Reviewerly/exHarmony huggingface dataset:
Interest Point Detection by Limiting Form of Median Log Filter

Interest point detection has been widely used in image analysis applications. However, some interest points, including small structures and large angle corners, could not be effectively extracted. This paper proposes a limiting form of median Laplacian of Gaussian (LMLG) filter, which combines the superiority of the traditional Laplacian of Gaussian (LoG) filter and a limiting form of the weighted median LoG filter. A detector is also proposed based on the LMLG filter. The LMLG filter aims to improve the detection of LoG-based methods for interest points, especially small structures and large angle corners. Also, it could detect blobs, edges, and local structures. We conduct the repeatability and discrimination experiments on the Oxford dataset. Moreover, we conduct the recall rate experiment on the DTU dataset. The experiments show that the proposed method achieves comparable performance with state-of-the-art methods. In order to verify the utility of the LMLG detector, we carry out a series of interest point detector-based applications: face recognition, infrared-visible image registration, and image classification. The results demonstrate that the LMLG detector performs better than the nine detectors in face recognition. The LMLG detector outperforms the nine detectors and Hrkać's, Han's and Liu's methods in infrared-visible image registration. Our method also gives a comparable result on image classification. The source code of the proposed LMLG detector is made publicly available at https://github.com/chenjzBUAA/LMLG-detector.
The Implementation of Debate Technique to Enhance the Students’ Speaking Skill

The objective of this research was to improve the quality of teaching and learning speaking by using debate technique at the tenth grade students of SMAN Modal Bangsa, Aceh. The academic year was 2017/2018. The participants of this research were 27 students at class X/IPA-5. The research was classroom action research which was done in two cycles.Eachcycle consisted of two meetings. There were two types of data namely quantitative data and qualitative data. The result of the first cycle shows that the percentage score for the researcher’s performance was 70 % which is categorized as good; while in the second cycle the score was 90 % which is categorized as very good. Regarding to the students’ involvement, the percentage score in the first cycle was 75% or in the middle category, and it increased significantly in the second cycle with the percentage 95% or in the excellent category.Furthermore, the class passing percentage in the pretest was 55,55 %, but it increased 81,48 %in the first cycle and 100 % in the second cycle.  It indicates that the success indicator is reached. Finally, the data from the questionnaire shows that the students responded positively to the use of debate technique in the process of teaching and learning speaking. The outcome of this research showed that using debate technique were able to improve the teacher’s performance in teaching speaking, and the students’ involvement in learning speaking. It also improved the students’ speaking skill. Key words :  Speaking Skill, Debate Technique, Classroom Action Research
More DOIs are Accessed Through Library Discovery Services than Through Google

A Review of:&#x0D; Wang, X., Cui, Y., &amp; Xu, S. (2018). Evaluating the impact of web-scale discovery services on scholarly content seeking. The Journal of Academic Librarianship, 44(5), 545-552. https://doi.org/10.1016/j.acalib.2018.05.010 &#x0D; Abstract&#x0D; Objective – To examine trends in digital object identifier (DOI) web referrals and explore the referring domains, especially those originating from web-scale discovery systems like ProQuest’s Summon and Primo.&#x0D; Design – Log analysis and web traffic analysis.&#x0D; Setting – CrossRef, a web server that connects DOIs to the corresponding articles’ landing pages.&#x0D; Subjects – Web traffic that passed through CrossRef between 2011 and 2016.&#x0D; Methods – The researchers collected data from CrossRef using a web tool called Chronograph. The data captured information about the websites users were on when they requested a DOI (called the referrer) and about the time and date of each request.&#x0D; The researchers used time series analysis to discover longitudinal patterns in the data. Annual, monthly, and weekly trends were also examined with a seasonal adjustment model, a seasonal trend decomposition, and log transformation. They also isolated traffic from four institutions in Australia, Japan, Sweden, and the United States of America to determine if overall seasonal patterns were reflected locally.&#x0D; ProQuest websites were of particular interest to the researchers because they determined that it had the highest market share of discovery services. Much of the analysis focused on ProQuest’s serialsolutions.com, exlibrisgroup.com, and proquest.com website domains.&#x0D; Main Results – ProQuest servers sent over 25 million DOI referrals through CrossRef – more than either Web of Knowledge (n=24.47 million) or Google (n=15.38 million).&#x0D; Referral traffic grew over the period with the sharpest growth rate occurring between 2011 and 2012. Of ProQuest’s domains, serialsolutions.com (Summon) had more traffic and more growth over the observation period than exlibrisgroup.com (Primo).&#x0D; In all of the years studied, the busiest months were September to November and January to March, while June to August and December were low points. Seasonal fluctuations were attributed to university vacation schedules as demonstrated in the traffic patterns of four ProQuest-subscribing institutions.&#x0D; Weekly trend analysis showed that Monday to Thursday had consistently heavy referral traffic. Of the remaining days, the fewest referrals were observed on Saturdays.&#x0D; Conclusion – DOI referrer traffic is closely tied to the university calendar. Library discovery products are used more frequently to access DOIs than Google.
PostAc : A Visual Interactive Search, Exploration, and Analysis Platform for PhD Intensive Job Postings

