Reviewerly/exHarmony huggingface dataset:
Practice and thinking on constructing a scientific research system for regional liver pathology center under the concept of collaborative innovation

Objective  To investigate the influence of the concept of collaborative innovation on the construction of a scientific research system for regional liver pathology center from multiple perspectives, and to explore its application significance. Methods  A total of 1246 liver biopsy specimens which were examined in Department of Pathology in Wuxi Second People's Hospital and Wuxi Fifth People's Hospital from January 2014 to September 2020 were collected, among which the specimens examined before the founding of the regional liver pathology center were collected as nI group, and those examined after the founding of the center were collected as nII group. According to the examination time of the first, second, or third year after founding, the nII group was further divided into nIIa group, nIIb group, and nIIc group. A multi-perspective analysis was performed based on five indices, i.e., number of liver biopsy specimens, growth rate of liver biopsy specimens, growth rate of internal collaborative departments, growth rate of external collaborative units, and evaluation of the collaborative and innovative scientific research system. Results  The growth rate of liver biopsy specimens in the nI group was 15.51%; after the founding of the regional liver pathology center, the highest growth rate of 187.76% was observed in the nIIa group, and a relatively stable growth rate of 76.35% was observed in the nIIb group. There was a gradual increase in the number of specimens in internal collaborative departments, with a growth rate of 50% in the nIIa group and 83.33% in the nIIb group, while the number of external collaborative units increased steadily, with a growth rate of 100% in the nIIa group and 50% in the nIIb group. The nII group showed a diversified increasing trend in the evaluation indices of the scientific research system. Conclusion  It is a new perspective for the construction of regional disciplinary scientific research system to grasp the opportunity of policy-supported development and innovate the effective cooperation mode between internal departments and external units under the concept of collaborative innovation.
Efektivitas Penggunaan Aplikasi Quizizz Dalam Proses Pembelajaran Bahasa Inggris Bagi Mahasiswa

One of learning application that is commonly used in doing quizzes is Quizizz. The purpose of this research was to determine student perceptions of the effectiveness of using the Quizizz application in English courses. This research used a mixed method, namely quantitative method and qualitative method. The data collection method used was a questionnaire. Quantitative data collection was obtained with closed questions and qualitative data was collected with open questions. The conclusion of this research was that the use of the Quizizz application in general has a positive impact on the process of learning English. Based on student perceptions, the Quizizz application is a learning application that is fun, effective, not boring, varied, challenging, simple, and can be used anywhere. However, the weakness of this Quizizz application is that it must have stable internet usage. There were also comment from student who hoped that more lecturers would use the Quizizz application in the learning process on a regular basis.
ORAL QUIZ EFFECT ON STUDENTS SPEAKING SKILL

The objective of this research was to know the effect of oral quiz toward students’ speaking ability at the eleventh grade students of SMA Negeri 2 Lakudo. This study is pre-experimental in nature, with a single group pretest and posttest design and no control groups. The participants in this study were eleventh-grade students from SMA Negeri 2 Lakudo, a school with 168 students organized into five classes. The sample of this study was taken by using cluster sampling which consisted of 30 students. The instrument that is used in this research was oral test. The data suggest that oral quizzes have a considerable impact on students' speaking abilities in SMA Negeri 2 Lakudo eleventh grade pupils. The value of t test = 12.39, which was consulted to the t table at a significant level of 0.05 with the standard and degree of freedom (df) = 29, revealed that ttable=1.699. ttest= 12.39 &gt; ttable = 1.699, according to this value. As a result, Ho is denied, whereas H1 is approved. It means that oral quizzes have a big impact on learning English at a higher level.
UTILIZING FEATURETOOLS IN AUTOMATICALLY CREATING FEATURE ENGINEERING

Back in the time when the technological knowledge has bloom into the 21st century, technology has become one of the solutions that have been focused especially in using the machine learning to help the human making a better decision making. In the machine learning, there are feature engineering process where this method has evolved extensively in construction of novel features from the data provided within the goals to improvise the predictive learning performance. This process has been performed manually because it relies on the human domain knowledge as it a time�consuming factor that are used during the project of data science workflow. In this project, presence of the framework called Featuretools helps to automatically perform feature engineering a set of related tables. The open-source Python library explores the various feature construction choices based on the method known as Deep Feature Synthesis. Additionally, the deep feature synthesis stacks of multiple transformation and aggregation operation called Feature Primitives, to create features from data spread across many tables. In the other hand, the system allow user to specify domain or data specific choices to prioritize the exploration. The implementation of automation on feature generation was a success. Using the concept can perform deep feature synthesis to create new features and functions applied to one or more columns in a single table or to build new features from multiple tables. The output for the project is to obtain the recognition of utilizing automated feature engineering with features compare to the manual way for the data analysis and machine learning pipelines.
Software Development Environment : the DevOps perspective

