Reviewerly/exHarmony huggingface dataset:
Application of Fuzzy Cognitive Maps for Modelling OSH Management Systems

Fuzzy Cognitive Maps (FCMs) method is applied in research as well as in business and non-profit practice to model fragments of reality composed of logic constructs. The method allows for description and analysis of the interrelated objects constituting these fragments, especially when both objects and interrelations are immeasurable or difficult to be characterized with the use of numbers. FCMs are created on the basis of knowledge of people with practical expertise of the modelled objects. Verbal descriptions of experts are converted into numbers according to the defuzzification procedure. This allows for mathematical simulations to be carried out and forecasting changes in the model. In this chapter, FCMs are recommended as a tool for modelling and improving OSH management systems. The proposed methodology assumes presenting an OSH management system as a set of interrelated processes and factors exerting negative and positive impact over these processes and over safety and health performance. Practical information is provided on how to elaborate such a model and conclude on possible OSH management system improvement options. An exemplary model is presented in a graphic form. Furthermore, the methodology for transforming the graphical model into a mathematical notation that allows for calculation-based simulations is explained.
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Software Defect Prediction Based on Selected Features Using Neural Network and Decision Tree

Software defect prediction is a vital part in software reliability field. Here, the software modules are identified as defective or non-defective based on selection of the right set of software metrics. Software quality has become an emerging area for researchers to deal with challenges like defect prediction, defect removal, bug severity etc. The objective of this paper is to apply Machine Learning techniques for feature selection to remove redundant metrics and build software defect prediction model to label the software modules. We use principal component analysis technique as feature selection technique to reduce the redundant features on basis of Eigen value. After identifying the best set of software metrics, we develop software defect prediction models to classify software modules using Artificial Neural Network (ANN) and Decision Tree (DT). We have worked on data sets collected from data repository available on GitHub. The best set of software metrics act as predictors, which are obtained after removing irrelevant software metrics and building model for software defect prediction. We also compare the two classifying techniques on the basis of F-score, AUC, precision and sensitivity and accuracy.
A Mixed Model for Privacy Preserving and Secure Sharing of Medical Datasets

Data mining has been a huge success from the beginning because of what it can offer and do. But there are some concern about the privacy of people in the used data. The problem here is being able to share datasets without putting privacy of the concerned people at risk and without being accessed by unauthorized people. That’s where the different anonymization techniques like suppression and generalization can be employed to safeguard privacy of people in the datasets. Privacy preserving data mining (PPDM) has been researched for some years now, but there still many things to do. Privacy concerns are everywhere, but here the author only considered privacy issues with medical dataset. How to protect privacy of people in those dataset while keeping the data in them useful. In this paper, the author present a work which combines anonymization in order to tackle privacy issues in a medical dataset and secure sharing in order to control the access to the datasets. In the end, it is clear that the combination of anonymization and secure sharing offers not only protection against re-identification but also against unauthorized access to a given dataset.
Building Neural Networks as Dataflow Graphs

Generally, data processing programs can be organized into a data flow graph that defines the operations to be performed sequentially on the data. The operation of neural networks can also be interpreted in a similar way, in which the input data to be processed is a specific data set and the operations to be performed on the data are the layers of the net. Due to architectural reasons, the entire neural network graph must be built before actual running, thus it is necessary to change data flows' topological execution to evaluation preceding graph building since knowing the layers separately is not enough to operate the nets. As a solution for displaying editable program graphs, we created a framework in which data processing related Python packages can be described and the programs built from them can be visualized and executed.
Computational Hardness of Multidimensional Subtraction Games

We study the algorithmic complexity of solving subtraction games in a fixed dimension with a finite difference set. We prove that there exists a game in this class such that solving the game is $${\mathbf {EXP}}$$-complete and requires time $$2^{\varOmega (n)}$$, where n is the input size. This bound is optimal up to a polynomial speed-up. The results are based on the construction introduced by Larsson and Wästlund. It relates subtraction games and cellular automata.
Display Standards for French Cinemas

