Reviewerly/exHarmony huggingface dataset:
مؤشرات قياس الأداء في جامعة القدس المفتوحة في ضوء الجودة الإدارية

ملخص: هدفت الدراسة إلى تعرف درجة توافر مؤشرات قياس الأداء في جامعة القدس المفتوحة في ضوء الجودة الإدارية من وجهة نظر الإداريين، واستخدمت الدراسة المنهج الوصفي التحليلي، والاستبانة كأداة للدراسة تكونت من 30 فقرة موزعة على ستة مجالات: (القيادة الإدارية، الجودة والتطوير، إدارة الموارد البشرية، نظم المعلومات الإدارية، الرقابة وتقييم الأداء، رضا المستفيد)، وطبقت الاستبانة على عينة عشوائية مقصودة تكونت من أصحاب المناصب الإدارية في قطاع غزة.وأهم ما توصلت إليه نتائج الدراسة أن استجابات أفراد عينة الدراسة حول درجة توافر مؤشرات قياس الأداء في جامعة القدس المفتوحة في ضوء الجودة الإدارية من وجهة نظر الإداريين جاءت بدرجة كبيرة، حيث بلغت الدرجة الكلية للمتوسط الحسابي للمجالات الستة (3.96)، وبوزن نسبي بلغ (79.2%)، كما أظهرت النتائج عدم وجود فروق ذات دالة إحصائياً عند مستوى الدلالة (α ≤ 0.05) بين متوسط تقديرات عينة الدراسة حول درجة توافر مؤشرات قياس الأداء في جامعة القدس المفتوحة في ضوء الجودة الإدارية تعزى إلى متغير الجنس، ووجود فروق ذات دالة إحصائياً بين إجابات أفراد عينة الدراسة تعزى إلى متغير سنوات الخدمة كانت لصالح الفئة (أكثر من 10 سنوات). الكلمات المفتاحية: مؤشرات قياس الأداء، الجودة الإدارية، جامعة القدس المفتوحة. Abstract The study aimed at identifying the degree of availability of performance measurement indicators at Al-Quds Open University in the light of administrative quality from the point of view of the administrators. The study used the analytical descriptive method and the questionnaire as a study tool consisting of 30 paragraphs divided into six fields: (administrative leadership, quality and development, , Management information systems, monitoring and performance evaluation, beneficiary satisfaction). The questionnaire was applied to a random sample of the owners of administrative positions in the Gaza Strip. The most important findings of the study were that the responses of the sample of the study on the degree of availability of performance measurement indicators at Al-Quds Open University in light of administrative quality from the point of view of the administrators came to a great extent. The total score for the six domains (3.96), with a relative weight of 79.2 The results showed that there were no statistically significant differences at (0.05 α ≤) between the average of the sample of the study sample on the degree of availability of performance measurement indicators at Al-Quds Open University in light of the administrative quality due to gender variable and the existence of statistically significant differences between The responses of the study sample individuals are attributed to the absentee Years of service was in favor of the category (more than 10 years). Keywords: Performance Indicators, Quality Management, Al Quds Open University
User Data Driven Recommendation for Location

Location recommendation plays a crucial play in serving to users to seek out their interested spots. Considering recent analysis that was studied the way to advocate locations with the important, social, geographical knowledge, a number of them shown regarding the problems relating to attributes of new users. complicated methodology is to convey them into explicit- feedback- based mostly content-aware (cf)collaborative filtering, however they have to draw negative attributes for higher learning performance, as users’ negative preference isn’t thought-about in human quality. Before theories have slightly shown sampling-based strategies don't exercising well. So, we tend to projected a ascendable Implicit-feedbackbased mostly Content-aware cooperative Filtering (ICCF) framework to urge precise real knowledge and to good afar from negative attributes sampling. At last, we tend to perform ICCF with in users have profiles and details of attributes. Final performance show that ICCF outperforms many different competitory baselines,so that user attribute info isn't solely effective for up recommendations however additionally addressing initial knowledge and different eventualities
Eyeball Controlled Wheelchair

