Reviewerly/exHarmony huggingface dataset:
URGENSI KOMPETENSI KOMUNIKASI ILMIAH PUSTAKAWAN UNTUK PROGRAM PENGEMBANGAN LAYANAN PERPUSTAKAAN

The purposes of this study are to know: (1) the urgencies of librarian’s scholarly communication; (2) competence of librarian's scholarly communication; and (3) library’s scholarly communication programs. The data type of this study is descriptive - qualitative. The data source for this study is a literature review. The study results showed that scholarly communication is a core competency of librarians who could help library service development programs. These core competencies include the ability of librarians to implement the digital literacy and scientific literacy programs in the library, such as user education, publications or research, education or training, focus group discussions, scientific meetings, and research corner services. As a recommendation, the librarian's institutions (especially academic libraries and research institutions) should arrange the librarian's scientific competency development programs
ANILISIS IMAGE QUALITY CT SCAN THORAX DENGAN VARIASI LUNG WINDOW KERNEL PADA MSCT SIEMENS SOMATOM EMOTION 6 IMAGE QUALITY ANALYSIS CT SCAN THORAX LUNG WINDOWS WITH KERNEL VARIATIONS USING MSCT SIEMENS SOMATOM EMOTION 6

Background: To be able to show the Lung anatomy in detail in CT Scan Thorax lung window then required a sharp image quality. One way to improve image sharpness is to use kernel settings. The purpose of research is to know the difference of the quality of anatomical image with kernel variation CT Scan Thorax Lung Window and know the proper kernel selection to produce CT scan of thorax lung windows the best Methods: Type of research is an experiment. The study was conducted using a CT image scan of thorax on axial lung window slices in cases of lung tumors in the kernel B50s, B60s, B70s, B80s, and U90s. The research was conducted by measuring the CT image quality of thorax scan on the windows lung by way of questionnaire assessment to 5 radiologist as the observer to CT Scan image to determine the level of clarity of anatomical criteria. Results: The results showed that there were significant differences in the quality of anatomical imagery with kernel variation of B50s, B60s, B70s, B80s, U90s with p-value &lt;0.05. CT images can thorax lung windows that have the best anatomical image quality of the samples taken are shown by the use of the kernel U90s. Conclusions : There are significant differences in the quality of anatomical imagery with kernel variation of B50s, B60s, B70s, B80s, U90s. The kernel that generates image detail for CT thorax lung windows is the U90s kernel
A New Design for Smart and Decentralized Approach for Resource Allocation in Cloud Computing using CSP Model

Cloud computing is the latest technology in both hardware and software.The cloud computing architecture offers a number of services including the SAAS, PAAS and IAAS.When customers specify their technical and economic needs, cloud computing helps them satisfy their request at the lowest possible cost and the best quality of resources.This paper presents a new approach for resource allocation (RA) in cloud computing.Its architecture is based on multi-agent system (MAS) and distributed constraint satisfaction problems (DCSP) where variables and constraints are distributed among multiple agents.In MAS, each agent makes his choice via a distributed negotiation to satisfy the global objective which is looking for the best solution to the users' needs.The present work highlights a new approach that is based on hybridizing (DCSP) and (MAS).This decentralized approach is designed to solve a number of problems such as resource allocation and planning cloud-computing systems.
Study on Electromagnetic Visualization Experiment System Based on Augmented Reality

When learning physics, electromagnetism is one of the most difficult concepts for students to understand. This paper proposes a real time visualization method for 3D magnetic field based on the augmented reality (AR) technology, which can not only visualize magnetic flux lines in real time, but also simulate the approximate sparse distribution of magnetic flux lines in space. An application utilizing the proposed approach is also presented, which permits students to freely and interactively move the magnets in 3D space and observe the magnetic flux lines in real time. An experiment is conducted to evaluate the application and its result shows that the application utilizing the proposed method can visualize the invisible physical phenomenon of 3D magnetic field, which has significant supplemental learning effects for students.
Ways to Improve the Training of Future Educators to Health-Saving Activities

The peculiarities of students’ learning activity organization based on partnership during the course "Theory and Methodology of Physical Training of Pre-school Children" are observed. The intensification of learning activity of students is determined as the main mechanism of vocational training optimization. Cooperation of the teacher and students during lectures, practical lessons, self-studies gives an opportunity to found the base of job-related abilities and experience in the field of physical training of pre-school children. Teaching based on partnership using different interactive methods of teaching reflects student-centred results-based paradigm based on competency-based approach. Educational activity organization based on interaction, applying methods of actualization of the students’ reference knowledge and ideas, methods of getting new knowledge, practical skills and abilities formation, generalization, methods of knowledge arrangement, organization of self-reflection of cognitive activity makes it possible to improve vocational training&nbsp; of a specialist who would be able to solve unusual professional tasks and have a creative attitude to life. Only understanding by future specialists of rich theoretical and practical potential of physical training, proficient awareness of methodology of physical training of pre-school children by specialists, their readiness to realize health-improving paradigm in their own career will allow to provide effective practical experience in circumstances of student-centred pedagogical model.
STRATEGIES TO IMPROVE QUALITY OF DATA DISSEMINATION WEBSITE: A CASE STUDY OF THE CENTRAL BUREAU OF STATISTICS