DevOps is a collaborative effort based on a set of practices and cultural values developed in order to improve software quality and release cycle while operating at the lowest cost possible. To ena ...
Reframing the artificial intelligence concept

This chapter seeks to analyses the legal definitions of artificial intelligence. The artificial intelligence concept was shaped by the scientific community that created the field. However, as artificial intelligence has sparked the attention of the legal community, most scholars have preferred to ‘skip’ the process of redefining terminology, adopting instead whichever conceptions of the scientific vocabulary they believe preferable in a given discussion. The third chapter outlines the various definitions and approaches for the term ‘artificial intelligence’ and offers new terminology for that legal concept.
A dictionary learning algorithm for compression and reconstruction of streaming data in preset order

&lt;p style='text-indent:20px;'&gt;There has been an emerging interest in developing and applying dictionary learning (DL) to process massive datasets in the last decade. Many of these efforts, however, focus on employing DL to compress and extract a set of important features from data, while considering restoring the original data from this set a secondary goal. On the other hand, although several methods are able to process streaming data by updating the dictionary incrementally as new snapshots pass by, most of those algorithms are designed for the setting where the snapshots are randomly drawn from a probability distribution. In this paper, we present a new DL approach to compress and denoise massive dataset in real time, in which the data are streamed through in a preset order (instances are videos and temporal experimental data), so at any time, we can only observe a biased sample set of the whole data. Our approach incrementally builds up the dictionary in a relatively simple manner: if the new snapshot is adequately explained by the current dictionary, we perform a sparse coding to find its sparse representation; otherwise, we add the new snapshot to the dictionary, with a Gram-Schmidt process to maintain the orthogonality. To compress and denoise noisy datasets, we apply the denoising to the snapshot directly before sparse coding, which deviates from traditional dictionary learning approach that achieves denoising via sparse coding. Compared to full-batch matrix decomposition methods, where the whole data is kept in memory, and other mini-batch approaches, where unbiased sampling is often assumed, our approach has minimal requirement in data sampling and storage: i) each snapshot is only seen once then discarded, and ii) the snapshots are drawn in a preset order, so can be highly biased. Through experiments on climate simulations and scanning transmission electron microscopy (STEM) data, we demonstrate that the proposed approach performs competitively to those methods in data reconstruction and denoising.&lt;/p&gt;
A Study on the Development of a Measuring Instrument of Educational Service Quality for the Department of Airline Services Using Delphi Method

This study aims to develop the measuring instrument of the educational service quality that can be applied to the department of airline services in universities, and reveal the dimensions that reflect the characteristics of the department of airline services in universities. To achieve the purpose of this study, the initial measuring instrument of the education service quality was derived through the thorough analysis of the previous studies, and the contents of the measuring instrument were developed through conducting three rounds of Delphi surveys. The results showed that the educational service quality factors in the department of airline services were identified 7 dimensions and 42 items which were global support factors, employment support factors, education factors, professor factors, reputation factors, environmental factors, and department management factors.<BR> This study suggests the direction of education that the department of airline services should aim for, and provides implications for efficient department operation to improve the department of airline services’ specialty and educational service quality in the future.
Water Security During the Covid-19 Pandemic in Sentul City

This research was conducted to determine the state of the water in Sentul City. The method used in this research is observation, interview and water measurement. The results showed that Sentul area has five soil classifications, namely typic hapludult, typic dystropept, oxic dystropept, typic hemipropept and aquic dystropept. The Sentul area has a undulating, hilly and mountainous topography with an altitude between 200 m-750 m above sea level. The Sentul area has 2 rivers, namely the Cikeas River and the Citeureup River. It was found that the chemical parameters for BOD5 and COD exceeded the established thresholds. The physical and microbiological parameters are still below the established threshold. Sentul City's water needs are currently at 5,162,500 liters / day. The water requirement is supplied by PDAM Tirta Kahuripan of 17,280 m3 / day. This situation makes Sentul City a surplus of water. The water surplus made Sentul City have water resistance during the Covid-19 pandemic.
BLOCKCHAIN IN THE PUBLIC ADMINISTRATION OF KAZAKHSTAN