: A basic wheelchair is a gadget for people influenced by moderate, extreme physical incapacities and interminable disease. It is also meant for the elderly people. Many people with disabilities cannot manage the energized wheelchair operating joystick, sound, furthermore, hand developments as it is harder for the individual to do such specific tasks also it is programming focused. This strategy comprises of equipment which reduces the person's work utilizing the image processing method. This model comprised of a camera that tracks the eyeball movement and hence the position of the pupil by the image processing technique. And thereby the wheelchair is constrained by a user’s eye gesture in an indoor space. When the development has been initiated and it is given to the Raspberry pi for processing. The procedure relies on the feed coding and an output is given into the driver circuit. Likewise, the hindrance location sensors will be associated as an Emergency Brake that gives necessary conditions for the conventional activity of the wheelchair framework. Every one of the four wheels are associated with a driving circuit that moves the wheelchair
Riding Robotics

This paper outlines the research field of Riding Robotics (RiRobo). This research field targets small vehicles (small mobility) such as manned mobility, manned robot, riding robot, personal mobility, smart mobility, vehicle, riding, mobile robot. Small vehicles are fun, convenient and help our lives. This paper introduces research in the field of Riding Robotics, focusing on the presentations made in the organized session over the past two years. Researches on various aspects such as research on the structure, mechanism, control, and movement of vehicles, research on the body of a rider, research on the psychology of a rider, and concept proposal are being conducted. This field is an area where future development is expected.
Security Using Modified Hierarchical Attribute Based Encryption for Mobile Cloud Computing

This manuscript is an undertaking to give an improved statistics amassing safety show in Cloud Computing as well as making a put confidence in condition in cloud computing. There is a significant proportion of persuading clarifications behind associations to send cloud-based limit. For another business, start-up expenses are basically reduced in light of the fact that there is no convincing motivation to contribute capital ahead of time for an inside IT structure to support the business. We judge so as to information storing safety in Cloud Computing, a domain overflowing with difficulties and of focal criticalness, is immobile in its soonest arranges currently, as well as various investigation issues be nevertheless to exist recognized. In this manuscript, we investigate the issue of statistics safety in cloud statistics accumulating, to make sure the rightness of clients' data in cloud statistics storing. We projected a Hierarchical Attribute -base safe Outsourcing pro admittance in Cloud computing which in like manner ensures data amassing protection as well as survivability thusly giving trust in condition to the customers. To fight beside unapproved in sequence spillage, receptive information must exist mixed via re-appropriating to offer start to finish information security certification in the cloud as well as past. We include condensed the estimation instance in light of input dimension via executing ECDSA algorithm pro Cryptographically undertakings. Many cloud has are giving administrations to various customers to their information. Because of calamity the executives cloud can be utilized as reliable stockpiling system. For such cloud stockpiles encryption is done numerous far for verifying information. The trait based encryption is the strategy to encode the substance. In like manner we exploit push mail algorithm pro solution exchange among owner as well as customer. It improves the security in the proposed show sufficiently.
LATENT-SEMANTIC ANALYSIS, SOCIAL NETWORKS AND NON-STRUCTURED DATA: INTERACTION METHOD

This article examines the method of latent-semantic analysis, its advantages, disadvantages, and the possibility of further transformation for use in arrays of unstructured data, which make up most of the information that Internet users deal with. To extract context-dependent word meanings through the statistical processing of large sets of textual data, an LSA method is used, based on operations with numeric matrices of the word-text type, the rows of which correspond to words, and the columns of text units to texts. The integration of words into themes and the representation of text units in the theme space is accomplished by applying one of the matrix expansions to the matrix data: singular decomposition or factorization of nonnegative matrices. The results of LSA studies have shown that the content of the similarity of words and text is obtained in such a way that the results obtained closely coincide with human thinking. Based on the methods described above, the author has developed and proposed a new way of finding semantic links between unstructured data, namely, information on social networks. The method is based on latent-semantic and frequency analyzes and involves processing the search result received, splitting each remaining text (post) into separate words, each of which takes the round in n words right and left, counting the number of occurrences of each term, working with a pre-created semantic resource (dictionary, ontology, RDF schema, ...). The developed method and algorithm have been tested on six well-known social networks, the interaction of which occurs through the ARI of the respective social networks. The average score for author's results exceeded that of their own social network search. The results obtained in the course of this dissertation can be used in the development of recommendation, search and other systems related to the search, rubrication and filtering of information.
Research on Spatial Modeling of Urban Transportation Networks using GIS

delivery availability is a substantial motive force of city development and key to the possible development of metropolis agencies. This paper famous a number one GIS-based totally tool created to permit the short research of availability by way of diverse vehicle modes. supposed to be adaptable and use brazenly available statistics, this device (worked in ArcGIS) makes use of summed up fee to quantify shipping charges crosswise over systems which include financial and separation components. The paper displayed three fundamental avenue set up availability assessing hints, provided hypothesis premise of the model development in detail, and the version development technique. Taking Foshan town as an example, the models had been tried utilising the metropolis street set up statistics. At final, further urban street prepare availability evaluation fashions are mentioned. The shape contemplations and statistics necessities for executing a GIS-based totally metropolis transportation research framework are broke down and part of the economically on hand GIS programming is assessed. Accentuation is ready on the utilization of a GIS in version-prepare transportation programs as opposed to with appreciate to specific capability employments of GIS. some utilizations of GIS approach for city transportation research are portrayed. I
Cloud Foundations

