Reviewerly/exHarmony huggingface dataset:
Performance Assessment of Various Encoding Schemes with Bit Stuffing

This paper discusses the implementation of a novel technique of encoding data bits using the concept of bit stuffing in addition to the conventional methods of source coding. This technique can be applied to any of the existing methods of source encoding under controlled conditions. In particular, the method is very efficient when the encoded bits have more number of ones or zeros than a predefined threshold, at any point of time and in any part of the stream. Usually, bit stuffing is a common method used for data compression in data communication layers to reduce the bandwidth. In this paper, we have attempted to incorporate bit stuffing in various encoding schemes and have compared the improvement in performance with and without bit stuffing. The software used for simulation is MATLAB. The primary motivation of this work is to determine the maximum amount of bandwidth savings that can be achieved due to bit stuffing for a random series of alphabets.
An Efficient Vector Quantization Based Image Compression using Fruit Fly Algorithm

Image compression is a searing research topic because of the large-scale increase in multimedia applications. The goal of the image compression is not only to reduce the quantity of bits needed to represent the images but also to get used to the image quality in accordance with the users’ requirements. The existing methodology CSGRVQ is evaluated by the performance of the parameter. Fruity Fly (FF) optimization algorithm proposed to further improving the FF-GRVQ. Extensive experiment demonstrates our proposed FF-GRVQ algorithm outperforms existing algorithm in term of quantization accuracy and computation accuracy.
Data Analysis of Educational Websites Using RapidMiner

With an exponential increase in the World Wide Web's size, collecting precise information which satisfies particular requirements is a challenge, especially when time is an entity of great importance leading to demand efficiency. In this paper, RapidMiner is used to collect information from educational websites. Collected data is analyzed and visualizations of data is created to evaluate it.
Incentive Compatible Active Learning.

We consider active learning under incentive compatibility constraints. The main application of our results is to economic experiments, in which a learner seeks to infer the parameters of a subject’s preferences: for example their attitudes towards risk, or their beliefs over uncertain events. By cleverly adapting the experimental design, one can save on the time spent by subjects in the laboratory, or maximize the information obtained from each subject in a given laboratory session; but the resulting adaptive design raises complications due to incentive compatibility. A subject in the lab may answer questions strategically, and not truthfully, so as to steer subsequent questions in a profitable direction.We analyze two standard economic problems: inference of preferences over risk from multiple price lists, and belief elicitation in experiments on choice over uncertainty. In the first setting, we tune a simple and fast learning algorithm to retain certain incentive compatibility properties. In the second setting, we provide an incentive compatible learning algorithm based on scoring rules with query complexity that differs from obvious methods of achieving fast learning rates only by subpolynomial factors. Thus, for these areas of application, incentive compatibility may be achieved without paying a large sample complexity price.
Students’ English Problems in Writing Thesis Proposal at Program Khusus Ulama (PKU) in Academic Year 2019/2020

Research proposal is an activity that will take place in the form of writing in systematic and detailed, proposal made to get approval from others. The thesis proposal is an outline of the research work that we plan to do in our thesis or dissertation. The thesis proposal is also summary that details an outline of our work. It identifies a problem that we are researching, clearly states all the questions that will be researched as well as describes that resources and material that we need. The purpose of this solve was to find out the students’ problems in writing thesis proposal at Program Khusus Ulama (PKU) and how can they solve the problems. This research was qualitative descriptive research. The subject of the research was the six student participants at Program Khusus Ulama (PKU). The object of the research was the thesis proposal. The result of this research indicates that there were student problems the students encountered in writing a thesis proposal. the problems were grammatical, especially the tenses usage, spelling, vocabulary, punctuation and conjunction. The students solve their problem in writing thesis proposal by doing Google translate, Google drive, dictionary, English literature and ask lectures also their friends. The solution is really helpful for them in learning English. Mainly writing proposal Program Khusus Ulama (PKU).
Real Image Reproduction Algorithm Based on Sigmoid-iCAM Color Model

Aiming at the characteristics of color prediction and color matching in color appearance model, a vision local adaptation mechanism based on Sigmoid function of artificial neural network is introduced on the basis of iCAM color appearance model, and a real image reproduction algorithm based on Sigmoid-iCAM color appearance model is proposed. Compared with the real image reproduction algorithm based on CIECAM02 and iCAM color model, this algorithm can effectively improve the image contrast and local details while restoring the color of tone-distorted image.
EVALUASI KEMAMPUAN DAYA DUKUNG SALURAN DRAINASE PERKOTAAN

