Reviewerly/exHarmony huggingface dataset:
Bidirectional Chain Replication for Higher Throughput Provision

Provision of higher throughput without sacrificing consistency guarantees in replication systems is a critical problem.In this paper, we propose a novel approach called Bidirectional Chain Replication (BCR) to improve throughput in traditional Chain Replication (CR) through better utilization of computing and communication resources of the chain.Unlike CR where the whole replicated data store is treated as a single unit, in BCR the replicated shared data at each server in the chain is split into two disjoint Logical Partitions (LP 1 , LP 2 ).This forms two chains running concurrently on the same hardware in two opposite directions; the first chain (CR 1 ) exclusively manipulates data objects in LP 1 , while the second chain (CR 2 ) exclusively manipulates data objects in LP 2 , therefore, conflict is avoided and concurrency is guaranteed.The simultaneous employment of these two chains results in better utilization of hardware in the sense that the two chains can evenly share the workload, hence, throughput can be improved without sacrificing consistency.Experimental results showed an improvement of approximately 85% in throughput of BCR over CR.
Genogram Visualization Using Social Network Approach for Medical Family Tree

Genogram is a graphical representation of a family tree. It can also be used to track and provide some information about family medical history and relationships, which allow user to understand the general and complex information of their family for generation. However, some limitations do exist while using genogram, namely scalability problems while visualizing the wealth and complex information once the family tree gets bigger. In this paper, we present an approach to visualize these type of data using social network visualization approach. Results shows that the prototype tool, which employ the social action approach, does improve user understanding of medical family tree in terms of usefulness and on ease of use. It is hope that this approach can help user especially healthcare professionals to understand medical family tree data.
Fossil Finds Around Ancient Troy

Greek myths mention the existence of a monster (ketos) arount the city of Troy.This monster was killed by Heracles at cape Agammia (now Kucuk Besire Burun).There is a scene on a Greek vase dated to the sixth century, which depicts the heroic deed of Heracles at Agammia.The head of the monster is unmistakably a large animal fossil skull.In our survey project around Troy, we found fossil beds in in Beşige Burun, which most likey is the source of Greek myths concerning the Monster of Troy.
A Study on the Realization of ‘-(으)ㅁ’, ‘-기’ Noun Clause Embedded Sentence : Use and Awareness Levels of Korean Learners for Academic Purpose.

This study aimed to prepare basic educational data so that learners can fully understand the usage of sentences embedded with noun clauses “-(으)ㅁ” and “-기,” and to actively utilize them in academic texts. Accordingly, this study attempted to gain a comprehensive understanding of usage aspects and awareness levels by analyzing academic texts written by those whose mother tongue is Korean as well as academic learners, and by conducting a grammaticality judgement test among the learners. Based on the research on usage aspects and awareness levels of sentences embedded with noun clauses “-(으)ㅁ” and “-기,” this work suggests categorization of the combined predicates shown in native Korean speakers’ academic texts into types in the education on sentences embedded with noun clauses “-(으)ㅁ” and “-기.” In addition, it highlights the need to explain not only the syntactic restriction but also its function within academic texts in detail. Lastly, it posits that the learners would be better able to grasp the difference if the two nominalizer endings are presented in a comparative manner. This study clarified the usage patterns of native Korean speakers and academic learners by limiting the scope of the text corpora, which have been utilized previously to analyze sentences embedded with noun clauses, to academic texts written by people whose mother tongue is Korean. Furthermore, this study is meaningful as it suggests effective contents and methods for the education for academic learners by looking at the difficulties learners have faced in utilizing sentences embedded with noun clauses “-(으)ㅁ” and “-기,” based on their grammaticality judgement test results.
Integrated platform and response systemFor healthcare using Alexa

This paper presents a Healthcare system by providing a virtual personal assistance using the Amazon Alexa.Amazon Alexa is an application program that understands voice commands and completes that commands for the user.Amazon Echo is not only a smart speaker, but operates as an intelligent personal virtual assistant. Alexa is Hands-free thatcan allow easier access to the medical information. Alexa has been programmed with the information about the patients,doctors, nurses, pharmacy details, events and general information about the Healthcare. Users can interact with the Alexa tofind out the scheduled appointments, availability of the doctor, availability of the rooms, etc.
Effect of Pretreatment methods on Face Detection in Video Images