Over 60% of Australian PhD graduates land their first job after graduation outside academia, but this job market remains largely hidden to these job seekers. Employers’ low awareness and interest in attracting PhD graduates means that the term “PhD” is rarely used as a keyword in job advertisements; 80% of companies looking to employ similar researchers do not specifically ask for a PhD qualification. As a result, typing in “PhD” to a job search engine tends to return mostly academic jobs. We set out to make the market for advanced research skills more visible to job seekers. In this paper, we present PostAc, an online platform of authentic job postings that helps PhD graduates sharpen their career thinking. The platform is underpinned by research on the key factors that identify what an employer is looking for when they want to hire a highly skilled researcher. Its ranking model leverages the free-form text embedded in the job description to quantify the most sought-after PhD skills and educate information seekers about the Australian job-market appetite for PhD skills. The platform makes visible the geographic location, industry sector, job title, working hours, continuity, and wage of the research intensive jobs. This is the first data-driven exploration in this field. Both empirical results and online platform will be presented in this paper.
SCIENTIFIC JOURNAL “BIBLIOTEKOSNAVSTVO. DOCUMENTATION. INFORMOLOGY” IN PROFESSIONAL СОММUNICATIONS SPACE

The purpose of the article. To carry out a thematic review of articles published in the journal “Library Science. Record Studies. Informology”. The methodology is to use general scientific methods and special methods: analysis, synthesis, logical method, a method of visualization of research results. Scientific novelty is to analyze the thematic component of publications for 15 years (from 2004 to 2018), which reveal the main areas of research presented in the journal. Conclusions. The review of publications shows that the magazine has become an important historical source that retains the results of scientific research and research on information, librarianship and archival affairs. The content of publications allows to analyze trends in the development of science and practice of the document and information industry, the activity of separate archives, libraries, museums, scientific institutions, institutions of higher education, and training of specialists in the field, which in turn increases the level of knowledge and communication between specialists.
A Japanese Word Segmentation Proposal

Current Japanese word segmentation methods, that use a morpheme-based approach, may produce different segmentations for the same strings.This occurs when these strings appear in different sentences.The cause is the influence of different contexts around these strings affecting the probabilistic models used in segmentation algorithms.This paper presents an alternative to the current morpheme-based scheme for Japanese word segmentation.The proposed scheme focuses on segmenting inflections as single words instead of separating the auxiliary verbs and other morphemes from the stems.Some morphological segmentation rules are presented for each type of word and these rules are implemented in a program which is properly described.The program is used to generate a segmentation of a sentence corpus, whose consistency is calculated and compared with the current morpheme-based segmentation of the same corpus.The experiments show that this method produces a much more consistent segmentation than the morpheme-based one.
THE INFLUENCE OF DISCOVERY LEARNING AND SNOWBALL THROWING METHOD IN IMPROVIN WRITING SKILLS OF HIGH SCHOOL STUDENTS

The purpose of this study is to analyze the improvement of students' writing skills by using Discovery learning and the Snowball Throwing method. this study uses Quasi-Experimental by comparing two different variables with the stages of giving pre-test, treatment, and post-test and looking for the difference in value using the Gain Test. This research was conducted in class XI of SMK 4 Padalarang LPPM with a sample population of 60 students namely 30 students of class XI RPL 1 as control class and 30 students with discovery learning method and RPL 2 class as Experimental class with Snowball Throwing approach. From the results of this study conclusions are obtained 1). The ability to write students using the Snowball method is effective and better than using discovery learning. 2). There is a change in the value of writing narrative texts of students using the snowball method rather than discovery learning.
xSS: A Soccer Server extension for automated learning of high-level robotic soccer strategies

A solution for an optimal robotic soccer strategy is yet to be found. Multiple agents interacting in an environment with continuous state and action spaces is a recipe for machine learning lethargy. Fortunately, due to the increasing hardware performance and new algorithms, the area of reinforcement learning is growing considerably. However, simulating the environment for strategy purposes is not following this trend. Several simulators are available, including those used in major soccer competitions (e.g. RoboCup). However, no option combines a good repository of teams with a simple command set that abstracts low-level actions. To clarify this problem, we surveyed the most promising simulators and proposed an extension for the well-established Soccer Server. The objective was to simplify the process of learning strategy-related behaviors through automated optimization algorithms. The results have shown a clear advantage in using the extension to improve the agent's performance. This work contributes to the development of future strategies related with RoboCup or other soccer competitions. Despite the good results, there is space for improvement in computational efficiency and behavior diversity.
f90nml - A Python module for Fortran namelists

