Reviewerly/exHarmony huggingface dataset:
Penerapan Sistem Informasi Tracer Study Pada Universitas Muhammadiyah Kotabumi

Tracer Study is research on the situation of alumni that aims to get a lot of information from graduates / alumni to improve the quality of graduates. Tracking alumni information that can be used as input and evaluation for improving learning and the competencies of graduates. Information in the form of activities / activities of the graduates / alumni after taking education at UMKO, both in the waiting period or having activities in the work world. Computerized tracer studies online in tracking alumni can easily list the desired alumni that can be directly provided by graduates / alumni, where the system built can record graduates / alumni based on graduation years, cometensi fields, number of graduates, job profiles depicted in the form percentage, graph or diagram. Software development uses OOSE method with stages: (1) Requirement Engineering, (2) Object Oriented Design, (3) Implementation or Coding, (4) Testin. The tracking process using an integrated system is able to connect and store all graduate information in 1 (one) media, so that it can provide information to anyone who needs it. In addition, the data entered directly by the alumni so that the data level is more accurate, so that it can provide input to UMKO to improve the quality of graduates.
A Comparison between Different Recommender System Approaches for a Book and an Author Recommender System

A recommender system is a popular tool used by companies to increase customer satisfaction and to increase revenue. Collaborative filtering and content-based filtering are the two most common appro ...
Drive Your Project Team’s Engagement: A mixed methods study of engagement drivers beyond rewards and punishment

Project teams lack the ability to incentivize engagement. To cope with increasingly dynamic environments businesses adopt temporary organizational forms, such as project teams, that promise more adaptability but not seldom lack clear structures of power and authority. Given that research has repeatedly underlined the importance of engagement for the economic thriving of businesses, project teams seek methods to drive engagement that are within their application scope. This study aims to identify the most effective engagement drivers and to understand what their effectiveness depends on, mainly focusing on individuals’ career orientations. Building on existing work on engagement it asks: What factors engage project members the most and does their career orientation and career self-awareness interplay with the effectiveness of the engagement factors? In this context engagement is defined as being fully involved, characterized by the three states of vigor, dedication, and absorption, across the physical, cognitive, emotional, and social dimension. Based on a review of the literature on engagement, a survey was distributed to the team members of a student project. Afterwards, the participants’ career orientations were identified with an online test. Lastly, a randomly selected group of the participants was interviewed to follow up on survey responses. Analysis of the data suggest: The most effective drivers of engagement address the social dimension of teamwork. The results indicate that it can be distinguished between universal engagement drivers that motivate nearly anybody to engage and conditional engagement drivers which effectiveness depends on the career orientation but not career self-awareness of the individual. Moreover, this study discovered additional characteristics, such as assertiveness, egocentricity, and team- or task-focus that seem to affect the effectiveness of engagement factors. However, more research is needed to further validate the findings and hypotheses by considering a representative sample. (Less)
Improving the Speed of Support Vector Regression Using Regularized Least Square Regression

The Regularized Least Square (RLS) method is one of the fastest function estimation methods, but it is too sensitive to noise.Against this, ε-insensitive Support Vector Regression (ε-SVR) is robust to noise but doesn't have a good runtime.ε-SVR supposes that the noise level is at most ε.Therefore, the center of a tube with radius ε, which is used as the estimated function, is determined in a way that the training data are located in that tube.Therefore, this method is robust to such noisy data.In this paper, to improve the runtime of ε-SVR, first, an initial estimated function is obtained using the RLS method.Then, unlike the ε-SVR model, which uses all the data to determine the lower and upper limits of the tube, our proposed method uses the initial estimated function for determining the tube and the final estimated function.Strictly speaking, the data below and above the initial estimated function are used to estimate the upper and lower limits of the tube, respectively.Thus, the number of the model constraints and, consequently, the model runtime are reduced.The experiments carried out on 15 benchmark data sets confirm that our proposed method is faster than ε-SVR, ε-TSVR and pair v-SVR, and its accuracy are comparable with that of ε-SVR, ε-TSVR and pair v-SVR.
Influence of Modern Electronic Information Sources on Quality of Education of Student at History Department