E-government facilitates the use of Information Technology to establish government public services.A common feature of e-government is a Website as public portal.One of prominent institutions in Indonesia, which is obliged to provide the Website is the Central Bureau of Statistics.However, a data requirement survey by the Central Bureau of Statistics in 2017 indicated a gap between user expectation and user satisfaction of the Website.Besides, an assessment by the Open Data Inventory (ODIN) indicated that the Website has not met the international Website quality criteria, especially data completeness and data openness measures.To address this problem, a research was conducted to investigate its shortcomings and propose strategies for improvement.The data were collected using questionnaires, which were grouped into the Importance Performance Analysis (IPA) matric quadrants.It was followed by literature studies and interviews with experts in statistical Website to propose improvement strategies.The priority of strategies was compiled using the Quality Functional Deployment (QFD).The results show that the Central Bureau of Statistics are required to optimize the Website code, redesign the Website layout, create statistical data forum, conduct statistical capacity building, and improve the data interoperability.Lesson learned from this research and its findings are potential to be adopted in other emerging economies, which strive to provide qualified data on e-government Websites to their citizens.
A user study to compare two conversational assistants designed for people with hearing impairments

Participating in conversations can be difficult for people with hearing loss, especially in acoustically challenging environments.We studied the preferences the hearing impaired have for a personal conversation assistant based on automatic speech recognition (ASR) technology.We created two prototypes which were evaluated by hearing impaired test users.This paper qualitatively compares the two based on the feedback obtained from the tests.The first prototype was a proof-of-concept system running real-time ASR on a laptop.The second prototype was developed for a mobile device with the recognizer running on a separate server.In the mobile device, augmented reality (AR) was used to help the hearing impaired observe gestures and lip movements of the speaker simultaneously with the transcriptions.Several testers found the systems useful enough to use in their daily lives, with majority preferring the mobile AR version.The biggest concern of the testers was the accuracy of the transcriptions and the lack of speaker identification.
Improving Students’ Reading Comprehension through Guessing Strategy

The purposes of this research were: to describe the students’ reading comprehension through guessing strategy and to identify the factors which influenced students’ reading comprehension through guessing strategy at Grade XI MAS Darul Istiqomah Hutapadang - Pijorkoling. This research used classroom action research consisted of two cycles. Moreover, the participants of this research were the class of XI (19 students) and there was collaboration with an English teacher. Meanwhile, the data was derived from reading comprehension tests, observation, and interview. Students’ score in cycle 1 was 62.24 (4%) and students’ score in cycle 2 was 78.68 (79%). Based on the research result in cycle 1 and cycle 2, it showed the improvement of students’ mean score and students’ percentage. So, students’ improvement in reading comprehension through guessing strategy was good category (high).
Enhanced biologically inspired model for image recognition based on a novel patch selection method with moment

Biologically inspired model (BIM) for image recognition is a robust computational architecture, which has attracted widespread attention. BIM can be described as a four-layer structure based on the mechanisms of the visual cortex. Although the performance of BIM for image recognition is robust, it takes the randomly selected ways for the patch selection, which is sightless, and results in heavy computing burden. To address this issue, we propose a novel patch selection method with oriented Gaussian–Hermite moment (PSGHM), and we enhanced the BIM based on the proposed PSGHM, named as PBIM. In contrast to the conventional BIM which adopts the random method to select patches within the feature representation layers processed by multi-scale Gabor filter banks, the proposed PBIM takes the PSGHM way to extract a small number of representation features while offering promising distinctiveness. To show the effectiveness of the proposed PBIM, experimental studies on object categorization are conducted on the CalTech05, TU Darmstadt (TUD) and GRAZ01 databases. Experimental results demonstrate that the performance of PBIM is a significant improvement on that of the conventional BIM.
Robust Visual Tracking via Multiple Experts With Correlation Filters

As one of the key components in many computer vision applications, visual tracking has been widely investigated in recent years. Correlation filter-based trackers have achieved compelling performance in terms of both efficiency and accuracy by speeding up online training and inference procedures in the frequency domain. For a visual object, such trackers often perform tracking by searching the most correlated patch within a limited search region in a new frame. The acknowledged problem is that a small search region prohibits the successful tracking of fast moving targets while a large search region increases the difficulty of model learning. In this paper, we propose to use different candidate search regions to train multiple tracking experts to alleviate this dilemma. Based on these experts, the final tracker learns to make the optimal decision using a decision-theoretic online learning approach. Besides, we also establish multi-scale experts to handle scale variations during tracking. The experimental results on the public datasets demonstrate that the proposed approach achieves favorable performance against several state-of-the-art methods.
Collecting and analyzing multidimensional data with local differential privacy

