Reviewerly/exHarmony huggingface dataset:
Hack Your Library: Engage Students in Information Literacy through a Technology-themed Competition

Abstract Hack Dibner is a library competition for engineering students focused on information literacy, technology, and user experience. The challenge statement was “To enhance user experience in the library through technology.” Students were allowed to participate as individuals or as teams, and were required to submit three deliverables throughout the semester: an initial concept, a written proposal, and a presentation. These deliverables required the students to perform a literature review to support their project ideas and to practice crafting and delivering effective presentations. To hold the students’ interest throughout the semester, the library scheduled five engagement activities. These ranged from librarian-hosted information literacy workshops to faculty research presentations. The written proposals and presentations were scored by a committee of judges to determine the contest winner. The success of the competition was evaluated through a focus group of student participants. In this paper we present an overview of Hack Dibner, as well as a starter kit for other libraries. A timeline of the competition, marketing materials, and contest templates are presented to help librarians organize their own version of the contest.
Designing a Deep Neural Networks Structure to Acquire the Top Level Depiction of Human Interactions

The latest research studies have really concentrated on slim complications including individual action recognition approaches utilizing depth information, 3D-skeleton information, still photo applicable info, spatiotemporal interest point-based approaches, and also human strolling proposition recognition Nevertheless, there has actually really been no methodical research study of individual action recognition. We present the scene context features that describe the atmosphere of the topic worldwide and also local levels. We design a deep neural network structure to acquire the top-level depiction of human activity combining both activity attributes as well as context features.
Generating Objects

Creating objects is a messy business. So, many object-oriented designs deal with nice, clean abstract classes, taking advantage of the impressive flexibility afforded by polymorphism (the switching of concrete implementations at runtime). To achieve this flexibility, though, I must devise strategies for object generation. This is the topic I will look at in this chapter.
INCREASING INTEREST AND STUDENT LEARNING OUTCOMES BY USING COOPERATIVE LEARNING TYPE 'MAKE A MATCH’

The purpose of this research is improve the interest and learning outcomes of student grade XI Senior High School of Muhammadiyah Pringsewu on Verb and Noun material by using cooperative learning type “Make a Match”. Data collection component obtained from the pre-test, post-test I and II, questionnaires, observations and interviews. The results showed thatthe application of cooperative learning model of “Make a Match” can increase student interest and learning outcomes XI Senior high school class Muhammadiyah Pringsewu on Verb and Noun material.
QR Code As the Delivery of Information to Universities

Wall or magazine magazines are a means of delivering information on Raharja College campus. In the delivery of information, the magazine has been widely spread in several applications of Raharja College, iRan and GreenDoc. However, this is still not optimal because the method used is still using paper. And also the lack of awareness of students will read the information on the magazine. QR codes are a type of two-dimensional matrix code or bar code developed by Denso Wave in 1994. With that, the form of information is reduced to a QR code that can store detailed information displayed on a monitor screen available at several strategic corners of the campus and scan the code on the main page of the online magazine website. The method used is the waterfall method, observation, and literature study and journal references as supporting in writing. This research was designed to make it easier to access information and attract reading interest to students of Raharja College.
Evaluation of the Implementation of Information Technology-Based Survey Practice and Hydro-Oceanographic Mapping Practices

Practice Training Survey is an activity in the teaching and learning process for one or more subjects to provide the knowledge and skills of the Hydrographic profession. The purpose of this study was to find out the implementation of the Hydro-Oceanographic Survey and Mapping Practice as a means of developing knowledge and skills for the achievement of education that would use Information Technology facilities. The method used by the kirkpatick model. This model uses four levels, namely: level of satisfaction, level of understanding, behavior change and impact produced. Thus, the implementation of Survey Practice and Mapping Practices become more effective. In order for the Implementation of the Practice Survey and Hydro-Oceanographic Mapping to be able to equip students with behaviors that support the assignment.
Artikel Administrasi Keuangan

The financial administration in school is very important to be accountable for the teaching and learning process. Accountability, reporting and inspection, and the role of teachers in the financial administration shall be liable in accordance with the prevailing rules
Smart Vision Based ATM Transaction using Deep Learning Neural Networks