The article explores the use of modern information technology by modern students studying at history department in the search for the necessary information. The work focuses on the ability of a student studying at history department to use the capabilities of the provided resources of the Internet correctly. It implies the ability to navigate electronic versions of libraries, archives and other sites of cultural and historical organizations, as well as the ability to select reliable information, which can sufficiently facilitate the search for high-quality material for writing all kinds of scientific papers. As a result of the analysis of statistical data regarding the popularity of the use of information offered by Internet resources, it was revealed that this topic is relevant nowadays. As a research task, the authors made an attempt to assess the nature of the use of Internet resources by students at the present stage. As a result, it was revealed that this issue has a number of contradictions. Methods of research. A significant part of the study is the description of reliable Internet resources that students studying at history department can use. These include the official sites of libraries, archives and museums. The results of the study showed that with the correct use of Internet resources offered on the World Wide Web, you can quickly find the necessary information and save time. It is concluded that nowadays it is necessary to continue developing the sites of cultural and historical organizations for the positive impact of electronic information sources on the quality of education, and it is also essential to build the information competence of students studying at history department.
An Efficient Clustering Algorithm with Enhanced MapReduce Design based Modified K Means for Outlier Detection

With an increase in amount of data also the speed of access to information has increased. Large data is the distorted form of every data well gained from different sources such as photos, , videos, social media sharing, network blogs, log files, etc. into a consequential and feasible forms. Clustering methods are very useful. Clustering process permits very analogous data to be positioned under a group by unscrambling the data into a explicit group. Once datasets are separated, outlier detection is used to discover false data. In this research work, goal is to formulate data clustering and outlier detection process quicker by using MapReduce technology with modified K-means clustering method. Clustering on enormous data can be time overriding. Hence, MapReduce computing design is utilized and focused on reliable, unfailing and swift clustering process by this technology. The successful execution with comparison to traditional K means is drawn. The results are offered in tables and graphs using sample dataset. The obtained results prove that an improved execution time is achieved in k means MapReduce algorithm along with a robust and efficient system for removing the outliers. The results also revealed an efficacy in terms of resource optimization.
Logical Differential Constraints Based on Interval Boolean Tests.

Continuous-time dynamical systems play a crucial role in the study or the design of systems in various domains. Checking the satisfaction of properties on these systems is important in particular in robotics or control-command systems. Constraint satisfaction problems is a well-suited framework for this purpose and recent papers extend this framework to deal with differential constraints. This article proposes an improvement of constraint differential satisfaction framework by providing a new solving algorithm based on interval Boolean functions.
LibGuides: Using the Catalog: Ebooks

Steps for searching the catalog, which types of resources to look for in the catalog, and which resources to NOT search for in the catalog. List of business/professional ebooks as well as a sampling of our more eclectic titles
Generation of two-mode quantum states of light with timing controllable memories

We created and experimentally verified two-mode entangled states of light, α|0,1⟩ + βe*+|1,0⟩, by means of two phase-sensitive optical quantum memories. The release timing of each optical mode can be independently controlled for up to 400 ns.
HUMAN RESOURCE DEVELOPMENT AMONG LIBRARIES IN THE CHANGING CONTEXT : AN OVERVIEW OF DEGREE COLLEGE PROFESSIONALS OF KARNATAKA

Development of any Nation is depends upon its quality of education. In this digital era libraries must adopt and change from traditional system to digital system. Academic library plays important and main role in imparting education to its students. Due to the rapid growth in the information generation and in varied forms, ever increasing information demands from users, now a days libraries must convert their collection and services from traditional to the automated. With the help of computer and software, Libraries can provide right information to right user in minimum time and at affordable cost. Hence they must change their traditional ways. This paper is focused on “In the age of automation, why continuous training and updates in knowledge regarding advanced technologies are necessary for library staff, Training and various training modules, Advantages of Training to the library staff as individual and to the library and why training is necessary to improve the quality of library services to achieve optimal satisfaction of library professionals.
Architecture and Research of Smart Book Management System Based on Artificial Intelligence Technology

With the continuous innovation and development of various new technologies, artificial intelligence technology has also been widely used in the field of smart books. The article proposes a design idea for a smart book management system based on artificial intelligence technology. It first analyzes the characteristics of various types of information in the book, analyzes the design requirements and system architecture of the smart book management system based on artificial intelligence technology, and truly realizes the automated office management of the book management system using artificial intelligence.
Hybrid Measurement Fusion Estimation of Distribution Network Based on Quadratic Constrained Quadratic Estimation