In this chapter, we lay the foundation for understanding what the cloud actually is. We start by considering the history of the term. Then we look at how to define it in order to get a firmer handle on what we mean by cloud computing. We also investigate different ways to conceptualize the cloud. It has, for example, been suggested that the cloud is a utility or a service, which highlights certain important aspects of the cloud but also mischaracterizes it in other ways. The chapter seeks to establish an understanding of what it means when we talk about the cloud.
Novel Copy Move Forgery Detection Based on Repeated Feature Extraction and Delaunay Triangulation

Nowadays new and creative methods of forging images are developed with the invention of sophisticated softwares like Adobe photoshop. Tools available in such softwares will make the forged image look real which cannot be even identified by a naked eye. In this paper, key point based approach of taking out features using Scale Invariant Feature Transform (SIFT) is used. The feature points thus extracted are then modeled to get a set of triangles using Delaunay Triangulation method. These triangles are matched using mean vertex descriptor and the removal of false positives is done using the method of Random Sample Consensus (RANSAC). Implementation show that the proposed approach outdoes the equivalent methods
Neural Nets and Deep Learning

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.
Crossing the Boundaries: Codeswitching in Conversation

Language contact occurs when speakers of different languages interact and their languages influence one another. Drawing on the author's own first-hand observations of child and adult bilingualism, this book combines his original research with an up-to-date introduction to key concepts, to provide a holistic, original theory of contact linguistics. Going beyond a descriptive outline of contact phenomena, it introduces a theory of contact-induced language change, linking structural change to motivations in discourse and language processing. Since the first edition was published, the field has rapidly grown, and this fully revised edition covers all of the most recent developments, making it an invaluable resource for researchers and advanced students in linguistics.
Continuous Rationale Visualization

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.
Awe-Inspiring Experiences

In this chapter, I’ll walk you through some tips and tricks on making awe-inspiring Mixed Reality experiences! By now, you’ve learned all the basics you need to make compelling applications. There are dozens of books that can be written on advanced Mixed Reality development and techniques – and even more Mixed Reality techniques that are yet to be discovered! I’ll give you a taste of some things you can do to enhance your applications and experiences by introducing you to some design concepts, HoloLens project samples, and some third-party tools that you can use.
Beating Cyberthieves

The internet ecosystem is constantly evolving, and while it has enabled businesses to grow in ways never thought possible, it has also created a number of unintended opportunities for cyberthieves to take advantage of unsuspecting engineers and their businesses. Knowing what to do should you fall victim to a cyberthief can protect you and your business from serious problems.
Preface

GeoProNH III National scientific conference with foreign participants “Geodynamical Processes and Natural Hazards” This issue presents the proceedings of the GeoProNH – III National scientific conference with foreign participants “Geodynamical Processes and Natural Hazards”. The conference was held May 27-31, 2019 in Yuzhno-Sakhalinsk, Russia, and considered the following topic areas: - the seismicity of the Russian Far East and Eastern Siberia; - the tectonics and geodynamics of the northwestern Pacific; - manifestations of tsunamis and other marine hazards; - recent volcanism and methods of its monitoring; - geological and geomorphological aspects of the coastal assimilation strategy; - environmental problems and geoecological hazards. The Sakhalin and Kuril Islands are parts of the Pacific Ring of Fire, so this region undergoes almost all possible geohazards: earthquakes, tsunamis, volcano eruptions, etc. More than 120 scientists, experts and postgraduates from Belarus, Egypt, France, Japan, Kyrgyzstan, and Russia took part in the GeoProNH Conference and discussed the current state of the art and advances in geosciences related to the analysis of natural hazards and/or their preventions. The conference also considered fundamental and applied problems of geology, geophysics, geodynamics, geoecology, oceanology, seismology, volcanology, etc. related to the dangerous natural phenomena mentioned. The Conference Program included four days of plenary and topical sessions, poster presentations, and two days of field geological excursions. The ultimate goal of the conference was to highlight and share the best ways to reduce negative impacts of the above hazards using modern monitoring systems. The published proceedings, hopefully, will serve the same purpose. The issue is addressed to researchers, experts, and students who deal with geohazard assessments and relevant topics of geosciences.
Blockchain Enabled Supply Chain Management

