Reviewerly/exHarmony huggingface dataset:
Location based Web Object Search using Probabilistic Classification Model.

The classical Web search engines focus on satisfying the information need of the users by retrieving relevant Web documents corresponding to the user query. The Web document contains the information on different Web objects such as authors, automobiles, political parties e.t.c. The user might be accessing the Web document to procure information about a specific Web object, the remaining information in the Web object [2-6] becomes redundant specific to the user. If the size of Web documents is significantly large and the user information requirement is small fraction of the document, the user has to invest effort in locating the required information inside the document. It would be much more convenient if the user is provided with only the required Web object information located inside the Web documents. Web object search engines provide Web search facility through vertical search on Web objects. In this paper the main goal we considered is the objective information present in different documents is extracted and integrated into an object repository over which the Web object search facility is built.
Factors Effecting Information Security Management and their impacts on Organization performance in the work environment: Case study; Hatif Libya Company ( HLC )

Information security (InfoSec) is an important issue which is gaining more and more interest by organizations worldwide.This study aims to evaluate the service management approach of information security management that applied and utilized to improve effective information security management in the Hatif Libya Company (HLC).The aim of this study is to evaluate the processes and the performance of HLC by following the improvements of information security management standards at the company.This research study has used a descriptive research approach to collect the required data by designing and distributing an online questionnaire to the study participants.An interpretive case-study approach, as well as questionnaires, were employed to support data gathering.On the other hand, the researchers have reviewed previous studies that talked about subjects to compare among identifying the similarities as well as differences among related to the research topic.The discussion and analysis processes has been applied for the findings and results to evaluate the importance of considering information security management for HLC and Libyan related companies; and also, for those who are interested in the same study subject.In conclusion, The main objective of this research, concepts and principles of information security have been tested to deliver actionable information for decision-makers within HLC firm to manage their corporate assets and ensure their resilience and increase productivity.In addition, this practical research study is an important for Libyan organizations as organizations are working at one of the development countries who they are seeking to ensure high level of information security management factors to increase company's performance and productivity to make time to market.
Reports of Conferences, Institutes, and Seminars

This quarter’s column offers a report from the 2018 annual meeting of the Ex Libris Users of North America (ELUNA), as well as coverage of sessions from the annual meeting of the Northern Ohio Technical Services Librarians (NOTSL). A handful of reports were also collected from courses offered at the FORCE11 Scholarly Communications Institute. Topics covered include features within ExLibris’s Alma library that support print serials operations, current and future developments in serials librarianship, and critiques about open peer review.
Restaurant Recommendation System using Machine Learning

Nowadays a big challenge when going out to a new restaurant or cafe, people usually use websites or applications to look up nearby places and then choose one based on an average rating. But most of the time the average rating isn't enough to predict the quality or hygiene of the restaurant. Different people have different perspectives and priorities when evaluating a restaurant. Many online businesses now have implemented personalized recommendation systems which basically try to identify user preferences and then provide relevant products to enhance the users experience . In turn, users will be able to enjoy exploring what they might like with convenience and ease because of the recommendation results. Finding an ideal restaurant can be a struggle because the mainstream recommender apps have not yet adopted the personalized recommender approach. So we took up this challenge and we aim to build the prototype of a personalized recommender system that incorporates metadata which is basically the information provided by interactions of customers and restaurants online(reviews), which gives a pretty good idea of customers satisfaction and taste as well as features of the restaurant. This type of approach enhances user experience of finding a restaurant that suits their taste better. This paper has used a package called lightfm(the library of python for implementing popular recommendation algorithms) and the dataset from yelp. There are different methods of filtering the data, here we have used Hybrid filtering which is a combination of Content-based filtering (CBF) and Collaborative Filtering (CF). Since the results from Hybrid filtering are far more closer to accuracy than CBF or CF respectively. Then hybrid filtering gives results in the form of personalized recommendations for users after training and testing of the data
A Cloud-Based Architecture for Interactive E-Training

Cloud-based technologies play a significant role in the technology-enhanced learning domain. The adoption of cloud technologies in the educational environment has a positive impact on the learning process by offering new tools and services to improve and support the learning life cycle, including interactivity. In specific fields, such as clinical skills training, that involve computer-intensive training scenarios, there is an increased demand to deliver training services to a larger number of learners, therefore the need for cloud services. However, to date there has been a lack of a formalized framework relating to the use of cloud computing for on-demand interactive e-training resources. This paper is to formalize a theoretical framework for an interactive e-training system particularly for clinical skills training, taking into consideration e-training system requirements and with a focus on applying cloud technologies to ensure the dynamic scalability of services and computing power while maintaining QoS and security
A Ranking Based Model for Selecting Optimum Cloud Geographical Region