Local differential privacy (LDP) is a recently proposed privacy standard for collecting and analyzing data, which has been used, e.g., in the Chrome browser, iOS and macOS. In LDP, each user perturbs her information locally, and only sends the randomized version to an aggregator who performs analyses, which protects both the users and the aggregator against private information leaks. Although LDP has attracted much research attention in recent years, the majority of existing work focuses on applying LDP to complex data and/or analysis tasks. In this paper, we point out that the fundamental problem of collecting multidimensional data under LDP has not been addressed sufficiently, and there remains much room for improvement even for basic tasks such as computing the mean value over a single numeric attribute under LDP. Motivated by this, we first propose novel LDP mechanisms for collecting a numeric attribute, whose accuracy is at least no worse (and usually better) than existing solutions in terms of worst-case noise variance. Then, we extend these mechanisms to multidimensional data that can contain both numeric and categorical attributes, where our mechanisms always outperform existing solutions regarding worst-case noise variance. As a case study, we apply our solutions to build an LDP-compliant stochastic gradient descent algorithm (SGD), which powers many important machine learning tasks. Experiments using real datasets confirm the effectiveness of our methods, and their advantages over existing solutions.
Improved CF based prediction technique for recommendation systems

Any eCommerce websites use recommendation system to recommend items to users. Collaborative filtering is a technique to recommend an item to the customers by understanding the past behavior of the same user and other similar users. The accuracy of the recommendation system is a major issue while recommending items to users. In this paper a research is done to propose a new system to predict ratings for items for the users by finding similarity between the users. Similarity between the users is found by analyzing the previous history of the users for rating items. A similarity matrix is created that store a similar weight between users. Similar users are selected if the similarity weight between the users is found greater than a similarity threshold. The proposed system is implemented on a data set and the quality of the proposed system is analyzed by comparing the value of mean absolute error (MAE). The experimental results are found better than some other existing techniques. The value of MAE is approximate 11% better and value of RMSE is 15% better as compared to existing algorithms.
The Students’ Attitude Towards English Classroom Environment of Madrasah Tsanawiyah Negeri Model Makassar 2018/2019

This research aims to find out the students’ attitude toward English classroom environment especially English teacher, English material and English classroom management. This research used descriptive method to find out the student’s attitude toward English teacher, English material and English classroom environment. The population of this research was the second-year students MTS Negeri Model Makassar. The sample technique of this study was random sampling which consists of 50 students.The instrument of this research was questionnaire by using mean score to find out the mean score of them xˉ=n1(x1+x2+50+xn). The result of data analysis of the questionnaire indicated that the students have positive attitude toward English teacher (59. 24 %), the students have positive attitude towards English material (53. 64 %) and the students have neutral attitude toward English classroom management (39%).
Configuration and Monitoring of the Optical Physical Layer Using Software-Defined Tools

Get PDF Email Share Share with Facebook Tweet This Post on reddit Share with LinkedIn Add to CiteULike Add to Mendeley Add to BibSonomy Get Citation Copy Citation Text Y. Verbishchuk, C. Sreenan, and F. Gunning, "Configuration and Monitoring of the Optical Physical Layer Using Software-Defined Tools," in OSA Advanced Photonics Congress (AP) 2019 (IPR, Networks, NOMA, SPPCom, PVLED), OSA Technical Digest (Optica Publishing Group, 2019), paper NeT1D.2. Export Citation BibTex Endnote (RIS) HTML Plain Text Citation alert Save article
Integrated system for control of soil moisture and local weather conditions for remote sensing data interpretation

Research Institute (biopolygon of ARI) in 2018 are reported.The complex spatial attribute information was transmitted into the database of the GIS-ARI and was used for remote sensing data interpretation in the experiments on the precision crop production.
MANFAAT LIDAH BUAYA SEBAGAI MASKER UNTUK PERAWATAN KULIT TANGAN KERING