Flood is a natural phenomena which are related to the amount of damage in terms of life and material. The small drainage capacity and the amount of sediment in the drainage causing flooding at Jl. K.H. Agus Salim Kelurahan Selumit Kota Tarakan. The data needed in this study is partial series daily rainfall data from Meteorology, Climatology, and Geophysics Tarakan. Rainfall data we tested with Abnormal Test, Smirnov-Kolmogorov and Chi Square and analysis with Log Pearson III. Rainfall data is then applied to the hourly rainfall intensity mononobe method. The intensity of rain is useful to calculate the peak water discharge. Based on the study, the drainage is not able to accommodate the entire volume of water during rainfall that occurs, the calculation of the existing drainage capacity (Qe) is 0.45 m/sec with water discharge plan (Qh) is 2.13 m/sec
Rotating invariant face detection via cascaded networks and pyramidal optical flows

In the unconstrained open-space, face detection is still a challenging task due to the facial posture changes, complex background environment, and motion blur. The rotation-invariant algorithm based on cascaded network and pyramid optical flow is proposed. Firstly, the cascading progressive convolutional neural network is adopted to locate the face position and facial landmark of the previous frame in the video stream. Secondly, the independent facial landmark detection network is used to reposition the current frame, and the optical flow mapping displacement of the facial landmark between the two frames is calculated afterwards. Finally, the detected face is corrected by the mapping relationship between the optical flow displacement of the facial landmark and the bounding box, thereby completing the rotation-invariant face detection. The experiment was tested on the FDDB public datasets, which proved that the method is more accurate. Moreover, the dynamic test on the Boston head tracking database proves that the face detection algorithm can effectively solve the problem of rotation-invariant face detection. Compared with other detection algorithms, the detection speed of the proposed algorithm has a great advantage, and the window jitter problem in the video is well solved.
Text Mining Technique for Driving Potentially Valuable Information from Text

With the growing number of digitized documents and having large text databases, text mining will become increasingly important.Text mining can be a huge benefit for finding relevant and desired text data from unstructured data sources.Text Mining is the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources.It is an important step of Knowledge Discovery process.The aim of the paper is to study the concept of Text Mining and various techniques with a particular focus on text mining process.In the text mining community have been trying to apply many methods such as rule-based, knowledge based, statistical and machine-learning-based approaches.Finally, the paper discusses issues towards the techniques for driving potentially valuable information from text and also, discuss on integration data mining.The paper ends with conclusion and the future line of works in the combining text mining and data mining techniques into a single system, a combination known as duo-mining, and also be more effective text mining techniques for contextual extraction.
Improving DR outcomes through comprehensive medical management

Diabetes currently afflicts more than 30 million Americans (about 9.4% of the population). The American Diabetes Association estimates that more than seven million people are not even aware that they have this debilitating disease.
A Research on ICT Curriculum Co-construction under the Framework of School-enterprise Cooperation

The rapid changes in ICT technology have made it necessary for industry talents to constantly adapt to technology updates, and meanwhile, continuous integration and collaboration of business further strengthen the comprehensive requirements for talents. Application-oriented colleges and universities guided by vocational needs and based on engineering scene, need to carry out teaching design, aiming at developing professional job skills in line with market demand. The core content of the curriculum co-construction of school-enterprise cooperation includes the construction of practical talent training system, related standard of education and teaching, faculties of â€œdual abilitiesâ€, high-level practice base, certification training as well as curriculum and employment docking platform. During this process, enterprises can help colleges and universities create application-oriented curricula and promote the deep curriculum transformation of colleges and universities in talent training, professional teaching, quality education and human resource service with the close connection between professional education and regional industry development, in order to achieve the ultimate goal of industry-teaching integration.
Penerapan Model Fan-N-Pick dan Inside-Outside Circle untuk Meningkatkan Keterampilan Sosial dan Hasil Belajar Siswa Kelas IV Sekolah Dasar