French cinema theaters follow strict rules; there are two standards that must be followed when granting theater operation licenses. One standard is concerned with architectural considerations and the other movie reproduction parameters. These two standards undergo periodic revisions. The main goal behind these specifications is to ensure that movies are reproduced uniformly in all theaters while matching the intention of the creative team during the final check. Another goal is audience satisfaction and the avoidance of unnecessary physical or audio visual stress. The specifications listed in the standard related to movie reproduction include a uniformity formula. Counterexamples demonstrate problems with the validity of this uniformity. A new uniformity method of measurement is under study. The proposed method unifies projection and display systems in the same measurement. The projection vignetting effect is canceled using the current room and screen dimensions. The formula is also independent of the reproduction system’s dynamic range. Nine locations on screen are used as points of measurement. The proposed measurement of uniformity is based on a statistical measurement called the Kolmogorov–Smirnov (K–S) distance. It compares the current results with a standard statistical distribution. The type of distribution is chosen based on practical considerations.
The Influence of Reading of Various Genres on Writing Enhancement

Busy with daily works, people choose to relieve intensive pressure through reading. A growing number of language instructors and curriculum designers also believe that students’ language proficiency will be effectively enhanced when novel reading practices are applied. Therefore, this study aims to investigate the influence of reading of various genres on students’ written English. The research reviewed 30 papers on relevant topics between 2016 to 2018. They were categorized based on several aspects such as years, research design, levels of reading as well as research participants. A majority of the papers reviewed in this study employed experimental approach to conduct their researches. The results suggested that experimental approach is relatively more reliable than qualitative approach; choosing proper course materials plays a significant role when processing a research.
Modified HPSO using TVAC and Analysis using CEC Benchmark Functions

To speaks to the potential answers for the particles where every last molecule has two vectors: position vector and speed vector, A Particle Swarm Optimization calculation presented. In this paper we presented another idea for the estimation of the speed with the idea of Euclidian Distance. The presented idea will help in finding the closeness of molecule with Gbest (Global best) and Pbest (Personal best). Our mean to acquaint this idea is with simply locate the ideal arrangement inside a sensible number of ages.
Adaptation of MAPE-K and Fuzzy Q-Learning in SLA management

Abstract A Service Level Agreement (SLA) is the legal catalyst to monitor any contract violation between end users and ISPs and is embedded within a Quality of Service (QoS) framework. The key to the proposed architecture is the utilization of self-capabilities designed to have self-management over uncertainties and the provision of self-adaptive interactions. Thus, the Monitor, Analyse, Plan, Execute and Knowledge Base (MAPE-K) approach can deal with this problem together with the integration of Fuzzy and Q-Learning algorithms. The proposed experiment is in the context of autonomic computing. An adaptation manager is the main proposed component to update admission control on the ISP current resources and the ability to manage SLAs.The proposed solution, demonstrating Q-Learning works adaptive with QoS parameters, e.g. Latency, Availability and Packet Loss. With the combination of fuzzy and Q-Learning, we demonstrate that the proposed adaptation manager is able to handle the uncertainties and learning abilities. Q-Learning is able to identify the initial state from various ISPs iterations and update them with appropriate actions, reflecting the reward configurations. The higher the iterations process the higher is the increase the learning ability, rewards and exploration probability.
Real Time Detection and Recognition of Human Faces

Face detection and recognition has become a challenging issue in computer vision technology. Several algorithms have been implemented for the effective detection and recognition of human faces. In this paper, local binary patterns histogram algorithm and convolution neural networks are executed with different datasets considered. The datasets adapted are ORL dataset, FEI dataset and the dataset created by our own with 12 individuals each of 100 images. It is observed that the convolution neural networks algorithm performed better compared to LBPH. This work can be applied for security purposes and attendance monitoring applications.
Target detection performance for head mounted indirect vision displays

Participants used a helmet-mounted display (HMD) and a touchscreen monitor to detect targets across 3 different approaches to display 360º video for indirect vision display systems. A within-subject design was used with targets ranging from dismounted, mounted, and aerial targets. The number of targets detected, workload, and usability of each condition was measured. The HMD condition produced significantly more targets detected overall and within each type of target type compared to the monitor condition. HMD use also produced a significantly lower level of mental workload as measured by the NASA TLX and achieved a significantly higher level of usability compared to the other conditions. Possible reasons for these differences are discussed along with discussion on future studies using HMDs and mixed reality technology for indirect vision display systems.
The Effect of Mobile Application Usage on Dialect Perception