Abstract&#x0D; The purpose of this study was to analyze the effect of the use of Aloe Vera to overcome dry hand with different frequency of use. This research is an experimental study, the method used is quasi-experimental, the number of samples is 9 people each of three people for each group. Control group (X1) without the use of aloe vera, experimental group 1 (X2) with a frequency of 1 x three days, and experimental group 2 (X3) with a frequency of 1 x 7 days. Data analysis using Analysis of Variance (ANOVA), followed by Duncan test if there are significant differences in the results of analysis of variance. The results showed that 1) There was no change in the level of dry skin moisture in the control group 2) There was a change in the skin moisture level of the experimental treatment group 1 (X2) with the use of Aloe Vera 1 time 3 days, 3) A change in the moisture level of the hand skin dry in the experimental treatment group 2 (X3) with the use of Aloe Vera 1 time 7 days, 4) There were differences in the effect of dry hand care using Aloe Vera with three different treatments and treatment groups with a frequency of 1 time in 3 days had the best results.&#x0D;
Automatic detection of plan symbols in railway equipment engineering using a machine learning approach

Exact data in the form of technical drawings and plans of built assets are a significant requirement for the successful operation and reconstruction of such assets.When the consistency between this data and the real world situation cannot be assured, the data is not reliable and needs to be updated by comparing plans and reality.Depending on the size and number of assets this may involve an enormous amount of manual effort.In the scope of this research, an approach for supporting and automating such a process by utilizing concepts developed in the field of machine learning was developed.This paper focuses on the interpretation of technical drawings in terms of detecting and classifying plan symbols as this is a time intensive and error prone process when done manually.It is described how the capabilities of Convolutional Neural Networks are employed in analyzing images to automatically detect important plan symbols in the field of Train Traffic Control and Supervision Systems and how those networks are trained without the need for a time consuming-manual labeling process.
Archetype-Based Modeling and Search of Social Media

Existing keyword-based search techniques suffer from limitations owing to unknown, mismatched, and obscure vocabulary. These challenges are particularly prevalent in social media, where slang, jargon, and memetics are abundant. We develop a new technique, Archetype-Based Modeling and Search, that can mitigate these challenges as they are encountered in social media. This technique learns to identify new relevant documents based on a specified set of archetypes from which both vocabulary and relevance information are extracted. We present a case study from the social media data from Reddit, by using authors from /r/Opiates to characterize discourse around opioid use and to find additional relevant authors on this topic.
Hybrid Variational Predictive Coding as a Bridge between Human and Artificial Cognition

Predictive coding and its generalization to active inference offer a unified theory of brain function. The underlying predictive processing paradigmhas gained significant attention in artificial in...
Network Performance Criteria for Telecommunication Traffic Types driven by Quality of Experience

A common reason for changing the chosen service provider is the users' perception of service. Quality of Experience (QoE) describes the end user's perception of service while using it. A frequent cause of QoE degradation is inadequate traffic routing, where, other than throughput, selected routes do not satisfy minimum network requirements for the given service or services. In order to enable QoE-driven routing, per traffic type defined routing criteria are required. Our goal was to obtain those criteria for relevant services of a telecom operator. For the purpose of identifying services of interest, we first provide short results of user traffic analysis within the telecom operator network. Next, our work presents testbed measurements which explore the impact of packet loss and delay on user QoE for video, voice, and management traffic. For video services, we investigated separately multicast delivery, unicast HTTP Live Streaming (HLS), and unicast Real Time Streaming Protocol (RTSP) traffic. Applying a threshold to QoE values, from the measured dependencies we extracted minimum network performance criteria for the investigated different types of traffic. Finally, we provide a comparison with results available in the literature on the topic.
Volcanic hazards in the Pacific U.S. Territories

First posted July 19, 2019 For additional information, contact: Director,Volcano Science CenterU.S. Geological Survey4210 University DriveAnchorage, AK 99508 The Commonwealth of the Northern Mariana Islands, Guam, and American Samoa lie along the western side of the famed Pacific Ring of Fire. Here, the processes of active island and submarine volcanoes produce activity both underwater and in the atmosphere that poses potential hazards to the daily lives of residents and travelers. Since 2000, CNMI volcanoes have erupted six times, and one submarine volcano has been active in American Samoa.
Metode Pengenalan Tempat Secara Visual Berbasis Fitur CNN untuk Navigasi Robot di Dalam Gedung

Place recognition algorithm based-on visual sensor is crucial to be developed especially for an application of indoor robot navigation in which a Ground Positioning System (GPS) is not reliable to be utilized. This research compares the approach of place recognition of using learned-features from a model of Convolutional Neural Network (CNN) against conventional methods, such as Bag of Words (BoW) with SIFT features and Histogram of Oriented Uniform Patterns (HOUP) with its Local Binary Patterns (LBP). This research finding shows that the performance of our approach of using learned-features with transfer learning method from pre-trained CNN AlexNet is better than the conventional methods based-on handcrafted-features such as BoW and HOUP.
Pre-irresolute Functions in Closure Spaces

The preopen sets are used to define pre-open functions, preclosed functions, pre-continuous functions, contra-pre-continuous functions and pre-irresolute functions which are investigated. They are also used to introduce a new type of connectedness and compactness in closure spaces, they called p-connectedness and p-compactness respectively.