&lt;pre&gt;&lt;strong&gt;Abstract:&lt;em&gt; &lt;/em&gt;&lt;/strong&gt;The purpose of the study is to describe the application of the model FNP and IOC to improve the social skills and the learning outcomes of student class IV SDN 3 Besuki. Type of this research was PTK that includes two cycles. Research was conducted at SDN 3 Besuki, the subjectof this research is the students of class IV SDN 3 Besuki amounted to 32 people. Data collection: observation, interview, test, questionnaire, and documentation. The techniques of data analysis: reduction, data presentation and conclusion. The result of this research shows that the increased in social skills and the students learning outcomes in cycle I with a good criteria and increased to very good on the cycle II. The increase also occurred in the implementation of learning by teachers and students on the each cycle. &lt;/pre&gt;&lt;strong&gt;Abstrak:&lt;/strong&gt; Tujuan penelitian ini untuk mendeskripsikan penerapan model &lt;em&gt;F&lt;/em&gt;&lt;em&gt;NP &lt;/em&gt;dan &lt;em&gt;IOC &lt;/em&gt;untuk meningkatkan keterampilan sosial dan hasil belajar siswa kelas IV SDN 3 Besuki. Jenis penelitian PTK meliputi dua siklus&lt;em&gt;. &lt;/em&gt;Penelitian dilakukan di SDN 3 Besuki, subjek penelitian siswa kelas IV berjumlah 32 orang. Pengumpulan data, meliputi observasi, wawancara, tes, angket, dan dokumentasi. Teknik analisis data, meliputi reduksi, penyajian data, dan penarikan kesimpulan. Hasil pemelitian menunjukkan terjadinya peningkatan keteranpilan sosial dan hasil belajar siswa siklus I dengan kriteria baik dan meningkat menjadi sangat baik pada siklus II. Peningkatan juga terjadi pada pelaksanaan pembelajaran oleh guru dan siswa pada masing-masing siklus.
Subject Guides: The End of EndNote Desktop : Transfering to Mendeley

AU Library will be canceling our subscription to EndNote Desktop in May 2021. This guide will help EndNote users determine how best to move forward and will include details on maintaining access to the current version of EndNote, as well as how to chose w
Method and Research on Automatic Generation and Fluency Discrimination of Movie Word Sequence Based on NNLM

In the context of massive information on the Internet, how to automatically generate word sequence statements based on words and make them compliant is crucial. In this paper, the neural network language model (NNLM) is used to judge the automatically generated Chinese movie title sentence, and the highest probability value in the data set is obtained, that is, the top 10 statements with the best fluency. At the same time, the N-Gram algorithm is used for screening, and the screening results are compared with the results of NNLM. After professional evaluation and analysis, the discriminant result of NNLM algorithm is better. However, in the real-time discriminating scene, the computational complexity of the NNLM algorithm is much larger than that of the N-Gram algorithm, so it needs to be considered after comprehensive consideration.
Fast Multiple Pattern Cartesian Tree Matching

Cartesian tree matching is the problem of finding all substrings in a given text which have the same Cartesian trees as that of a given pattern. In this paper, we deal with Cartesian tree matching for the case of multiple patterns. We present two fingerprinting methods, i.e., the parent-distance encoding and the binary encoding. By combining an efficient fingerprinting method and a conventional multiple string matching algorithm, we can efficiently solve multiple pattern Cartesian tree matching. We propose three practical algorithms for multiple pattern Cartesian tree matching based on the Wu-Manber algorithm, the Rabin-Karp algorithm, and the Alpha Skip Search algorithm, respectively. In the experiments we compare our solutions against the previous algorithm [18]. Our solutions run faster than the previous algorithm as the pattern lengths increase. Especially, our algorithm based on Wu-Manber runs up to 33 times faster.
Rajasthan medical library consortium: A proposed model

The emergence of electronic formats of publishing has resulted in to the formation of library consortia for resource sharing among the member libraries on economic basis. Various types of library consortia are formed in the recent past; such as CeRA, NKRC and E-Shodhsindhu. But no library consortium seems to be working in the field of medical science except that ERMED. Thus, an idea for forming a medical library consortium for Rajasthan state is floated in this paper.
A Semantic Image Retrieval Technique Through Concept Co-occurrence Based Database Organization and DeepLab Segmentation

In this paper, a semantic image retrieval technique that efficiently depicts users' perspective is proposed.It primarily aims in the representation of contextual diversity of the user through a high level semantic segmentation technique called DeepLab-V3+.An online user interactive step is also included during the retrieval process.The significance of intra-concept variation in image retrieval is clearly presented in this paper.An efficient database organization, which forms the essence of the retrieval methodology, based on concept co-occurrence and inter-concept distance is also proposed.ResNet-101 CNN features extracted from the regions are utilized in classification and retrieval tasks.The simulation results and performance analysis conducted on PASCAL VOC2012 and SUN '09 datasets depict the superiority of the proposed technique over other approaches.
Stereoscopic view image generation algorithm based on surface projection of object coordinate system

In this paper, a surface projection image stitching algorithm based on object coordinate system is proposed to generate stereoscopic image, which can be applied to virtual reality and vehicle assisted driving. According to the actual application, a suitable 3D model is established, and the image is mapped based on the object coordinate system. The 3D model is divided into fusion and non-fusion regions, and the original image is mapped to the non-fusion region. For the stitching region, combined with the model features, a weighted average fusion algorithm based on angle information is designed to correct the color of the stitched image to eliminate uneven illumination and brightness. The experimental results show that the stereoscopic image generated by this method can display the surrounding environment of the car body in a stereoscopic manner, with high image stitching accuracy and good visual effect.
LibGuides: Hot Topics: Immigration: Websites