Abstract The extent of mobile application usage roles in language dialect retention has roused curiosity and called for research. The fast-paced world that we are living in today has resulted in many effects with regard to the use and retention of a subject including how dialects are used. This concept paper talks in general about the significance and effect of using mobile applications on dialect and language. The use of mobile applications in most cases has become a very handy tool for every business. We have to admit that it is a time-saving, financial, and information-sharing system that makes things go faster and travel more efficiently. The study of mobile application in many parts of the world involves the use of qualitative and quantitative methods so that more accurate and scientific results can be extracted. Our goal is to look at the impact and importance of using mobile applications to retain the dialect used in particular and the use of language in general. The findings of the study have brought us to two conditions with good and bad consequences on the use of both dialect and language. The vast education system that we have in particular has demonstrated the significant use of mobile applications. As everything requires a very efficient and efficacious financial system its significant is irefutable. The results shown here will boost the improvement in language learning and dialect retention via a multitude of mobile applications. The use of both methods in carrying out mobile application review have been getting some very good responses.
Clustering on the Basis of a Divisive Approach by the Method of Alternative Adaptation

The paper presents a combined approach to clustering based on the integration of the divisive method with the methods of collective alternative adaptation. This group of methods is characterized by the sequential separation of the original cluster consisting of all objects, and the corresponding increase in the number of clusters. The objective is to enhance the convergence of the algorithm and the ability to exit from local optima, which allows you to work with large-scale problems and get high-quality results in a reasonable time. In this paper, the process of finding a solution is represented as an adaptive system. Under the influence of a series of adaptive actions, all objects (collective) are successively redistributed between the clusters. The goal of a specific object mi is to reach a state in which the total vector of forces acting on it from all objects placed in the same cluster with mi had the maximum value. The goal of the collective of objects is to achieve such a separation of objects into clusters, at which the minimum distance between a pair of objects belonging to different clusters has a maximum value. To implement the adaptation mechanism, each object mi is assigned an adaptation machine AAi. Studies have shown that the time complexity of the algorithm at one iteration has an estimate of O (n2), where n is the number of objects.
Integrity based Authentication and Secure Information Transfer Over Cloud for Hospital Management System

Cryptography has been utilized to address security issues on various administrations. It is essential to secure information and to guarantee the secure exchange of medical information. Symmetric key crypto-algorithms are quick and incredibly secure because of their extraordinary key size. Amidst the other symmetric crypto-algorithms, Blowfish algorithm has indicated prevalence in execution. SHA3 and Diffie Hellman algorithms among the others exhibited fantastic security since it is well known to have no effective attacks. Right now, a large portion of the calculations depends on symmetric key or asymmetric key to verify data. The vast majority of the applications need trustworthiness and confirmation of information. The proposed application has a hybrid approach for safeguarding data. The framework joins private and open key cryptography idea for accomplishing the objectives of security (CIA). The secrecy can be accomplished utilizing symmetric key Blowfish calculation. Integrity is accomplished through SHA3. Secure information transmission is guaranteed using the Diffie-Hellman key exchange algorithm. The EC2 which is Amazon web service's web server provides scalable computing in the amazon cloud. The S3 is the simple storage service involved in the proposed work which is used to store and retrieve information or data at any time and place.
Properties of cartesian multiplication operations in complete fuzzy graphs, effective fuzzy graphs and complement fuzzy graphs

Abstract This study aims to investigate the properties of cartesian multiplication operations on fuzzy graphs. The properties investigated are cartesian multiplication on complete fuzzy graph, effective fuzzy graph and complement fuzzy graph. The method used in this study is a theoretical research method. The results showed that the Cartesian multiplication of two complete fuzzy graphs is not a complete fuzzy graph. The Cartesian multiplication of the two effective fuzzy graphs is the effective fuzzy graph, while for the Cartesian multiplication of the two fuzzy complement graphs, it is not the same as the Cartesian multiplication of the two effective fuzzy graphs.
The effectuality of animated media for teaching biotechnology materials in indonesian rural primary schools