In the last decade, there has been an increasing interest in blockchain technology around the world. Its functional qualities, such as the invariability of data, openness, transparency and cost-effectiveness, determine the interest in it from the state as well. The purpose of this study is to identify and analyze the possibilities and conditions for the effective use of blockchain technology in the public administration system. In addition, this paper describes the experience of using blockchain technology in certain sectors of the economy and public administration of Kazakhstan.The research methodology is based on a theoretical review, study and analysis of foreign and Kazakhstani experience in the implementation of pilot blockchain projects. To identify the factors of the internal and external environment that influence the development of blockchain technology in the public administration system, SWOT and PEST analyses are presented. In addition, selected regulatory legal acts of the Republic of Kazakhstan regulating digital technologies were studied. A sociological survey was carried out to define the possibility of introducing blockchain into the real estate registration sphere. Based on the results of the study, it was concluded that there are both opportunities and the presence of factors that promote and hinder the introduction of this technology into the state administration of the Republic of Kazakhstan. At present, the blockchain industry is highly fragmented, mainly of a local nature, and if it is possible to implement it in the public administration system, it is accompanied by the complexity of technical implementation.
Design of Lighting System for Substation Area 13 LPG Arun With Lumen Calculation Method

Lighting is one of the important factors in designing space to support user comfort and safety. To carry out all activities that are in a room, an adequate lighting intensity is needed, namely in accordance with predetermined lighting standards, so in designing the lighting of a room it must be carried out with full accuracy, among others in terms of lamp selection, calculation of the number of lamps needed and setting the condition of the lights in illuminating the room. LPG Arun is one of the projects being worked on by PT. Engineering. One of the stages of the process is to design the intensity level of artificial lighting in the Electrical room building. In designing artificial lighting, DIALux 4.10 software is used. In this simulation, a more accurate design result is obtained because it can simulate in 3D. Also obtained the value of the intensity of light and the number of lights needed in the lighting. In this design the results are obtained where the artificial lighting design in each room is in accordance with the owner’s request standards.
PROSEDUR PENGOPRASIAN DAN PERAWATAN AC CENTRAL UNTUK MENINGKATKAN KENYAMANAN RUANG AKOMODASI DI KAPAL SV. RIG TENDER ELANGPT. KANAYA JAKARTA

ABSTRACOPRATING PROCEDURES AND AC CENTRAL ACCURATE FOR IMPROVING COMFORT ROOM IN SHIP SV. RIG TENDER ELANG PT. KANAYAArranged by :ARIF SETYO AJINRP : 145220038 Cooling system is one of the systems that work on the ship. The function of AC Central is to improve the comfort of the ship's accommodation so that the crew can feel comfortable at the time in the riung accommodation and the bedroom so that it can be maximized.Central Central Operating Procedures and Maintenance System To Improve Comfort of Accommodation Space On board. In order for the crew of the ship can rest comfortably and can work more leverage SV. RIG TENDER ELANG. PT. KANAYA Refrigerant vapoured then condensed, while compression occur in vapor phase, so that the system is called Vapor Compression System. To obtain the necessary evaporation of gas (air) reaches a certain temperature (heat). After the hot air was changed so that heat loss, resulting in evaporation. When the evaporation, there arises a temperature in the low temperature (cold) for it also requires a good ac treatment. Key Words : Operational AC,System AC Central, Principle Operation
Near-duplicate image detection for the insurance field

Near-duplicate detection aims at finding images from the same scene or place inside a wide collection. In this context, near-duplicate (ND) detection differs from the extensively studied image retrieval task because of its objective is finding different version of a same object in which the distinction between ND and non-ND pairs is done through a classification function while image retrieval is usually a search to retrieve semantically similar images based on a specific query. Near-duplicate discovery has many applications as social media evaluation, web content creation, image forensic and fraud detection. I created a machine learning method that exploits images' descriptors to learn similarities between image pairs. In particular, I developed a Siamese architecture composed by convolutional neural networks to extract image pairs' features and calculate similarity scores and pairs' distances. The dataset used to train the network is a private database owned by Reale Mutua Assicurazioni, formed by claims mostly regarding building damages. The final goal is to identify all possible near-duplicates, thresholding the output score of the model, starting from a set of queries. Because false positives have to be checked by the user, a high specificity is required. To evaluate results the problem is a binary classification of near-duplicate vs. not-near-duplicate pairs. Metrics are evaluated through Receiver Operating Curve (ROC) and a final Area Under the Curve score of 0.73 is achieved.
Body Systems - PGDE & Corpus Christi Primary

The lesson, Body Systems is part of the Biological systems within the CfE Broad General Education, Experiences and Outcomes. We targeted activities appropriate to primary school level including level 1 and level 2 Outcomes. We used traditional methodology to explore the body systems such as peak flow meters and velcro organs aprons. From diagrams to illustrated pop up books. We also used more advanced technology such as ClassVR virtual reality from Avantis and Augmented reality apps and tools such as Augmented reality T-Shirt Virtuali-tee. This was a fantastic opportunity for our PGDE students to take the lead in micro teaching sessions and for the pupils from Corpus Christi to visit the School of Education and conduct their experiments. Huge thank you to all who took part.
An Analysis of Rear-End Impact Crash Characteristics and Injury Pattern in Malaysia