Fortran namelist files (ISO, 2018).The primary use case for this module is to read a namelist file via the Parser and save its contents into a Namelist data structure, which is a case-insensitive subclass of a dict, Python's intrinsic associative array.The Namelist object can be read and modified as a standard Python dict, and its contents can be saved as a formatted namelist file.
Diagnostic Accuracy in Staging of Carcinoma Cervix Using Magnetic Resonance Imaging versus Clinical Staging

Cervical cancer is the second most common cancer for women world Wide.The management of the ca cervix depends on the stage of the disease, hence, accurate staging of the disease is necessary for the selection of therapeutic strategy.The current staging system, that is the FIGO clinical staging system, has got some limitation and inconvenience to the patient.It is inadequate in the evaluation of prognostic factors like tumor size, parametrial invasion and nodal status.MRI is a noninvasive method of imaging without using ionizing radiations.Recent technical advances in MR imaging and proven ability of MRI in evaluation of parametrial invasion, tumor size, lymph node metastasis made MRI an optimal option for evaluation of the main prognostic factors and selection of therapeutic strategy.Objectives: The present study was aimed to find out the sensitivity, specificity, positive and negative predictive value and accuracy of MRI in staging carcinoma cervix by comparing with the FIGO clinical staging system, which was taken as the reference.Methods: Our study was a diagnostic test evaluation study involving 61 objects who were newly diagnosed cases of carcinoma cervix, already staged clinically by the FIGO system and referred to the radiology department for MRI imaging of pelvis during the period January 2016 to June 2017.MRI imaging of the pelvis and screening of abdomen was done for these patients.Patient was then staged with MRI.Then the predicted stage for each patient with the two methods were compared.The analysis done by standard Chi square test.The sensitivity, specificity, positive and negative predictive values were obtained.Results: In assessing whether the lesion was confined to cervix or extended beyond cervix sensitivity, specificity, PPV, NPV, & accuracy was 60%, 100%, 100% 92.7% and 93% respectively.In assessing the parametrial extension MRI had a sensitivity, specificity, PPV, NPV, & accuracy of 100%, 60%, 88.5%, 100%, 90.1% respectively.In assessing the bladder mucosal invasion MRI had a sensitivity, specificity, PPV, NPV, & accuracy of 100%, 94%, 78.6%, 100%, 95% respectively.In assessing the rectal mucosal invasion MRI had a sensitivity, specificity, PPV, NPV, & accuracy of 100%, 96.5%, 66.7%, 100%, 96.7% respectively.Clinical staging and MR staging concurred in 85% of cases and differed in 15% of cases.Conclusion: Magnetic resonance imaging in carcinoma cervix has a good sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy in differentiating between different stages of the disease .In addition to the information regarding tumor size and its local extension, MRI also provided details regarding the pelvic lymphadenopathy, abdominal and inguinal lymphadenopathy, abdominal, pelvic metastasis as well as possibility of lung metastasis if pleural effusion or basal lung lesion were present.
An Approach towards Development of a Migration enabled Improved Datacenter Broker Policy

Cloud computing has left its remarkable note on the computing world over the last few years. Through its effectiveness, litheness, scalability &amp; availability cloud computing has changed the nature of computer system deployment. The Quality of Service (QoS)of a cloud service provider (CSP) is an important element of research interest which includes different critical issues such as proper load, minimization of waiting time, turnaround time, makespan and suppressing the wastage of bandwidth of the system. The Datacenter Broker (DCB) policy help assigning a cloudlet to a VM. In the present study, we proposed an algorithm, i.e., Migration enabled Cloudlet Allocation Policy (MCAP) for allocation of cloudlets to the VMs in a Datacenter by taking into account the load capacity of VMs and length of the cloudlets. The experimental results obtained using CloudSim toolkit under extensive loads that establish performance supremacy of MCAP algorithm over the existing algorithms.
CHANGE MANAGEMENT IN RUSSIAN RESEARCH UNIVERSITY IN A CHANGING CONTEXT. CASE STUDY OF HSE UNIVERSITY ST. PETERSBURG

This article presents an analysis of management practices that lead to increase of competitiveness of St. Petersburg branch of the National Research University Higher School of Economics on the national market in 2013– 2018. The authors discuss a list of the main indicators of success of changes in Russian universities in the context of the institutional and market conditions of Russian higher professional education in the early 2010s. The article highlights and analyzes the main groups of factors of changes in university management: a new strategic vision and the formation of a critical mass of supporters of change, introduction of internal institutions of change along with external institutions of change. The authors argue that radical increase of market competition drives complex changes within Russian universities, which require significant changes both in the strategic positioning and in the organization of primary and support business processes. Such changes are close to changes in corporate sector of firms in conditions of radical transformation of the external environment. The analysis presented in the article can be useful for the management of Russian universities when choosing tools to accelerate university changes.
KNOWLEDGE AND USERS’ PREFERENCES OF CONTEMPORARY MARKETING STRATEGIES USED IN ACADEMIC LIBRARIES