Blockchain technology has the potential to create new avenues for Economic and Social systems. Blockchain enabled supply chain solutions have drastically proven to reduce cost and efficiency in supply chain industry. The complexity of Supply chain management which helps to create and distribute goods is very high. The supply chain spans over numerous stages with long time duration involving different geographical locations and large number of invoices and payments, people and entities based on the nature of the product involved. The blockchains are perceived to bring huge transformations in the current supply chain and logistics industry which are complex and transparent. This paper is organized as Section I-Introduction, Section II-Blockchain in Supply chain, Section III-Elements of Blockchain affecting Supply chain, Section IV-How Blockchain revolutionizes Supply chain, Section V-Results,Section V1-Conclusion.
Hybrid Deep Transfer Network and Rotational Sample Subspace Ensemble Learning for Early Cancer Detection

Accurate histopathology cell image classification plays an important role in early cancer detection and diagnosis. Currently, Convolutional Neural Network is used to assist pathologists for histopathology image classification. In the paper, a Min mice model was applied to evaluate the capability of Convolutional Neural Network features for detecting early-stage carcinogenesis. However, due to the limited histopathology images of the mice model, it may cause overfitting for the classification. Hence, hybrid deep transfer network and rotational sample subspace ensemble learning is proposed for the histopathology image classification. First, deep features are obtained by deep transfer network based on regularized loss functions. Then, the rotational sample subspace sampling is applied to increase the diversity between training sets. Subsequently, subspace projection learning is introduced to achieve dimensionality reduction. Finally, the ensemble learning is used for histopathology image classification. The proposed method was tested on 126 histopathology images of the mouse model. The experimental results demonstrate that the proposed method has achieved a remarkable classification accuracy (99.39%, 99.74%, 100%). It has demonstrated that the proposed approach is promising for early cancer diagnosis.
K-Means Cluster Based Oversampling Algorithm for Imbalanced Data Classification

Imbalanced data classification problems endeavor to find a dependent variable in a skewed data distribution. Imbalanced data classification problems present in many application areas like, medical disease diagnosis, risk management, fault-detection, etc. It is a challenging problem in the field of machine learning and data mining. In this paper, K-Means cluster based oversampling algorithm is proposed to solve the imbalanced data classification problem. The experimental results show that the proposed algorithm outperforms the existing oversampling algorithms of previous studies.
Design and Implementation of Grievance Filing Application using Automatic Text Classification

This research aims to design a Grievance Filing System built using automatic text classification without any manual interruption. Various methodologies are followed to achieve it and are implemented. Performance of the different algorithms is discussed. People are less aware about the lengthy methods for lodging complaints. We propose a simplified process of enrolling grievances to ministries. The system accepts grievances in recorded voice form. The system is designed for Marathi language. Input in the form of speech will ease people’s comfort for lodging grievances. We present a model where voice is first preprocessed, followed by text classification using deep learning approaches such as CNN and LSTM, the grievances will be sent to respective ministry. This system can be used by government ministries to get grievances from common people through a simplified process. User will be notified on the progress of their lodged complaint and on its successful resolution by respective ministry.
Logical & Analytic features of Internet of Things (IoT)

The Internet of Things (IoT) is changing individual’s encompassing physical world into a data biological system that encourage our regular day to day existence. Billions of brilliant articles will progress toward becoming information producing "things" that can detect ecological changes and report their detected information in not so distant future. Utilizing the immense measure of tactile data is a key issue to understand the IoT arrangements in numerous territories. Sufficient advancements are required for information accumulation, transmission, information handling, investigation, announcing, and progressed questioning. The Internet of Things (IoT) has been picking up force in both the business and research networks because of a blast in the number of keen cell phones and sensors and the potential uses of the information delivered from a wide range of spaces. The IoT has a particularly promising future, since governments of several countries is focusing, supporting and endeavouring the undertakings for developing better establishment, even associations are considering inventive things, and organizations think about the points of interest which Internet of Things conveys to the table. IoT progress could end up being astonishing on a gigantic scale, with additionally created research and resources.