The necessity of credit cards and online payment techniques become extremely popular and simple to perform because of easy and safe money handling techniques. The usage of the ATM by visually challenged people is a problem. Though there are certain features for the visually challenged users like speech instructions, there is no conformity of the amount entered or of that transacted. As a result, these people have no security, ease or comfort during the ATM transactions. So, there is a need to provide a method for the visually challenged people to effortlessly perform ATM transactions with better security. Our proposed system designed a device that can act as an aid for the visually challenged to transact in the ATM. The devised system recognizes the amount to be transacted as entered on the screen using Optical Character Recognition (OCR) and conveys it to the user via speech. After transaction, the banknotes are recognized by the system using image recognition through vital banknote feature extraction and the verification is provided regarding the amount transacted and the intended amount.
The Public Perception of the #GeneEditedBabies Event Across Multiple Social Media Platforms: Observational Study (Preprint)

<sec> <title>BACKGROUND</title> In November 2018, a Chinese researcher reported that his team had applied clustered regularly interspaced palindromic repeats or associated protein 9 to delete the gene &lt;i&gt;C-C chemokine receptor type 5&lt;/i&gt; from embryos and claimed that the 2 newborns would have lifetime immunity from HIV infection, an event referred to as #GeneEditedBabies on social media platforms. Although this event stirred a worldwide debate on ethical and legal issues regarding clinical trials with embryonic gene sequences, the focus has mainly been on academics and professionals. However, how the public, especially stratified by geographic region and culture, reacted to these issues is not yet well-understood. </sec> <sec> <title>OBJECTIVE</title> The aim of this study is to examine web-based posts about the #GeneEditedBabies event and characterize and compare the public’s stance across social media platforms with different user bases. </sec> <sec> <title>METHODS</title> We used a set of relevant keywords to search for web-based posts in 4 worldwide or regional mainstream social media platforms: Sina Weibo (China), Twitter, Reddit, and YouTube. We applied structural topic modeling to analyze the main discussed topics and their temporal trends. On the basis of the topics we found, we designed an annotation codebook to label 2000 randomly sampled posts from each platform on whether a supporting, opposing, or neutral stance toward this event was expressed and what the major considerations of those posts were if a stance was described. The annotated data were used to compare stances and the language used across the 4 web-based platforms. </sec> <sec> <title>RESULTS</title> We collected &amp;gt;220,000 posts published by approximately 130,000 users regarding the #GeneEditedBabies event. Our results indicated that users discussed a wide range of topics, some of which had clear temporal trends. Our results further showed that although almost all experts opposed this event, many web-based posts supported this event. In particular, Twitter exhibited the largest number of posts in opposition (701/816, 85.9%), followed by Sina Weibo (968/1140, 84.91%), Reddit (550/898, 61.2%), and YouTube (567/1078, 52.6%). The primary opposing reason was rooted in ethical concerns, whereas the primary supporting reason was based on the expectation that such technology could prevent the occurrence of diseases in the future. Posts from these 4 platforms had different language uses and patterns when they expressed stances on the #GeneEditedBabies event. </sec> <sec> <title>CONCLUSIONS</title> This research provides evidence that posts on web-based platforms can offer insights into the public’s stance on gene editing techniques. However, these stances vary across web-based platforms and often differ from those raised by academics and policy makers. </sec>
Outlook

Abstract The aforementioned representation learning models and methods have shown their effectiveness in various NLP scenarios and tasks. With the rapid growth of data scales and the development of computation devices, there are also new challenges and opportunities for next-stage researches of deep learning techniques. In the last chapter, we will look into the future directions of representation learning techniques for NLP. To be more specific, we will consider the following directions including using more unsupervised data, utilizing few labeled data, employing deeper neural architectures, improving model interpretability and fusing the advantages of other areas.
Early Detection of Sepsis using Machine Learning

Sepsis is a global cause of the death due to infection and subsequent overreaction of the immune system. Mortality rates are highest in developed and developing countries in cases of septic shock. Sepsis is a clinical condition with an emergency referral that can be avoided by advance warning. SIRS is a normal immune response to any infection, and hospitals or antibiotics are not required by most people. Early sepsis prediction is possibly life-saving, and we are planning to predict sepsis 6 hours before clinical sepsis diagnosis. We used two types of Standard Scalar and Min Max Scalar pre-treatment methods to pre-treat the data. The Recursive Feature Elimination (RFE) method is used to pick the features most closely related to the predictive or efficiency factor. The ML algorithms used are the Logistic Regression algorithm and XGboost. Cross-validation 10 times with the train splitting method is used to validate attributes. we selected the best model from these two trained models.
Foreword