Immigration involves moving to a new country with the intention of settling there permanently after leaving one's country of citizenship. The United States has more immigrants than any other country in the world. Today, more than 40 million people living
CNN-based leukocyte detection for microscopy imaging at 10x magnification objective lens

Examination of peripheral blood smears by light microscopy helps to provide valuable information for disease diagnosis, but remains one of the major labor-intensive procedures in hematology laboratory. As a key part of white blood cell morphology examination, leukocyte detection at 10&times; magnification objective lens is considered as small object detection problem in this paper. After establishing leukocyte dataset at 10&times; magnification objective lens, we design a classification-based two-stage approach to this challenging problem. Stage one generates proposals by pixellevel ANN pipeline based on the color and size of leukocyte. Stage two is responsible for proposal classification task by CNN architecture. Extensive experiments are carried out to prove its effectiveness for peripheral blood samples. Experimental results demonstrate that the proposed classification-based approach, obtains a desired precision of 94.69%, recall of 95.73%, accuracy of 90.85% and F<sub>&beta;</sub> of 0.96. The data is available at https://doi.org/10.6084/m9.figshare.9037370.v1.
Surface loss for medical image segmentation

Last decades have witnessed an unprecedented expansion of medical data in various largescale and complex systems. While achieving a lot of successes in many complex medical problems, there are still some challenges to deal with. Class imbalance is one of the common problems of medical image segmentation. It occurs mostly when there is a severely unequal class distribution, for instance, when the size of target foreground region is several orders of magnitude less that the background region size. In such problems, typical loss functions used for convolutional neural networks (CNN) segmentation fail to deliver good performances.Widely used losses,e.g., Dice or cross-entropy, are based on regional terms. They assume that all classes are equally distributed. Thus, they tend to favor the majority class and misclassify the target class. To address this issue, the main objective of this work is to build a boundary loss, a distance based measure on the space of contours and not regions. We argue that a boundary loss can mitigate the problems of regional losses via introducing a complementary distance-based information. Our loss is inspired by discrete (graph-based) optimization techniques for computing gradient flows of curve evolution.Following an integral approach for computing boundary variations, we express a non-symmetric L2 distance on the space of shapes as a regional integral, which avoids completely local differential computations. Our boundary loss is the sum of linear functions of the regional softmax probability outputs of the network. Therefore, it can easily be combined with standard regional losses and implemented with any existing deep network architecture for N-dimensional segmentation (N-D).Experiments were carried on three benchmark datasets corresponding to increasingly unbalanced segmentation problems: Multi modal brain tumor segmentation (BRATS17), the ischemic stroke lesion (ISLES) and white matter hyperintensities (WMH). Used in conjunction with the region-based generalized Dice loss (GDL), our boundary loss improves performance significantly compared to GDL alone, reaching up to 8% improvement in Dice score and 10% improvement in Hausdorff score. It also yielded a more stable learning process.
LibGuides: University of Vaasa writing guidelines: Support for writing

The guidelines contain instructions about the layout and contents of theses and other written assignments as well as instructions on how to refer to source literature and other material used in the work.
EDUCATION AND TECHNOLOGY: DESIGNING NEW HORIZONS WITH LITERACIES

Modern society has created a profound and compelling need to (re)think the universes of Education and Pedagogy, namely with the incorporation of Literacies into the teaching-learning process. As a result of technological advances, societal mutations and new information skills, there is a need to harmonize Education and Technology in order to enhance teachers at all levels of education, including Higher Education, to respond appropriately to these technological challenges and to the deeply embedded students in this ocean of technology and permanent change. The great challenges of Education on the horizon for 2030 are clearly focused on acquiring the skills to understand and decode the world, launch ready-made layouts and activate critical thinking for more fruitful understanding of the contemporary ideas, spaces and times, values and key issues like citizenship, as referred to in the OECD report on the future of education and skills. This is the reason why UNESCO (2013) supports the essential contribution of teachers to ensuring that all citizens can access information, as literate citizens and contribute to sustainable development goals, better living conditions, employment, per capita income, industrialization and land infrastructure development. Thus, it is important to recognize Literacies as sources and strategies to understand our world through a pluralistic approach to multiliteracies, taking into account the context, level of education and area of ​​scientific teaching and research, and always connecting Education and Technology.
LibGuides: Project Planning for the Beginner: Developing a Researchable Question

This Sage Research Methods tool is designed for the first time researcher to guide you through your research project. Developing research questions that are new