Reviewerly/exHarmony huggingface dataset:
Taking the Long Way Around: Improving the Display of HathiTrust Records in Primo

As with any shared format for serializing data, Primo’s PNX records have limits on the types of data which they pass along from the source records and into the Primo tool. As a result of these limitations, PNX records do not currently have a provision for harvesting and transferring rights information about HathiTrust holdings that the Kansas State University (KSU) Library system indexes through Primo. This created a problem, since Primo was defaulting to indicate that all HathiTrust materials were available to KSU Libraries (K-State Libraries) patrons, when only a limited portion of them actually were. This disconnect was infuriating some library users, and creating difficulties for the public services librarians. There was a library-wide discussion about removing HathiTrust holdings from Primo altogether, but it was decided that such a solution was an overreaction. As a consequence, the library IT department began a crash program to attempt to find a solution to the problem. The result was an application called hathiGenius.
Self-Assessment of Russian Students’ Social Resistance

Introduction. The problem of assessment and enhancement of social resistance of the Russian students is dealt with in the article. It focuses on the influence of a number of factors on the enhancement of social resistance among students under modern conditions. The authors give the first ever quantitative assessment of social resistance of students of higher education institutions in Russia. The purpose of the article is to examine the results of a study on the formation of social sustainability of students, to conduct on this basis an assessment of its level, to summarize the experience of developing and using special educational technologies that increase social sustainability and students' readiness for future professional activities. Materials and Methods. The following methods are used: questioning, expert poll, comparison, decomposition, and the group analysis. Data from more than 40 domestic and foreign sources are analyzed. The study population included students of Russian typical regional universities, the sampling totality comprised 400 students of 13 state-financed universities from 5 federal districts of the Russian Federation. The study also involved 36 skilled experts. Results. The research broadened the comprehension of the role and importance of the enhancement of student social resistance using special educational technologies. The coefficient of social resistance of Russian students (0.36) is not high enough. Also, the study revealed that for 50 % students the need of personal and professional development for successful employment in the futur e was a priority. Discussion and Conclusion. Conclusions are drawn concerning the need to realize the system of dedicated measures directed to increase the social resistance of the Russian students. The paper addresses students and teaching staff of Russian higher schools, education authorities as well as scientists studying problems of students’ evolvement.
Marketing and Promotion of E-journal in Academic Libraries in Tanzania

This paper examines promotion and marketing strategies used by academic libraries in Tanzania to make users aware of the availability of e-resources.To collect data, this study used survey.Data were analyzed using an Independent T-Test and One-Way MANOVA using SPSS Version 16.Documentary review of secondary data related to the study was done.Major findings of the study revealed that e-journals are being used in Universities and Colleges in Tanzania despite the various challenges.Various marketing strategies such as use of OPAC, the Web 2.0 and others were used for informing users about a range of available e-resources in academic libraries and thus promoting their access and use.Finally, the recommendations for enhancing the marketing of e-resources are given.
The Tamunier gold deposit in the Northern Ural: Physicochemical formative conditions, ore and fluid sources, genesis

Research subject. This research study was aimed at investigating metasomatic minerals and ores in the Tamunier Deposit, which is located in the Northern Urals, at the Eastern side of the Tagil megazone within the Auerbach volcano-plutonic belt. Materials and methods. Well core samples were investigated using a complex of research methods, including optical and electron microscopy, X-ray spectral microanalysis, mineral geothermometry, thermobarogeochemistry (microthermometry, gas chromatography, determination of the salt composition of fluid inclusions in minerals) and isotope geochemistry (isotopes C, O, S, Sr, Pb). Results . A genetic model describing the formation of the Tamunier deposit was developed using the data obtained on its geological structure, mineral composition of metasomatites and ores, fluid formation mode, sources of ore matter and ore-bearing fluid. In the proposed model, the magmatogenic sodium chloride fluid carrying ore components and S is separated from the Auerbach complex at the depth of intrusion. Penetrating to the surface, this fluid interacts with the rocks of volcanic-sedimentary strata, thereby extracting a number of components, including CO2, S and Sr. Conclusion . Despite the presence of sulphide mineralization of hydrothermal-sedimentary genesis in the volcanogenic-sedimentary rock mass, the data obtained has allowed us to refer the gold-sulphide ores under study to magmatogenic-hydrothermal formations. The estimated P-T conditions ( t = 100–370ºС and P = 0.4–0.6 kbar) and the shallow depth of the Tamunier field have shown its correspondence to the sub-epithermal level in the model of the porphyry-epithermal ore-magmatic system.
A Split-Merge Evolutionary Clustering Algorithm