&#x0D; &#x0D; &#x0D; Rear-end crashes are one of the most common types of accidents. The characteristics of rear impact crash (based on accident data in Malaysia) have not been well studied. The objective of this study is to investigate the rear impact crash characteristics in Malaysia between 2016 and 2018 using data obtained from Bukit Aman Traffic Investigation and Enforcement (JSPT), Royal Malaysia Police (RMP) Pol 27. The analysis revealed that motorcycles (40.3%) were the largest contributor to rear-end crashes, followed by occupant car (36.3%), lorry (16.3%), four-wheel (3.8%), bus (1.6%) and other vehicles (1.6%). The majority did not suffer any injury (60.8%), while there were fatalities (16.8%), injuries (14.3%), and severe injuries (8.1%). The highest percentage of fatal crashes occurred at the speed limit area 110 km/h (23.6%). The chi-square test showed that speed limit and type of crash were significantly associated (p&lt;0.01). The result also showed a significant association between main vehicle part damage and injury level (p&lt;0.01). The study shows a thorough examination and analysis of rear impact crash characteristics can provide important and useful information to guide transport policy, vehicle design, and driver education. Further research is needed to fully understand the key factors that contribute to rear-end impact crashes in Malaysia.&#x0D; &#x0D; &#x0D;
Persuasive Chatbot Conversations : Towards a Personalized User Experience

Helping drivers improve their driving skills and become safer drivers is a problematic topic. Most drivers have a lacking self-assessment ability and consider themselves above average driving skill ...
Towards a declarative approach to constructing dialogue games.

In this paper we sketch a new approach to the development of dialogue games that builds upon the knowledge gained from several decades of dialogue game research across a variety of communities and which leverages the capabilities of the Dialogue Game Description Language as a means to describe the constituent parts of dialogue games. Our ultimate aim is to produce a method for rapidly describing and implementing games that conform to the designer's needs by declaring what is required and then automatically constructing the game from components, called 'fragments', that are distilled from existing dialogue games.
Methodology for the Implementation of Kalman Filters on Real Applications

Some industrial variables cannot be measured directly due to environmental factors or high costs, then this variables need to be estimated by using Kalman Filters (KF). In order to solve this problem, this paper proposes a methodology that allows the complete design and implementation of KF estimators. A practical application shows that the implementation of the linear KF only consumes the \(3.33 \%\) of the capacity of an AMD A8-5550M processor.
Sustainability Principles for Data Ethics: An Explorative Research

Digital world deserves a balance, while over period we expect most of the civilization on earth will adopt to digital world, it may still not be in equilibrium. There may be some who would have evolved with power of digital and some who would have not. Power will always have an imbalance, by its nature, with economics and politics on one side and rights and transparency on other. Digital world’s two key pillars are Data and technology. These pillars shall be used to bridge the existing societal / economic gaps, but not to extend them. Hence its pertinent to consider Data and Technology as key sustainability principles. Sustainability principle does not limit itself to environment, but expands to its varied sects of people. Sustainability principles focus on (a) Current and future potential to meet human needs and aspirations, (b) Socio-economic process contributing to transparency, (c) Equitable distribution of benefits, (d) Developing and building a balanced environment, through human ecosystem equilibrium. These principles are relatable to data and technology as well. When adopted as part of sustainability, data and technology will evolve to Green Data and Green Technology. Green Data and Green Technology is a social economic process for the pursuit of common ideal. While this is not discussed or explored in today’s environment, it will be inevitable for us to adopt it to preserve the world for our future generation.As reflected in professional responsibility principle of Principled Artificial Intelligence ( Berkman klein, March 2020), its responsibility of professionals to protect, preserve and enrich the world. While, certainty of the direction that data ethics evolves cannot be predicted the predicated argument of data ethics moving towards sustainability appears plausible. This research could thereby allow future deliberations around Green Data/ Green technology.
Quantum Error Correction

DiVincenzo criterion #5 from Chap. 18 states that the qubit lifetimes should be long compared to the duration of the algorithm. However, quantum systems are fragile. Unwanted external perturbations from the environment (e.g., electromagnetic waves, thermal excitations, charge, etc.) can interact with the quantum system, such that the system becomes entangled with the environment. Quantum computing presents two conflicting requirements: qubits should be isolated from the environment for long qubit lifetimes (DiVincenzo criterion #5), while also possessing good addressability (DiVincenzo criterion #2 and #4). We need to be able to address qubits without letting the noisy environment leak into the system. Due to the difficulty of this challenge, present day quantum algorithms have been demonstrated with only a few 10s of qubits. We need a way of correcting errors, known as quantum error correction (QEC).
LibGuides: LibGuides Website Tips: Remove tabs from view

This guide accompanies PALNI's Website Style Guide and focuses on assisting you to create a custom website in LibGuides