Cloud computing has become a dominant service computing model where the services such as software, platform, infrastructure are provided to the cloud consumers on demand basis using pay as you go model. Every cloud consumer requires high performance service in minimal cost. The performance of service in cloudis measured by the parameters availability, agility, cost, and security etc. The service performance and cost are very much dependent on the cloud geographical region (CGR) where these are deployed. The services offered by the cloud service provider are installed on multiple data centers located at different CGR. In cloud environment, the selection of a service installed on the optimum CGR within the limited time overhead is a challenging and interesting problem. In this paper, the multi criteria decision making method, PROMETHEE II and objective weighting method Shannon’s Entropy,based ranking model is proposed for solving the optimum CGR selection problem. The CGR dataset of Amazon Web Service is used for the numerical analysis. The sensitivity analysis is performed for validating the stability of the proposed model and getting the most sensitive parameter. The applicability and usefulness of the service selection process is validated through the experimental results on synthetic dataset. Results show that the service selection process is achieved withlimited time overhead and hence suitable for online selection process in cloud.
International Students Assesment of Service Quality In Academic Libraries

Service quality assessment is a key and significant issue in library management since it gives criticism to libraries to enhance on services delivery to their users.This study presents LibQUAL+ TM tool and SERVQUAL gap analysis by measuring the perception and expectation of the quality services provided by academic libraries from the point of view and experiences of international students in Jiangsu University.The 22-item LibQUAL+ TM instrument, measuring the three service dimensions of Affect of Service, Information Control and Library as Place, was administered to the international students, with 201 respondents based on simple random sampling.The researchers used analysis method like descriptive statistics, reliability analysis and exploratory factor analysis.The study revealed that international students who are users of the Jiangsu University Library have high expectations of service quality at Jiangsu University Library whiles perception of services delivered by Jiangsu University Library was a mixture of both low and high across the three dimension of service quality based on the LibQUAL+ TM instrument.In addition, the results show that there is negative gap for Affect of Serve (-0.62) and Information Control (-0.54) dimension and a positive gap for Library as Place (0.07) service dimension.Even though, the library has high perception for one of the dimensions, the overall level of service quality (-0.44) is low and negative.This study therefore fills in as a guide for various libraries to utilize while leading service quality appraisal for their users and furthermore makes recommendation for libraries to consider in the provision of services for their users particularly international students.
Static scene target detection based on VIBE algorithm

In this paper, we analyze the foreground target extraction problem of surveillance videos and establish various mathematical models for different types of surveillance videos: two-frame difference model, Single Gaussian Model (SGM) and VIBE model, and apply these models comprehensively to achieve the extraction of foreground targets in surveillance videos with different background characteristics. On the basis of foreground target extraction, the effective features of the image sequence are extracted to determine the abnormal behavior of the crowd in the video.
Trusted Group Construction Mechanism Based on Trusted Management

The Internet of things connects a large number of device nodes through the Internet, realizing the interconnection of all things at any time and anywhere. However, the multi-source heterogeneous, free and open characteristics of the Internet of things lead to the lack of dynamic adaptability of the current network connection model and can not deal with a variety of security threats. Therefore, how to build a safe and reliable trusted group is a key problem to be solved in the Internet of things environment. Trusted measurement technology can comprehensively measure the large-scale terminal nodes of the Internet of things, ensure the credibility of the perceived nodes, and lay the foundation for the overall security of the Internet of things. In the Internet of things environment, the main research content of this paper is how to use the trusted measurement technology to build a safe and reliable trusted group, and solve the security threat faced by the trusted group in the dynamic operation process. Firstly, this paper analyzes the centralized and distributed network structure in the Internet of things perception network, and then designs the corresponding perception node Trusted measurement scheme and trusted group construction mechanism. In this paper, for the centralized networking, the sensing node has the three-tier structure characteristics of “base station, domain management node and ordinary sensing node”. In the Trusted measurement stage, hierarchical measurement is used to measure the static environment, dynamic behavior and energy of the sensing node respectively. In the construction of trusted groups, hierarchical management is used to decide whether individuals join trusted groups; Reduce the possibility of malicious nodes as management nodes by adding monitoring nodes; Regularly evaluate the security status of nodes and eliminate malicious nodes in time.
Youtube Video Ranking: A NLP based System