In this article we propose a bipartite correlation clustering technique that can be used to adapt the existing clustering solution to a clustering of newly collected data elements. The proposed tec ...
Phase measuring method and error compensation in 3D profile measurement

3D profile measurement is widely used in many areas such as manufacturing, computer-aided design, virtual reality and medical diagnostics. As one of the core technologies in 3D profile measurement, digital fringe pattern projection is a highly sensitive noncontact technique for obtaining the 3D shape of an object. Then the grating pattern deformed by the measured object is captured by CCD cameras and decoded using appropriate algorithms so that the shape of the object can be deduced. In this paper, three sets of phase shift fringe patterns with different frequencies are projected on the surface of the measured object by a DLP projector and the deformed patterns are captured by two cameras. Then the four-step phase shift method is used to obtain the three groups of fringe patterns phases, and the three-frequency heterodyne method is adopted to unwrap the phase and obtain the absolute phase. The causes of the phase errors are analyzed and the subsequent compensation method of gamma correction of grating pattern is proposed to eliminate the main errors. Experiments are carried out and the results verify the accuracy and effectiveness of the proposed methods.
Text-based Medical Image Retrieval using Convolutional Neural Network and Speciﬁc Medical Features

With the proliferation of digital imaging data in hospitals, the amount of medical images is increasing rapidly. Thus, the need for efficient retrieval systems, to find relevant information from large medical datasets, becomes high. The Convolutional Neural Network (CNN)-based models have been proved to be effective in several areas including, for example, medical image retrieval. Moreover, the Text-Based Image Retrieval (TBIR) was successful in retrieving images with textual description. However, in TBIR, all queries and documents are processed without taking into account the influence of certain medical terminologies (Specific Medical Features (SMF)) on the retrieval performance. In this paper, we propose a re-ranking method using the CNN and the SMF for text-medical image retrieval. First, images (documents) and queries are indexed to specific medical image features. Second, the Word2vec tool is used to construct feature vectors for both documents and queries. These vectors are then integrated into a neural network process and a matching function is used to re-rank documents obtained initially by a classical retrieval model. To evaluate our approach, several experiments are carried out with Medical ImageCLEF datasets from 2009 to 2012. Results show that our proposed approach significantly enhances image retrieval performance compared to several state of the art models.
Automatic Knowledge Discovery in Lecturing Videos via Deep Representation

In recent years, e-learning systems such as massive open online courses (MOOC) have been widely employed in academic institutions and have shown its power in enhancing the students' learning ability.Automatic detection and classification of knowledge points in lecture video would significantly enhance the performance of the online learning platform.Most of the previously presented approach for knowledge discovery focused on the text and audio documents, whereas the identification of knowledge points in videos still remains a challenge.To bridge this gap, we proposed a novel convolutional neural network which was designed for the characteristics of lecture video.It could both extract the temporalspatial and semantic information from the multimedia record.To evaluate the performance of the proposed technique, we conducted comparison experiments between the state-of-the-art methods and ours.The experimental results demonstrated that the presented approach outperformed the state-of-the-art techniques and could be potentially invaluable for the accurate discovery of knowledge points within videos.
Alignment of the initial phase during multiple-wavelength switching in microscopic interferometry

Surface morphology measurement based on multiple wavelengths interferometric theory has been widely used, and the alignment error of initial phase of different wavelengths can influence the measurement accuracy. A phase shift method to drive the piezoelectric transducer (PZT) by zigzag with a fallback path is proposed, which can overcome the hysteresis and creep behavior of the PZT before switching to different wavelengths. The ellipse fitting and unwrapping algorithms are applied to extract phase-shifts from interferograms. The starting points of different wavelengths are aligned according to the displacement and movement direction of PZT. The experimental results show that the presented method can improve the aligned accuracy of the initial position during multiple-wavelength microscopic interferometry measurement.
Research of the image restoration algorithm based on boundary pre-processing in the space domain and fast computing in the frequency domain

On a high power solid laser facility, the wavefront coding (WFC) technology has been adopted to obtain 3m-13m over-long depth of field in an array optical components defect detection system[1]; The lack of the boundary information due to the sudden boundary truncation will cause the ringing effect in the image restoration process. By using the theory of the boundary condition s(BCs), an image enlarged by the different boundary hypothesis can be given; The frequency filtering has been used to find the restored result. The frequency property of the enlarged image and the effect to the boundary of the restored image are analyzed. Effectiveness and speediness of the proposed method are demonstrated by experiment results, which can give excellent deconvolution and noise suppression restored image and reduce the boundary ringing effect under the reflective boundary conditions in a wave-front coding (WFC) system. The experiment shows the proposed algorithm can give satisfactory restoration results on the long depth of field array optical components defect detection system[1] .
Handwritten Arabic Numeral Character Recognition Using Multi Kernel Support Vector Machine