At present, face detection technology in video has attracted more and more attention, and its application areas are also very extensive, such as video surveillance, image detection, human-computer interaction, etc. However, the real-time and accuracy of face detection in the video environment are key issues that needs to be solved. In this paper, we preprocess differently frame images captured from video stream, then the AdaBoost face detection method is used to detect, along with tracking of Optical flow method, observe the influence of preprocessing methods on face detection. Thereby different pretreatment methods can be selected according to different detection environments to improve the accuracy of face detection.
PENERAPAN NOTE MAKING SKILL UNTUK MENINGKATKAN KEMAMPUAN MENYIMAK MAHASISWA PRODI PENDIDIKAN BAHASA INGGRIS FKIP UMSU

This study aims to improve the  listening skill of the second semester students Prodi English Education of FKIP UMSU by applying note making skills, and determine the extent of the increase in students learning outcomes in subjects Listening II after appliying Note making Skill. This research was conducted by using the method of Class Action Research (Class Action Research), and the result were analyzed by using descriptive quantitative and qualitative method to explain the observation of activities. The subjects were the students of the second semester, the class IIC-2, Prodi FKIP UMSU English Education, Academic year 2014/2015, totaling 33 people. The result showed that: (1) The  abilty  of students to record verbal  information needed appropriately increase. This is eviden from the increase in value of the average students 58.64 in pre-test I cycle I, being 74.70 in the post-test II, the second cycle with standart KKM = 70 (2) the result of the students’ learning showed a significant increase, which gained  100 % completeness study fulfilled within two cycles.  This improvement can also be seen from was the increase in the percentage mastery learning from 30.30% in pre test I cycle I, being 60,61% in post test I cycle II, and 100% in post test II cycle II with the standart learning completeness = 80% students passed.
I had an idea. Since you are ...

I had an idea. Since you are a published realistic fiction author why don't we work on an #OER around reading and writing historical fiction.
Pengembangan metode pembelajaran resitasi dan metode pembelajaran infocus untuk meningkatkan hasil belajar mahasiswa

This first year study aims to determine the effectiveness of learning using the Recitation Method compared to the Lecture Method, the Infocus Method compared to the Lecture Method, and the the Recitation Method compared to the Infocus Method. This study is quantitative research with a population of all active students of the Directorate of Postgraduate Edu-cation, UST Yogyakarta, amounting to 844 people. Members of the sample amounted to 107 people who were determined by the Purposive Sampling Method. Data analysis was carried out by the One Way Analysis of Variance and the Student Test Statistics. Requirements test of the analysis carried out is the Data Normality Test and the Variance Homogeneity Test. The results of this study are, in general there are differences in the effecti-veness of learning using the Recitation Method, the Infocus Method and the Lecture Method. In addition, on a case-by-case basis, the effectiveness of learning using the Recitation Method is higher than the Lecture Method, the Infocus Method is higher than the Lecture Method, and the Recitation Method is higher than the Infocus Method. That means the effectiveness of learning using the Recitation Method was higher than the other methods.
Distinguished Educator Talent Pool

PDF Version DATE: March 21, 2019 SUBJECT: Distinguished Educator Talent Pool CATEGORY: TAA & CAOs NEXT STEPS:
An approach to develop a smart and intelligent wheelchair

We live in a world, where the technology is growing to the next level every day. But it is very strange to see paralyzed people depending on someone's help for there mobility. In this project, we have developed a smart wheelchair which helps the completely paralyzed patient to move on their own. This is achieved by the voice control method by using an android application connected to the accelerometer. Another method is a hand gesture control method. In this method, we use the flex sensor to control the motion of the wheelchair. Hand gesture control can be used only by partially paralyzed patients. The Android-based voice control through the Bluetooth has been designed in the motor, the motor is controlled by the predesigned embedded C software.
Implementation of an Evolutionary Facial Recognition Algorithm on JETSON TK 1

This paper aims to contribute in visual computing over the implementation of face recognition algorithms on Jetson TK1.This powerful tool is a NVIDIA's embedded Linux development platform featuring a Tegra K1 SOC which contains a CPU, a GPU and an ISP in a single chip.The Tegra K1 'class one' is very faster than the former Tegra 2 'class two' and is the most efficient GPU in the ARM world.This particularity added to some optimizations we have made on implementation strategy and on recognition face algorithms conduct us to reach good results in real time systems RTS.
CITREX 2019 promotes innovative culture among young researchers