YouTube is an acclaimed video information source on the web among various social media sites, where users are sharing, commenting and liking/dis-liking the video along with the continuous uploading of videos in real-time. Generally, the quality, popularity and relevance of results obtained from searching a query are obtained based on a rating system. Now and then few irrelevant and substandard videos are ranked higher because of higher views and likes. To address this issue, we put forth a sentiment analysis approach on the user comments based on Natural Language Processing. The suggested analysis will be helpful in providing a desirable result to the search query. The effectuality of the system has been proved in this paper using a data driven approach in terms of accuracy.
Model of the Organization of the Blended Learning in the Translation of Business Correspondence on the Basis of Electronic Educational Resources

The article is devoted to the description and analysis of the implementation model of modern educational technologies of blended learning in the process of professional training of specialists in foreign languages. These technologies act as a means of stimulating motivation, cognitive independence and activity of students. Their use increases the efficiency of the educational process by changing the models of interaction of its participants. At the same time, students make the transition from traditional passive perception of the material to its active development thanks to the capabilities of the virtual learning environment, which allows them to build their own learning path and consciously master the learning information. The advantage of blended learning is a more appropriate distribution of study time, high adaptability and interactivity, a deeper understanding and analysis of program material by students. The appropriateness of the application of educational technologies of blended learning was analyzed on the example of studying the course "Theory and Practice of Translation of Epistolary Texts (French)" by students of Kazan Federal University. The material for testing was an electronic educational resource developed specifically for the development of this educational discipline. An analysis of the results of the pilot training shows that the introduction of these technologies increases the significance and effectiveness of the educational process due to its individualization and differentiation, and also develops the creative thinking of students, forms their responsibility and ability to self-management.
Intelligent Classification Technique for Breast Cancer

Breast cancer is also a leading cause of cancer death in the less developed countries of the world. This is partly because a shift in lifestyles is causing an increase in incidence. Breast cancer originates from the inner lining of milk ducts/lobes either in the form of invasive or non invasive disease in general. Mammography, particularly with Computer-Aided Detection (CAD), can now produce images detailed enough for diagnostic purposes, and digital mammography allows transmission of 3-dimensionssal images over long distances. The aim for the system is to design a Computer Aided Diagnosis systematic tool for perceiving non cancerous and perilous (cancer causing) mammogram. The aim of the research is proposed to develop an image processing algorithm for an automatic detection and classification of breast lesions accurately. CAD tool helped radiologist in expanding his assurance accuracy. Support vector machine (SVM) classifier is used to discriminate the tumors into benign or malignant. Incorporate best features of the find out that has significant responsibility in achieving the perfect turnout which are then designated and associated with ANN to train and classify.
OO Metric Analysis of Optimally Sparse LSB-Based Steganography in E-Learning Environment

In an e-Learning environment, the communication between sender and receiver has been done via Internet. In general, while the sender sends their important documents to receiver through Internet, he/she encrypts the document which is decrypted by the receiver(s) at their end. In case of large images, decryption causes some sort of distortion, which may be overcome through our proposed model. The object oriented analysis of a system helps to make better understanding and cop up with the real world. The main characteristics of object oriented metric analysis are data hiding, data encapsulation, data abstraction, polymorphism etc. Here we calculate the values of different metrics like CK and MOOD metrics based on the class diagram of our proposed model regarding the transmission of documents from administrator to learner.
Cover

Meteoritics & Planetary ScienceVolume 54, Issue 8 p. i-i CoverFree Access Cover First published: 01 August 2019 https://doi.org/10.1111/maps.13162AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Graphical Abstract Volume54, Issue8August 2019Pages i-i RelatedInformation
ENHANCING STUDENTS' READING ABILITY THROUGH PEER-ASSISTED LEARNING STRATEGIES (PALS)