Handwritten recognition is how computer can identify a handwritten character or letter from a document, an image or another source. Recently, many devices provide a feature using handwritten as an input such as laptops, smartphones, and others, affecting handwritten recognition abilities become important thing. As the mother tongue of Muslims, and the only language used in holy book Al Qur’an, therefore recognizing in arabic character is a challenging task. The outcome of that recognizing system has to be quite accurate, the results of the process will impact on the entire process of understanding the Qur’an lesson. Basically handwritten recognition problem is part of classification problem and one of the best algorithm to solve it is Support Vector Machine (SVM). By finding a best separate line and two other support lines between input space data in process of training, SVM can provide the better result than other classify algorithm. Although SVM can solve the classify problem well, SVM must be modified with kernel learning method to be able to classify nonlinear data. However, determining the best kernel for every classification problem is quite difficult. Therefore, some technique have been developed, one of them is Multi Kernel Learning (MKL). This technique works by combining some kernel function to be one kernel with an equation. This framework built an application to recognize handwritten arabic numeral character using SVM algorithm that modified with Kernel Learning Method. The result shows that the application can recognize data well with average value of Accuracy is 84,37%
Warak Ngendhog Commodification as a Kind of Creative Industry in Semarang City

&lt;p class="Default"&gt;&lt;em&gt;Warak Ngendhog in Semarang City make it a cultural phenomenon. Some forms of commodification are used in the economic, political and cultural sectors. The purpose of this study is to find out the symptoms of the cultural phenomenon which has transformed into various forms. This research use qualitative analysis with descriptive approach. As for the results of this study, Warak Ngendhog which functions has transformed and changed, can be utilized in the cultural and tourism sectors as one of the cultural icons in the city of Semarang. Warak Ngendhog culture has contributed to the government of Semarang City with the emergence of various forms of its transformation into various forms of art and culture. In addition, this study is expected to give contribution in the field of cultural preservation in Semarang City.&lt;/em&gt;&lt;/p&gt;
Automatic Eyeglasses Replacement for a 3D Virtual Try-on System

This paper presents a 3D virtual eyeglasses try-on system for practical use. For fitting eyeglasses in a shop, consumers wish to look at themselves in a mirror while trying on various eyeglass styles. However, for people who need to wear eyeglasses for correcting problems with eyesight, it is impossible for them to clearly observe their face in the mirror without wearing eyeglasses. This makes fitting them for new eyeglasses difficult. This research proposes a virtual try-on system that can be used while wearing eyeglasses. We replace the user's eyeglasses in the input video with new eyeglasses virtually. Moreover, a fast and accurate face tracking tool enables our system to automatically display 3D virtual glasses following a user's head motion. Experimental results demonstrate that the proposed method can render virtual glasses naturally while the user is wearing real eyeglasses.
Mammography Images Segmentation Based on Fuzzy Set and Thresholding

Breast cancer is the most widespread cancer that influences ladies about the world. Early recognition of breast tumor is a standout amongst the hugest variables influencing the probability of recuperation from the illness. Hence, mammography remains the most precise and best device for distinguishing breast malignancy.&#x0D; This paper presents a method for segment the boundary of breast masses regions in mammograms via a proposed algorithm based on fuzzy set techniques. Firstly, it was used data set (mini-MIAS) for evaluate algorithm. it was preprocessing the data set to remove noise and propose a fuzzy set by using fuzzy inference system by generated two input parameters (employs image gradient), then used thresholding filter. Then it was evaluated this proposed method, qualitative and quantitative results were obtained to demonstrate the efficiency of this method and confirm the possibility of its use in improving the diagnosis.
Pedestrian Detection in Unmanned Aerial Vehicle Scene

With the increasing adoption of unmanned aerial vehicles (UAVs), pedestrian detection with use of such vehicles has been attracting attention. Object detection algorithms based on deep learning have considerably progressed in recent years, but applying existing research results directly to the UAV perspective is difficult. Therefore, in this study, we present a new dataset called UAVs-Pedestrian, which contains various scenes and angles, for improving test results. To validate our dataset, we use the classical detection algorithms SSD, YOLO, and Faster-RCNN. Findings indicate that our dataset is challenging and conducive to the study of pedestrian detection using UAVs.
Recipes, Plans, Instructions, and the Free Speech Implications of Words That Are Tools