Purpose: This study investigated knowledge and users’ preferences of contemporary marketing strategies used in academic libraries. It is a user study innovation characterized by granting users’ with the information appropriate for better library usage and their feedback to analyze how what is presented to them makes an impact towards their attainment of academic goals. Methodology: This study carried out in University of Calabar Library adopted survey research design on a population of 1804 registered users. A simple random sampling technique was adopted in selecting 600 undergraduate and postgraduate registered users. Accordingly, 600 copies of questionnaire were distributed in the reader services units, which comprised Social Sciences, Medical, Africana, Humanities, Law, Reference as well as Science and Technology/Annex Divisions of the library. Questionnaire was distributed with a condition that only registered users who use the library often (at least thrice a week) were eligible to respond. Only 428 usable copies were returned and these were analyzed for the study. Findings: Study revealed users’ knowledge of marketing strategies in the following sequence Digital media marketing 423(98.83%), Awareness services marketing 377(88.08%) and Conducive environment marketing 224(52.34%). The result of preferences showed Digital media marketing as most preferred with 421(98.36%), Awareness services marketing had 398 (92.99%) respondents and Conducive environment marketing 204(47.66%). On the challenges, two respondents (5&34) frankly indicated their lack of understanding for the term conducive environment. This has a great implication for the result altogether but other respondents revealed their challenges with regards to inappropriate time fixed for library use of e-library, epileptic power supply, low bandwidth, that causes the network to show while pages were unable to open and staff negative attitude. Suggestions were given to encourage the publications of local news and magazines, which would help to intimate users of issues relating to library use among others. Originality: This article offer valuable insight on the users’ knowledge and preferences of contemporary marketing strategies in academic libraries. This indicate that, it is only when users’ are given what they desire, that they could be said to be satisfied.
Analysis, Test and Management of the Meta-Heuristic Searching Process: An Experimental Study on SOS

In a search process, getting trapped in a local minimum or jumping the global minimum problems are also one of the biggest problems of meta-heuristic algorithms as in artificial intelligence methods. In this paper, causes of these problems are investigated and novel solution methods are developed. For this purpose, a novel framework has been developed to test and analyze the meta-heuristic algorithms. Additionally, analysis and test studies have been carried out for Symbiotic Organisms Search (SOS) Algorithm. The aim of the study is to measure the mimicking a natural ecosystem success of symbiotic operators. Thus, problems in the search process have been discovered and operators' design mistakes have been revealed as a case study of the developed testing and analyzing method. Moreover, ways of realizing a precise neighborhood search (intensification) and getting rid of the local minimum (increasing diversification) have been explored. Important information that enhances the performance of operators in the search process has been achieved through experimental studies. Additionally, it is expected that the new experimental test methods developed and presented in this paper contributes to meta-heuristic algorithms studies for designing and testing.
Detecting Phishing using Machine Learning

Phishing is a social engineering Technique which they main aim is to target the user Information like user id, password, credit card information and so on.Which result a financial loss to the user.Detecting Phishing is the one of the challenge problem that relay to human vulnerabilities.This paper proposed the Detecting Phishing Web Sites using different Machine Learning Approaches.In this to evaluate different classification models to predict malicious and benign websites by using Machine Learning Algorithms.Experiments are performed on data set consisting malicious and benign, In This paper the results shows the proposed Algorithms has high detection accuracy.
Linked Open Data for Taxonomic Databases: The Nordic/Baltic implementation

Starting with Finland and Sweden and a subset of taxonomic groups, the Nordic/Baltic countries are connecting national checklists using Linked Open Data standards (Auer et al. 2007) and agreed vocabularies. We use HTTP Uniform Resource Identifiers as globally unique, persistent identifiers for taxon concepts (Chawuthai et al. 2013). Currently, we provide both human-readable (html) and machine-readable (xml) responses for client requests via a central checklist, TAXONID.ORG, which in itself needs to be managed. However, we hope this can be replaced by Catalogue of Life Plus in a not too distant future. While initially exchanging taxonomic information, our goal is ultimately to share information also on genetics, images and traits as well as conservation status and observations in a standardized way. The work is part of the NeIC DeepDive project which is funded by the Nordic e-Infrastructure Collaboration (neic.no/deepdive). The vision is to establish a regional infrastructure network consisting of Nordic and Baltic data centers and information systems and to provide seamlessly operating regional data services, tools, and virtual laboratories.