Abstract Learning technology has been an intriguing medium which may escalate class engagement and students’ interests into learning. However, not every student is entitled to equal opportunity to be able to benefit from this often considered luxury for some, for instance for those living in the rural areas of Indonesia. This study aims to measure the effectiveness of animated media developed for teaching biotechnology materials in rural primary schools in Indonesia. Four teachers from two rural primary schools in the east of Java, Indonesia participated in this study. The teachers and research team collaborated in a lesson study style activities and take turn to use the media to teach materials regarding biotechnology for their students. This mixed method study utilised data gathered from students’ pre-test and post test and the results of interviews with the four teachers, and participatory observation reports of the activities. The results of this study indicated that the media were significantly effective to improve students’ mastery of biotechnology materials, which was facilitated by the affordance of the media to alleviate students’ excitement, autonomy, and focus on learning.
The Effect of Scene Context on Weakly Supervised Semantic Segmentation

Image semantic segmentation is parsing image into several partitions in such a way that each region of which involves a semantic concept. In a weakly supervised manner, since only image-level labels are available, discriminating objects from the background is challenging, and in some cases, much more difficult. More specifically, some objects which are commonly seen in one specific scene (e.g. "train" typically is seen on "railroad track") are much more likely to be confused. In this paper, we propose a method to add the target-specific scenes in order to overcome the aforementioned problem. Actually, we propose a scene recommender which suggests to add some specific scene contexts to the target dataset in order to train the model more accurately. It is notable that this idea could be a complementary part of the baselines of many other methods. The experiments validate the effectiveness of the proposed method for the objects for which the scene context is added.
Mobile application In al-Shafie Poetry

Abstract The use of mobile applications has grown rapidly in the world of science and technology. Besides, Internet access capability, this application also has operating system just like a computer but in a smaller, lightweight form that can be carried anywhere. Therefore, this application should be widely used especially as an educational learning medium because it facilitates every business. The purpose of this concept paper paper is to discusses the significance and effect of using mobile applications on poetry and literature in general. The study of mobile application in language and literature involves the used of qulitative approach with exploratory analysis methods to obtain more accurate and scienctyfics results.The results shown that mobile applications will facilitate improvements in language learning and literature. The use mobile application in language and literature review viewed very well.
Cinema Station Application (CSA): An augmented reality application for accessing film information and online cinema booking

Cinema is an effective medium for education and recreation, as it plays a crucial social, political, educational, and moral role in life. Reopening cinemas in Saudi Arabia has garnered much attention from cinema operators, moviemakers, and Saudi citizens who are eager to watch movies in cinemas. The main problem that cinemas will face when they reopen will be the overwhelming demand for tickets, as it will be difficult to reserve a ticket on a regular day and almost impossible for movie premieres. This paper describes a Cinema Station Application (CSA), which is a mobile application for cinemas that allows users to search for movies and cinema operators quickly and easily. Users have the opportunity to book a ticket anywhere and anytime. Furthermore, the application uses augmented reality technology to display a movie trailer directly on the poster and view reviews, the overall rating, and the cast.
Visual Representation of African Traditional Medicine Recipes Using Icons and a Formal Ontology, ontoMEDTRAD.

In traditional West African medicine, most practitioners are illiterate for official languages. 1127 local languages exist in this region. The transmission of knowledge in this traditional medicine is notoriously oral. In order to enable practitioners to communicate and preserve this knowledge, we are building SysMEDTRAD, a traditional medicine management system, based on a formal ontology of traditional medicine called ontoMEDTRAD. To overcome the language and illiteracy barriers, we propose to combine realistic photographs of plants with formal iconic descriptions of plants and recipes. This paper presents the formal and automatized representation of traditional African medicine recipes.
High-Resolution Document Image Reconstruction from Video

Today, smartphones with high-quality built-in cameras are very common. People prefer to take pictures from documents with smartphones instead of scanning them with a scanner. Due to the limitation of scanners input size, it is difficult to scan everything with them. Resolution and quality of smartphone cameras are not enough to take a picture from large documents like posters. In this paper, we proposed a pipeline to make a high-resolution image of a document from its captured video. We suppose that during the record of the video, the camera was moved slowly all over the surface of the document from a close distance. In the proposed method we find the location of each frame in the document and we use a sharpness criterion to select the highest possible quality for each region of the document among all available frames. We evaluated our method on the SmartDoc Video dataset and reported the promising results.