Abstract:This study aims to enhance the students' reading ability through Peer-Assisted Learning Strategies (PALS) in SMA Negeri 19 Makassar. This research is a Classroom Action Research (CAR), which consists of four stages: planning, implementing, observing, and reflecting. The research techniques used are pretest, post-test, and observation. The findings showed that the use of Peer-Assisted Learning Strategies was successful in improving the students' reading ability. The improvement can be seen from the mean score of the students in cycle one is 23.1, which is categorized as good, while in cycle two, it is 73.1, which is classified as very good. Seventeen students met the Minimum Completeness Criteria (MCC) in cycle one, and 22 students completed the MCC in cycle two. Therefore, this research concludes that Peer-Assisted Learning strategies improve the students' learning outcomes of reading ability in SMA Negeri 19 Makassar.Abstrak:Penelitian ini bertujuan untuk meningkatkan kemampuan membaca siswa melalui Peer-Assisted Learning Strategies (PALS) di SMA Negeri 19 Makassar. Penelitian ini merupakan Penelitian Tindakan Kelas (PTK) yang terdiri dari 4 tahap; perencanaan, pelaksanaan, observasi, dan refleksi. Teknik penelitian ini menggunakan tes dan wawancara. Hasil penelitian menunjukkan bahwa penggunaan Peer-Assisted Learning Strategies berhasil meningkatkan kemampuan membaca siswa SMA Negarei 19 Makassar. Peningkatan tersebut terlihat dari nilai rata-rata siswa pada siklus I sebesar 23,1 dengan kategori baik, dan pada siklus II sebesar 73,1 tergolong sangat baik. Tujuh belas siswa memenuhi Kriteria Ketuntasan Minimum (KKM) pada siklus satu, dan 22 siswa memenuhi KKM pada siklus dua. Oleh karena itu, penelitian ini menyimpulkan bahwa kemampuan membaca siswa meningkat melalui model pembelajaran Peer-Assisted Learning Strategies di SMA Negarei 19 Makassar.
Solar Energy Harnessing Optimization Algorithm in a Robotic Solar Tracker with Arduino Based Monitoring System

Solar power although an abundant source of renewable energy must be utilized properly. One of the main factors to optimize its benefits is the capacity of the consumers to efficiently channel its power. The motivational factor of this endeavor is creating a robotic sunlight tracker system in harnessing solar radiant to its optimum potential in the Philippine setting, where sun’s insolation is low on the average due to the factors affecting climate conditions (like temperature, rainfall, storminess, winds, etc.).The study developed a prototype robotic sun tracker that is operated by a microcontroller using the sun’s perpendicularity and shadowing techniques in the design of the mechanism that injected an intelligent comparator algorithm. A motor control method was used to execute the best turn to harness the optimum solar energy with an Arduino based monitoring system that measured the voltages obtained from each of the set-ups. The result was a 29% improvement in generating electricity using the robotic sun tracker system versus static panel installation.
Vetted Encryption

We introduce Vetted Encryption (VE), a novel cryptographic primitive, which addresses the following scenario: a receiver controls, or vets, who can send them encrypted messages. We model this as a filter publicly checking ciphertext validity, where the overhead does not grow with the number of senders. The filter receives one public key for verification, and every user receives one personal encryption key. We present three versions: Anonymous, Identifiable, and Opaque VE (AVE, IVE and OVE), and concentrate on formal definitions, security notions and examples of instantiations based on preexisting primitives of the latter two. For IVE, the sender is identifiable both to the filter and the receiver, and we make the comparison with identity-based signcryption. For OVE, a sender is anonymous to the filter, but is identified to the receiver. OVE is comparable to group signatures with message recovery, with the important additional property of confidentiality of messages.
Automated Evaluation of Students’ Feedbacks using Text Mining Methods

In this era of competition there is a culture of online reviews or feedbacks. These feedbacks may be about any product or service. However, major issues are their unstructured textual form and big number. It means every user gives feedback in own style. Study and analyzing of such unorganized big number of feedbacks that are growing every year becomes herculean task. This paper describes about mining of structured data (table) and unstructured data (text) both. An application from academic environment for structured and unstructured form of data is considered and discussed to enhance understanding and easiness of researcher. Stanford Parser plays a very useful role to understand the semantic of a sentence. It gives a base that how to separate data from the wellspring of information accessible in the literary structure like web based life, tweets, news, books and so on. It is also helpful to judge a teaching learning process in terms of teacher’s performance and subject’s weakness if any. This paper has five sections first about introduction, second about literature of text mining and its techniques, third about proposed work and result, fourth about future perspectives and finally fifth as a conclusion.