In view of the long-term coexistence of PMU measurement and SCADA measurement in the current power system, this paper analyzes the measurement characteristics of the distribution network. On the basis of the quadratic constraint quadratic estimation model, the Unscented Kalman Filter (UKF) algorithm is introduced to realize the fusion estimation of mixed measurement. The main research contents of this paper are as follows: First, the quadratic constraint estimation model is established, and the hybrid measurement quadratic constraint equation and hybrid measurement equation of PMU and SCADA are proposed; Second, in order to solve the problem of weak robustness of UKF, a Robust Unscented Kalman Filter based on Quadratic Constrained Quadratic Estimation (QCQE-RUKF) is proposed. The Strong Tracking Filter(STF) is introduced to modify the gain matrix in real time to enhance the robustness of the algorithm. Simulation results carried out on the IEEE 30-bus test system show that the QCQE-RUKF can track system status more accurately and reliably than UKF and Extended Kalman Filter (EKF).
On Multivariate Algorithms of Digital Signatures Based on Maps of Unbounded Degree Acting on Secure El Gamal Type Mode

&#x0D; &#x0D; &#x0D; Multivariate cryptography studies applications of endomorphisms of K[x1 x2, ..., xn] where K is a finite commutative ring given in the standard form xi →f1 (x1, x2,..., xn), i=1, 2,..., n. The importance of this direction for the constructions of multivariate digital signatures systems is well known. Close attention of researchers directed towards studies of perspectives of efficient quadratic unbalanced rainbow oil and vinegar system (RUOV) presented for NIST postquantum certification. Various cryptanalytic studies of these signature systems were completed. During Third Round of NIST standardisation projects ROUV digital signature system were rejected. Recently some options to seriously modify theses algorithms as well as all multivariate signature systems which alow to avoid already known attacks were suggested. One of the modifications is to use protocol of noncommutative multivariate cryptography based on platform of endomorphisms of degree 2 and 3. The secure protocol allows safe transfer of quadratic multivariate map from one correspondent to another. So the quadratic map developed for digital signature scheme can be used in a private mode. This scheme requires periodic usage of the protocol with the change of generators and the modification of quadratic multivariate maps. Other modification suggests combination of multivariate map of unbounded degree of size O(n) and density of each fi of size O(1). The resulting map F in its standard form is given as the public rule. We suggest the usage of the last algorithm on the secure El Gamal mode. It means that correspondents use protocols of Noncommutative Cryptography with two multivariate platforms to elaborate safely a collision endomorphism G: xi → gi of linear unbounded degree such that densities of each gi are of size O(n2). One of correspondents generates mentioned above F and sends F+G to his/her partner.&#x0D; The security of the protocol and entire digital signature scheme rests on the complexity of NP hard word problem of finding decomposition of given endomorphism G of K[x1,x2,...,xn] into composition of given generators 1G, 2G, ...tG, t&gt;1 of the semigroup of End(K[x1,x2,...,xn]). Differently from the usage of quadratic map on El Gamal mode the case of unbounded degree allows single usage of the protocol because the task to approximate F via interception of hashed messages and corresponding signatures is unfeasible in this case.&#x0D; &#x0D; &#x0D;
VIDEO TO IMPROVE STUDENTS’ SPEAKING ABILITY

Video as an audio-visual material in teaching English has grown rapidly and it is obvious that the use of video is a great help for students in stimulating and facilitating the target language. This study tries to solve students’ speaking problems and improve speaking ability by using video. The writer uses Classroom Action Research as research design. The implementation of video in teaching speaking class is arranged to bring benefit of the language learners. Video can make the classroom atmosphere more interesting and make students easier to speak. Video also stimulates students to be active. The students’ response about the implementation of video is positive and it will be alternative strategy in teaching speaking. So, video can improve the students’ speaking ability.
Effective Linear Policy Gradient Search through Primal-Dual Approximation

Recent research discovered that Reinforcement Learning (RL) algorithms with simple linear policies can achieve competitive performance as many state-of-the-art RL algorithms designed to train policies in the form of multi-layer neural networks. However, high learning performance is only achieved so far when policies are trained by jointly using multiple episodes of samples. An important research question remains as to whether linear policies can achieve cutting-edge performance when they are trained in a step-wise fashion (i.e., policies are iteratively updated based on every newly obtained sample). This paper presents a confirmatory answer to this question by developing a new RL algorithm called Primal-Dual Regular-gradient Actor-Critic (PD-RAC) as a generalization of RAC, which is a popular step-wise RL technique. Experiments on six benchmark control problems show that PD-RAC can achieve leading performance, in comparison to several recently developed baseline algorithms.
PENGEMBANGAN MEDIA GRAFIS DALAM PEMBELAJARAN