The Creation, Innovation, Technology and Research Exposition (CITREX) 2019 has entered into its ninth edition with Universiti Malaysia Pahang (UMP) seen as a platform that promotes and nurtures innovative culture among researchers, be it the academic staff or students.
12.5 kaththa plotting land on Budauli Bazar, Khairahani-05, Chitwan

Land For sale In Budauli Bazar, Ward No. 5, Khairahani Municipality, Chitwan, Pradesh 3 Nepal
Borgs&Schwarz Exceptional Convoy Escort - Traffic Infrastructure

We do the complete permission application exactly tailored to your special transport demands.
The Impacts of Territorial Communication Norms and Composition on Online Trolling

There is little research into online trolling on platforms with anonymity and geolocation features. On platforms such as Jodel, Whisper, and Yik Yak, anonymity may trigger online trolling and deviant behaviors, but geolocation features may hinder these behaviors through the imposition of territorial community norms and composition. Our study aims to address this gap through content analysis of 3,697 unique posts on Yik Yak, an anonymous geolocal platform that ceased to exist in 2017. Based on code co-occurrence, we found that trolling posts frequently include community-harming behaviors, such as insults, snark, and the use of vulgar language, and are more likely than other posts to include memes and vulgar language. We also found that territorial community events mediated the extent of community-building and community-harming behaviors, which increased or decreased on the platform according to changes in community composition context. Thus, we conclude that sociotechnical features of the platform in dynamic contexts affected online trolling behaviors by enabling and constraining manifestations of community-harming and community-building behaviors.
QUALITY ASSESSMENT OF THE EDUCATIONAL PROCESS OF GENERAL SECONDARY EDUCATION OF THE REPUBLIC OF BELARUS: CRITERIA BASIS

The quality of the educational process is considered here as a complex unity of substantive, procedural and effective components that are necessary and sufficient for achieving complex (pedagogical and socio-cultural) goals relevant to a particular stage of development of the national education system. The key parameters of the criteria for assessing the quality of the educational process of general secondary education include social and personal significance, realism, transparency and accessibility for assessment subjects, instrumentality and adaptability, adaptability, variable mobility, etc. Actually, the assessment of the quality of the educational process is considered as a multisubject, multidirectional and multidimensional activity.In accordance with this, a criterial basis is proposed for assessing the quality of the educational process of general secondary education.The system of criteria includes the positions of the educational itself (they are connected with the education, the formation of student subject and metasubject competences, preparation for professional self-determination, etc.) and sociocultural (associated with the fulfillment of the sociocultural order of society and the state, satisfaction of their expectations, including deferred).The proposed criteria differ in the nature of long-range actions: some of them are aimed at assessing the immediate, current and medium-term results of educational activities, while others are aimed at assessing the degree of achievement of strategic educational goals. This article focuses primarily on criteria of the first type; they are considered as indicators focused on assessing the quality of the educational process of general secondary education as a multi-vector activity for the provision of a set of relevant educational services. It is important to understand these educational services precisely as a complex, where the actual training and upbringing is combined with various types of sociocultural activity, the integral effect in the end should be the formation of a graduate ofthe school readiness for professional and personal self-determination, as well as an adequate level of sociocultural adaptability.The system of proposed integral evaluation criteria is aimed at the coordinated analysis of the conditions, the actual organization and implementation process, as well as the effectiveness and efficiency of the educational process. Along with the justification of the significance and novelty of a criterion for the contemporary system of education quality assessment, the most appropriatecontexts of its use by different subjects of evaluation (participants of the educational process) are determined.
Multiclass Classification Using Random Forest Classifier

A multiclass classification using Random Forest Classifier is proposed in this paper. The Random forest classifier is commonly used for solving the multiclass classification tasks in machine learning. The Random forest classifier predicts a valid classification results with minimum training time when compared to other classifier algorithms. For pattern classification tasks on an image dataset are performed in order to evaluate the performance of the proposed classifier. First, we consider some sample datasets of flower species and birds. Second, we train the object class models by using datasets to develop the random forest classifier for image classification. Third, we test the object class models and find the accuracy .In this we use Haralick,Hu moments to extract global features to quantify an image. In the experiments we test our method using FLOWERS-17,CUB_200_2011 dataset and compare the results with other methods like logistic regression, k-nearest neighbour, support vector machine.
Semantic Comparison of State-of-the-Art Deep Learning Methods for Image Multi-Label Classification.