SyntaxVolume 22, Issue 2-3 p. 113-115 Special Issue on Information Structure, Argument Structure, and Their Interfaces Foreword Ángel L. Jiménez-Fernández, Corresponding Author Ángel L. Jiménez-Fernández Guest editor ajimfer@us.es Search for more papers by this author Ángel L. Jiménez-Fernández, Corresponding Author Ángel L. Jiménez-Fernández Guest editor ajimfer@us.es Search for more papers by this author First published: 13 August 2019 https://doi.org/10.1111/synt.12185Read the full textAboutPDF 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 No abstract is available for this article. Volume22, Issue2-3Double Special Issue: Information Structure, Argument Structure, and Their InterfacesSeptember 2019Pages 113-115 RelatedInformation
Facets of Aspect Oriented Programming

AOP-Aspect Oriented Programming is a new programming paradigm for separating crosscutting concerns that are generally hard to do in object-oriented programming. As AOP has better ability to handle crosscutting concerns than Object-Oriented Programming (OOP,) it supports to write more modularized and more sustainable code. In addition, numerous publications discuss about the advantages of AOP design and implementation. However, for this new programming paradigm the work is in its early stages. The paper is all about the surveyed and reviewed several facets of AOP.
Proceeding Copyright

Abstract Applied Technology (ICEAT) List of Licence terms and conditions, Statement of Peer Review are available in this pdf.
Penerapan Model Quantum Teaching untuk Meningkatkan Hasil Belajar Siswa Kelas IV Sekolah Dasar

This study aims to describe the application of the Quantum Teaching model to improve student learning outcomes in social studies learning. This research is a classroom action research that uses qualitative and quantitative approaches. The subjects of this study were 28 teachers and fourth grade students. The implementation of this research was carried out in two cycles with research procedures consisting of planning, implementation, observation and reflection. The results of research was improve a) RPP cycle I 83.9% and cycle II 92.8%. b) Implementation of teacher aspects and aspects of students cycle I 80.5% and cycle II 94.4%, c) Student learning outcomes cycle I 78.5 and cycle II 87. Thus, the application of the Quantum Teaching model can improve learning outcomes students in social studies learning in Grade IV SD Negeri 08 Pisang Kota Padang.
Baofeng Energy awards contracts to KBR for Chinese methanol-to- olefins project

This paper investigates whether computer forensic tools (CFTs) can extract complete and credible digital evidence from digital crime scenes in the presence of file system anti-forensic (AF) attacks. The study uses a well-established six stage forensic tool testing methodology based on black-box testing principles to carry out experiments that evaluate four leading CFTs for their potential to combat eleven different file system AF attacks. Results suggest that only a few AF attacks are identified by all the evaluated CFTs, while as most of the attacks considered by the study go unnoticed. These AF attacks exploit basic file system features, can be executed using simple tools, and even attack CFTs to accomplish their task. These results imply that evidences collected by CFTs in digital investigations are not complete and credible in the presence of AF attacks. The study suggests that practitioners and academicians should not absolutely rely on CFTs for evidence extraction from a digital crime scene, highlights the implications of doing so, and makes many recommendations in this regard. The study also points towards immediate and aggressive research efforts that are required in the area of computer forensics to address the pitfalls of CFTs.
Students’ Motivation in Reading English Text: A Survey of Junior High School in Palembang

This study investigated students’ reading motivation in English text. The Quantitative research methodology carried out in this study is in order to collect information or data that is donated. Researcher used a survey with descriptive analysis that is research whose source of data and information is mainly obtained from respondents as a research sample using questionnaires as an instrument of data collection to describe students reading motivation of junior high school in Palembang. This study was conducted at SMP N 7 Pemulutan with 104 as the participants taken from the nine grade students of that school by using simple random sampling. in collecting data, the researcher used Motivation Reading Questionnaire (MRQ). The questionnaire consisted of 53 items with eleven indicators. The result covers 1. Self efficacy can make students more motivated in reading. 2. Intrinsic factor included enjoyable and students’ interest in reading. 3. Extrinsic factor covered such as for finishing assignment, for getting high getting praises, in getting high score.
RESTful Web Services Development in Situation-Oriented Databases

New features RESTful web services development, envisaged in the situation-oriented databases (SODB), are considered.SODB is a heterogeneous data integrator driven by an embedded hierarchical situational model (HSM), in which virtual documents are mapped onto heterogeneous physical data.Microservices and microservice architecture are discussed in terms of the benefits of scaling and modifying web applications.Elements of the situational model that define HTTP-request processing are considered in terms of access to request properties and attached data based on the concept of virtual documents.An HTTP-request processing design pattern developed to work with relational database tables for which data sources are external web services is discussed.The structure of the HSM-model, which performs selective processing depending on the type of request, is discussed in detail for HTTP-request methods GET and POST.An example of the practical implementation of microservices based on SODB for the problem of monitoring student views of educational videos on YouTube is given.
Power Management as a Service (Pmaas) – An Energy Saving Service by “Auto-Fit VM Placement” Algorithm in Cloud Computing for Maximum Resource Utilization at Minimum Energy Consumption Without Live-Migrating the Virtual Machines by using the Concept of Virtual-Servers