This chapter investigates whether speech acts of urging, advising, recommending, instructing, and informing ought all to be treated in the same way for purposes of implementing a principle of freedom of speech, and asks: If not, how do we justify treating them differently? This problem is arguably more pressing than it has been in the past, as the internet and various forms of social media have seemingly caused the mass distribution of instructions for committing antisocial acts have proliferated. After discussion of examples of publications that allow the reader to acquire knowledge on how to engage in dangerous activities, the chapter concludes that the normative and philosophical questions about the relationship between freedom of speech and the provision of instructions, plans, recipes, and detailed facts are in the final analysis less philosophical than they are empirical and social scientific.
Psychological Analysis of Specialists of the Institute for Leadership Development (National Technology Initiative): Training of Entrepreneurs of Technological Startups

The paper presents the results of a comprehensive psychological study of the professional network community of the Institute for the development of leaders as a strategic initiative, “Agency for strategic initiatives to promote new projects” (ASI). Based on its results, the authors attempt to formalize and justify the psychological determinants of personality, the purposeful impact and education of the younger generation, nudge and the correction of “mature” entrepreneurs will directly affect their personal growth, correspond to their individual development path, activate the activity “under the flag” of the National technology initiative (NTI) and the strategy of national technological development (NTD). The article presents the results of the study of individual psychological indicators of the professional community representatives of the Institute for Leadership Development ASI. Only representatives of the russian technological elite can be the main drivers of socio-economic growth of the national economy in the next 5–10–20 years. The Government of the Russian Federation has relied on the development of science and technology in its development Strategy.
Improvement of Character Recognition for Parts Book Using Pre-processing of Deep Learning

An OCR(Optical Character Recognition) based on deep learning for recognition of characters and numbers on drawings for machine maintenance, is proposed. The proposed pre-processing uses mathematical morphology operation to reduce false detection and recognition due to the leading lines and small parts of the drawings. The LSTM model is used to train and infer drawings of parts book. The results of experiments show that the proposed OCR improves the performance by 6.95 % compared to the classical LSTM In addition, the processing speed is improved compared to the conventional approaches.
Text Analytics: The Dark Data Frontier

Text is everywhere. Analysts at Gartner estimate that upward of 80 percent of enterprise data today is unstructured. Our everyday interactions generate torrents of such data, including tweets, blog posts, advertisements, news, articles, research papers, descriptions, emails, YouTube comments, Yelp reviews, surveys from your insurance company, and call transcripts; there is a tremendous amount of unstructured data, and the majority of it is text. Another general way to describe this large amount of mostly monetizable data (except YouTube comments—those are toxic!) is by classifying it as dark data. The origin of this term is not well known, but it was popularized by Stanford’s Dr. Chris Re, who founded the DeepDive program for extracting valuable information from dark data. The term pertains to the mountains of raw information collected in various ways, and such data remains difficult to analyze.
Investigating the Relationship Between SLOC and Logical Database Measures to Improve the Early Estimation of Software Cost

Project planning is a critical activity in the software development life cycle. At the early stages of a project, the managers need to estimate required time, effort and cost to plan, track and then to deliver the project successfully. Many studies have attempted to provide methods for precise software cost estimation. The current software cost estimation methods are mainly based on software size estimation and functional system requirements. The main assumption of this study is that, as the primary source of complexity in today’s software is the interaction between the database and the user, database measures may provide inputs allowing current software estimation methods to achieve more accurate results. Accordingly, this study attempts to gain insights from objective measures, collected through the logical database model of software systems, for better prediction of the software’s effort and hence cost through software lines of code (SLOC) measure. For this purpose, more than 2.5 million lines of code developed by four different companies, for 79 different software packages with their related database design measures, are analyzed. The results of this study show that there is a close correlation between the software size and database design measure, namely, the number of tables which can be collected at the logical database design stage. By adapting this result, the current estimation models could be improved significantly.
Assessing Privileged Access Management (PAM) using ISO 27001:2013 Control

ISO 27001 is one of the most widely adopted and respected information security standards in use today. It is promulgated by the International Standards Organization (ISO). Many organizations seek to be certified for the standard, which provides a framework for implementing an Information Security Management System (ISMS). The standard touches on virtually every aspect of information security. Access controls - including Privileged Access Management (PAM), thus figure prominently into the ISO 27001 certification and audit processes. In order to manage their privileged accounts, organization should be use PAM to protect critical IT assets, meet the compliance regulation and to prevent data breaches. But unfortunately many organizations do not have enough knowledge when they plan to build PAM solutions. Many organization do not have base-line when they acquire new PAM technology. This paper will help organization to acquire PAM solution that meet the ISO 27001 control. Our compliance matrix give organization a guideline to achieving the implementation of ISMS framework with PAM technology.