The use of media in the learning process is very important to support the learning process, in the modern era, graphic media is the most attractive medium, by using graphic media children can understand messages and help them to be more motivated to learn, the problem is when Graphic media is not able to develop and monotonous will make students tend to be bored and reduce motivation to learn, this paper, development of graphic media is something needs to develop, the affect children become active and have high learning motivation, several graphic media need to be developed such as Graphics, diagrams, charts, sketches, posters, comics, photo media, flannel boards and bulletin boards, educators (teachers) can present graphic media through visual media presenting, ideas through the presentation of words, sentences with numbers, and symbols or pictures. Graphics are used to attract attention, clarify the presentation of ideas, and illustrate facts, they are interesting and memorable. The advantages of graphic media can simplify and accelerate students' understanding of the message conveyed, increase student attention, and an affordable price. While the weakness of graphic media is requires special skills in its manufacture, especially for more complex graphics and the presentation of messages is only a visual element.
A Clustering Hybrid Algorithm for Smart Datasets using Machine Learning

In the field of data science, Machine Learning is treated as sub-field which primarily deals with designing of algorithms which have ability to learn from previous information and make future predictions accordingly.In traditional computational world the Machine Learning was generally performed on highly performance servers and machines.The implementation of these concepts on Big Data analytics algorithms has high potential and is still in its early stages.So far as machine learning is concerned, performance measure is an important parameter to evaluate the overall functionality of the algorithms.The data set is a different entity and the measuring of performance on a data which is unseen is also called as test set, and training set is a Data set which is training itself.The Data Mining is extensively using learning algorithms for data analysis and to formulate future predications based on archived data.The research presented provides a step forward to make smart data sets out of training data set by evaluating machine learning algorithm.The research presented a novel hybrid algorithm that attempts to incorporate the feature of similarities in Random Forest machine learning algorithm for improving the classification accuracy and efficiency of working.
An analysis on various types of Deep learning Techniques used for Named Entity Recognition System

Due to growing superficial solutions to the Natural language processing domains such as namedentity recognition for bio-medical, low resource languages and for annotated corpora where we can see thetremendous increase of the use of named entity systems in these fields for proper accurate results. ThisNamed entity recognition (NER)is likely the initial move towards data extraction that hopes to discover andgather named classes in content into pre-described classes, for instance, the names of individuals,affiliations, regions, enunciations of times, amounts, money related qualities, rates, and so forth. NER isutilized in numerous fields in Natural Language Processing, and where it can help to respond to somecertifiable inquiries. In this survey, we majorly discuss and give a brief description of the recently namedentity recognition which is built by the usage of deep learning techniques. This survey examines the paperswhich used the named entity recognition system for the contextualization of named entity corpora,predicting the diseases in the biomedical field and problems faced for low resource multilingual languagesthat have been already given before. In this, we compared the existing methodologies which present in thepapers to check which could give a better result or accuracy by using this Named entity recognition
AUTOMATIC DETECTION AND SECURITY DEFENSE OF NETWORK VULNERABILITIES BY USING CRAWLERS

The existence of network vulnerabilities has caused great hidden dangers to the network environment; hence it is necessary to detect and defend them using use appropriate methods. In this study, an automatic detection method was designed for XSS vulnerability by using a web crawler. The URL was crawled by the crawler, and the URL was deduplicated by using the tree-based HASN algorithm. Finally, the vulnerability was detected by simulating the XSS attack. The experiments showed that the method took 0.05s in URL deduplication, the accuracy rate was 89%, and the resource occupancy rate was also low; compared with XSSer, the number of false positives and false negatives of the designed method was smaller and the detection time was shorter. The experimental results verify the effectiveness of the vulnerability detection method designed in this study, making some contributions to its further promotion and application.
Stability of password authentication in infocommunication networks

The article discusses distributed infocommunication networks, in which the interaction of users, application servers and databases is carried out. When accessing an infocommunication network, the first procedure is to authenticate the agents through their authentication by password mechanism. It is shown that for social networks with a large number of users, widely used assessment of the security of password systems based on the calculation of the determination probability is not sufficient. The probability of the same passwords for two users with a password length of 6, 7 and 8 characters with alphabet size of 36, 42 and 57 characters and the number of users no more than 10 million is shown. An assessment of the strength of password authentication systems for info-communication networks based on the "birthday paradox" criterion is given. It has been determined that well-known social networks with a number of users comparable to the number of passwords used are not resistant to "birthday attacks". It is shown that for such systems the resistance of the password system to cracking should be assessed by m=A n/2 criterion.