Now a day Energy Consumption is one of the most promising fields amongst several computing services of cloud computing. A maximum amount of Power resources are absorbed by the data centre because of huge amount of data processing which is increased abnormally. So it’s the time to think about the energy consumption in cloud environment. Existing Energy Consumption systems are limited in terms of virtualization because improper virtualization leads to loads imbalance and excessive power consumption and inefficiency in terms of computational power. Billing[1,2 ] is another exciting feature that is closely related to energy consumption, because higher or lesser billing depends on energy consumption somehow-as we know that cloud providers allow cloud users to access resources as pay-per-use, so these resources need to be optimally selected to process the user request to maximize user satisfaction in the distributed virtualized environment. There may be an inequity between the actual power consumption by the users and the provided billing records by the providers, So any false accusation that may claimed by each other to get illegal compensations. To avoid such accusation, we propose a work to consolidate the VMs using the Power Management as a Service (PMaaS) model in such a way, to reduce power consumption by maximum resource utilization without live-migration of the virtual machines by using the concept of Virtual Servers. The proposed PMaaS model uses a new “Auto-fit VM placement algorithm”, which computes tasks resource demands, models a Virtual Machine that fits those demands, and places the Virtual Machines on a Virtual server made by the collective resources (CPU, Memory, Storage and Bandwidth) from the respective schedulers directly connected to the actual physical servers and that has the minimum remaining resources which is large enough to accommodate such a Virtual Machine.
An Efficient Data Segmentation and Replication Technique for Cloud using Fuzzy Centrality Measures

Cloud computing is a creating worldview to give reliable and resilient infrastructure permitting the clients (data proprietors) to store their data and the data purchasers (clients) can get to the data from cloud servers. This worldview decreases storage and maintenance cost of the data proprietor. Notwithstanding, cloud data storage still offers ascend to security related issues. In the event of shared data, the data face both cloud-explicit and insider threats. In this work, we propose fuzzy centrality measure based division and replication of data in the cloud for perfect execution and security that consider both security and execution issues. In our framework, we separate a data records and imitate the isolated data over the cloud center points utilizing fuzzy centrality measures. Every one of the nodes stores just a solitary data fragment of a particular data document that guarantees that even if there should arise an occurrence of a fruitful attack, no significant information is uncovered to the attacker. In addition, the cloud nodes storing the data fragments, are separated with certain distance by methods for altered fuzzy T-coloring to prohibit an attacker of predicting the locations of the fragments. We likewise contrast the exhibition of the our methodology and other standard replication plans. The greater amount of security with improved performance was observed.
Response time-based resource allocation according to service level agreements in cloud computing

Cloud computing is a technology which offers various services as and when required by the user through various cloud providers. The scalable nature of cloud has made it to reach various domains and have a strong root in every organisation. The resource provisioning has become a challenging task for many cloud providers. This work proposes an efficient framework for handling storage, application and computation services, offering service level agreements (SLA) backed performance and uptime promises for their services in cloud computing. Further, this tries to benefit both the users as well as cloud providers by enhancing the features for the customers and by gaining profit for the providers. The proposed SLA-based resource provisioning system is found to perform better than the existing other resource provisioning systems in terms of response time and other QoS parameters.
Improvement of straight running stability of 3-wheeled wheelchair with an active-caster

Recently, simplified electric wheelchairs, that is, wheelchair with a motorized device attached to a manual wheelchair has been gathered attention. Simplified electric wheelchairs are relatively lightweight. We developed the 3-wheeled simple electric wheelchair. This wheelchair has two large wheels and an active-caster, a type of powered caster which can move in any directions. With this structure, the active-caster saves as a support, the risk of falling backwards can be reduced when the wheelchair running over steps. However, 3-wheeled simple electric wheelchair have a problem that stability of straight running is poor. This is because 3-wheeled wheel chair has the same relative positional relationship between the wheelchair operator and the turning center as front-drive wheelchair. In previous studies, yaw rate feedback control was used to solve this problem. So in this paper, we introduce the control to 3-wheel simple electric wheelchair and improve the running stability of the wheelchair.