Image understanding relies heavily on accurate multi-label classification. Inrecent years, deep learning (DL) algorithms have become very successful toolsfor multi-label classification of image objects, and various implementations ofDL algorithms have been released for public use in the form of applicationprogramming interfaces (APIs). In this study, we evaluate and compare 10 of themost prominent publicly available APIs in a best-of-breed challenge. Theevaluation is performed on the Visual Genome labeling benchmark dataset using12 well-recognized similarity metrics. In addition, for the first time in thiskind of comparison, we use a semantic similarity metric to evaluate thesemantic similarity performance of these APIs. In this evaluation, Microsoft'sComputer Vision, TensorFlow, Imagga, and IBM's Visual Recognition performedbetter than the other APIs. Furthermore, the new semantic similarity metricprovided deeper insights for comparison.
Σύγκριση μεταξύ των προγραμμάτων συστήματος διαχείρισης περιεχομένου wordpress και joomla με δημιουργία δυο ιστοτόπων

Creation of two (2) websites with the use of Content Management System (CMS), Wordpress and Joomla and comparing them in terms of design, implementation and operation.Specifically, the comparison includes: •Τhe installation way of each CMS and the review of each website’s database•Presentation of each CMS with extensive reference in services and peculiarities•Presentation of advantages and disadvantages of each CMS•Presentation of conclusions from the comparison of WordPress and Jooml
Pfeiffer Library: Open Resources: Selecting "Open" Materials

This guide walks users through the definition of open source and explains the various options for classroom use.
Content-Based Motorcycle Counting for Traffic Management by Image Recognition

Over the past few decades, advanced technologies have increased the number of vehicles, including cars and motorcycles. Because of the large increase of vehicles, the traffic flow becomes more complex and the traffic accidents increase as rapidly. To decrease the number of traffic accidents, a number of studies has been made for how to manage the traffic flow. Especially for motorcycles, in this paper, we propose a method that counts the motorcycles by Convolutional Neural Network (CNN). To reveal the effectiveness of the proposed method, a set of experiments were conducted and the experimental results show the proposed method can bring out a good performance that provides a good support for traffic management systems.
Photo Aesthetic Scoring Through Spatial Aggregation Perception DCNN on a New IDEA Dataset.

The aesthetic quality assessment of image is a challenging work in computer vision field. The recent research work used the deep convolutional neural network to evaluate the aesthetic quality of images. However, the score of image data sets has a strongly normal distribution, which makes the training of neural network easy to be over-fitting. In addition, traditional deep learning methods usually pre-process images, which destroy the original aesthetic features of the picture, so that the network can only learn some superficial aesthetic features. This paper presents a new data set what images distributed evenly for aesthetics (IDEA). This data set has less statistical characteristics, which is helpful for the neural network to learn the deeper features. We propose a new spatial aggregation perception neural network architecture which can control channel weights automatically. The advantages and effectiveness of our method are proved by experiments in different data sets.
Application of local angle domain diffraction imaging

Preview this conference paper: Application of local angle domain diffraction imaging, Page 1 of 1 < Previous page | Next page > /docserver/preview/fulltext/2214-4609/2019/POS10-1.gif
An Adaptive Iterative Algorithm for Motion Deblurring Based on Salient Intensity Prior

In this paper, an adaptive iterative algorithm is proposed for motion deblurring by using the salient intensity prior.Based on the observation that the salient intensity of the clear image is sparse, and the salient intensity of the blurred image is less sparse during the image blurring process.The salient intensity prior is proposed to enforce the sparsity of the distribution of the saliency in the latent image, which guides the blind deblurring in various scenarios.Furthermore, an adaptive iteration strategy is proposed to adjust the number of iterations by evaluating the performance of the latent image and the similarity of the estimated blur kernel.The negative influence of overabundant iterations in each scale is effectively restrained in this way.Experiments on publicly available image deblurring datasets demonstrate that the proposed algorithm achieves state-of-the-art deblurring results with small computational costs.
Software Effort Estimation Techniques

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Study and Comparative Analysis of Existing Recommender Systems

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.