage a critical field identification method to adjust the mutation, which can help the engine to quickly produce the testcases satisfying the numerical dependence.We implement ADA based on AFL and radare2, and evaluate its performance on some benchmarks.The results demonstrate that ADA outperforms some other state-of-the-art coverage-guided fuzzers in discovering the bugs on the executed paths.It is the proof that our approach is effective.Besides, the experimental results also indicate that the introduced overhead by our approach is within an acceptable scope.
Performance Evaluation of Various Block Chain Platforms

Blockchain is a decentralized data processing and sharing platform that enables multiple domains that do not trust each other to cooperate, coordinate and collaborate in a rational decision making process. As internet made us all communicate with each other in just one click, Blockchain can do same for business environment. Blockchain for business environment provides a way to execute multiple transactions with multi-users in a much secured manner. For doing this a secure blockchain platform needs to be set up for various kinds of businesses. This paper presents a comparative analysis of thirty-four various blockchain platforms suitable for different applications. The objective of the paper is to provide an in-depth comparison of the various blockchain platforms belonging to different blockchain generations to help developers select a suitable blockchain platform for their application. Finally we conclude with our findings as well as a note on future directions for expanding the research blockchain technology platforms
BiasHeal: On-the-Fly Black-Box Healing of Bias in Sentiment Analysis Systems

The International Conference on Software Maintenance and Evolution is the premier international forum for researchers and practitioners from academia, industry, and government to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolution.
Therole of Metasomatic Breeds in Ore Bodies Forecasting to Depth (Beshkuduk)

Hydrothermal mineralization in the deposit has a wide development. It occurs itself in three stages: pre-ore, ore and post-ore. In the pre-ore phase, quartz-albite-sericite-chlorite metasomatitesoccurred. In the ore stage, two stages are distinguished: the earlier quartz-pyrite-arsenopyrite stage with gold and quartz - the bleachers association. The minerals of these stages are confined to tectonic troublesome zones, zones of vein silicification, quartz and shale breccias. In the placement of products of hydrothermal metasomatism, a certain horizontal zonality is detected. There is a consistent sequential change of zones with distance from the quartz veins and faults.
An improved reversible data hiding scheme based on pixel permutation

Low payload capacity is a flaw in pixel exchange-based reversible data hiding schemes. In order to improve it, this paper proposes a triangular pixel pair structure, which requires fewer pixels than a traditional 2 × 2 pixel block. At the same time, the corresponding embedding conditions are also proposed to screen out those pixel pairs that may reduce image visual quality seriously after data embedding. Embeddable pixel pair is binarised by its feature. And, Huffman coding method is used to create free space for secret data while ensuring reversibility. Eventually, data is embedded into a cover image by switching embeddable pixel pair features. The experimental results show that the greyscale histogram of the cover image is never modified by the proposed scheme. Consequently, secret data cannot be detected by the statistical steganalysis based on the greyscale histogram. Both payload capacity and imperceptibility get enhanced obviously, and PSNR is at the same level as the schemes that do not provide robustness of the greyscale histogram.
The Determinants of Information Technology Towards Innovation Performance in Iraqi SMEs

Information technology has inevitably perceived as a core source for the competitive advantages of SMEs. It facilitates innovation capabilities through transforming the needed knowledge that is important for new product, services, market, organizational and processes development. Yet, the literature on the application of IT on innovation abilities still suffering to empirical research, especially from developing countries. Therefore, this article aims to examine the role of IT infrastructure on innovation capabilities in Iraqi SMEs. The survey was used to gather data and regression analysis carried to analysis the data. The finding of this paper emphasizes that IT infrastructure (IT connectivity, modularity and personal) has positive effect on innovation performance in Iraqi SMEs.
Home Depot Foundation boosts commitment to veteran initiatives

The Home Depot Foundation has announced an increased commitment of a half billion dollars to veteran causes by 2025. The expanded commitment to veterans comes as company volunteers, known as Team Depot, completed more than 100,000 volunteer hours during the foundation's seven‐week Celebration of Service campaign.
Visualizing GitHub Issues

The ninth IEEE Working Conference on Software Visualization (VISSOFT 2021) builds upon the success of the previous eight editions of VISSOFT, which in turn followed after six editions of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT) and five editions of the ACM Sympo0sium on Software Visualization (SOFTVIS). In 2021, VISSOFT will take place and be co-located with ICSME.
SENTIMENT ANALYSIS USING SUPPORT VECTOR MACHINE BASED ON FEATURE SELECTION AND SEMANTIC ANALYSIS

Social media is a popular network through which user can share their reviews about various topics, news, products etc. People use internet to access or update reviews so it is necessary to express opinion. Sentiment analysis is to classify these reviews based on its opinion as either positive or negative category. First we have preprocessed the dataset to convert unstructured reviews into structured form. Then we have used lexicon based approach to convert structured review into numerical score value. In lexicon based approach we have preprocessed dataset using feature selection and semantic analysis. Stop word removal, stemming, POS tagging and calculating sentiment score with help of SentiWordNet dictionary have been done in preprocessing part. Then we have applied classification algorithm to classify opinion as either positive or negative. Support vector machine algorithm is used to classify reviews where RBF kernel SVM is modified by its hyper parameters which are soft margin constant C , Gamma γ. So optimized SVM gives good result than SVM and naïve bayes. At last we have compared performance of all classifier with respect to accuracy.
Implementation of VLSI Architecture for Montgomery Modular Multiplier

The paper proposes a Montgomery Modular Multiplier (MMM) using a simple and efficient Montgomery multiplication algorithm. Here a modification in the form of using hybrid full adders in the Carry Save adder is proposed. The hybrid full adder is designed using a conventional Complementary Metal Oxide Semiconductor and transmission gate logic. There is about 54% and 55% reduction of area (no. of components) in Radix 2 MMM and Semi-Carry-Save (SCS) based MMM with hybrid full adders. There is significant reduction in the power dissipation of 52% for Radix 2 MMM and 46% of SCS based MMM when hybrid adders are used instead of C-CMOS Full-Adders. The delay is also reduced by 47% in SCS based MMM as compared to that of Radix 2 MMM. The software used are Xilinx ISE 14.2 and Mentor Graphics Pyxis Schematic in 180-nm technology.
Detecting Malicious Facebook Applications using LSTM Algorithm

With twenty million introduces a day [1], outsider applications area unit a big purpose behind the acknowledgment and addictiveness of Facebook. Tragically, programmers have finished the aptitude of exploitation applications for spreading malware and spam. the problem is as of currently important, as we discover that a minimum of thirteen you look after applications in our dataset sq. estimates malignant. Up hitherto, the examination network has fixated on police examination vindictive posts and battles. we tend to tend to point out the issue: Given a Facebook application, can we tend to tend to affirm if it's vindictive? Our key commitment is in making LSTM—Facebook's Rigorous Application Evaluator—ostensibly the essential instrument fixated on police examination malevolent applications on Facebook. to make LSTM, we tend to tend to utilize info assembled by perceptive the posting conduct of 111K Facebook applications seen crosswise over 2.2 million purchasers on Facebook. to start with, we tend to tend to come to a decision plenty of decisions that encourage North yankee nation to acknowledge harmful applications from kind ones. for instance, we discover that vindictive applications normally share names with elective applications, which they for the foremost half demand less authorizations than amiable applications. Second, contributory these recognizing decisions, we tend to show that LSTM can find malignant applications with ninety nine .5% exactness, with no imitative positives and a high obvious positive rate (95.9%). At long last, we tend to tend to research arrange of harmful Facebook applications and distinguish parts that these applications use to unfold. Curiously, we discover that few applications get together and bolster every other; in our dataset, we discover 1584 applications endorsing the being engendering of 3723 choice applications through their posts. Long haul, we tend to tend to examine LSTM as a stage toward creating Associate in Nursing freelance working dog for application appraisal and positioning, during this manner on caution Facebook purchasers before putting in applications.
An Efficient Imputation Strategy Based on Adaptive Filter for Large Missing Value Datasets

A dataset is the heart of any data science algorithm. As the model accuracy build for any data science algorithm largely relies on quality of the datasets, data preparation plays an inevitable role. Most of the real-world data is found to be affected by missing values, which makes the dataset incomplete. This is certainly unavoidable as these are more prone to environmental problems, network issues, human error, etc. The easiest procedure is to discard the missing value that is not an optimized process, as even a small amount of missing data can have more information content that cannot be discarded. To improve the quality and reliability of the results obtained, missing values are generally imputated. In this chapter, a novel missing value imputation strategy based on adaptive filter is proposed. The conventional prediction algorithms based on Least Mean Square (LMS) suffer from a problem of large errors as it does not consider the correlation between predicted value and existing value. In this chapter, a new adaptive algorithm called the Data Imputation LMS (DI-LMS) adaptive algorithm is proposed, where a correlation factor is introduced in the weight update function such that only highly correlated data is used for prediction. Thus the proposed method of imputation has low complexity. Further the experimental results obtained using well-known datasets with different missing degrees and mechanisms shows that the error rate is reduced with improved accuracy when the proposed method of imputation is compared with other statistical and machine learning methods of imputation and validated by using state-of-the art classifiers.
Blockchain taiga

In this chapter the blockchain environment, an immutable, decentralized, and transparent record of all transactions throughout a peer network, is explained. Blockchain technology can enable trusted and secure transactions in healthcare systems, facilitating up-to-date and transparent data flows and thus decreasing siloed data parts. We show how reliable cradle-to-grave healthcare data set solutions can be developed, allowing patients to lead in facilitating a more efficient and up-to-date information flow between different healthcare providers. Blockchain applications in pharmaceutical care may result in, among other benefits, more secure personal health applications, improved health claim management, and faster reimbursement of services. Blockchain technology by itself will not automatically solve all data-related problems that have plagued healthcare information systems for decades. A number of hurdles have to be overcome before blockchain technology can help pave the way to a secure and interconnected healthcare system.
Hidden Surface Removal in Augmented Reality: Hand Region Extraction using PCA

Recently, augmented Reality (AR) is growing rapidly and much attention has been focused on interaction techniques between users and virtual objects, such as the user directly manipulating virtual objects with his/her bare hands. Therefore, the authors believe that more accurate overlay techniques will be required to interact more seamlessly. On the other hand, in AR technology, since the 3-dimensional (3D) model is superimposed on the image of the real space afterwards, it is always displayed on the front side than the hand. Thus, it becomes an unnatural scene in some cases (occlusion problem). In this study, this system considers the object-context relations between the user's hand and the virtual object by acquiring depth information of the user's finger using a depth sensor. In addition, the system defines the color range of the user's hand by performing principal component analysis (PCA) on the color information near the finger position obtained from the depth sensor and setting a threshold. Then, this system extracts an area of the hand by using the definition of the color range of the user's hand. Furthermore, the fingers are distinguished by using the Canny method. In this way, this system realizes hidden surface removal along the area of the user's hand. In the evaluation experiment, it is confirmed that the hidden surface removal in this study make it possible to distinguish between finger boundaries and to clarify and process finger contours.