Reviewerly/exHarmony huggingface dataset:
The Influence of Task Based Language Teaching and Learning Motivation Toward Writing Achievement

This study was to investigate the influence of task based language teaching and learning motivation toward writing achievement. The population of this study was the eleventh grade students at SMK N 3 Palembang. The sample was 64 students taken by using cluster random sampling. In carrying out of the research, the writer used an experimental method; factorial design. The writer distributed pretest, posttest, and attitude questionnaire in collecting the data. Then, in analyzing the data the writer used t-test and two-way ANOVA. The result of this study analysis indicated that: (1) there was a significant difference in writing achievement between the student who taught by using TBLT and those are taught using conventional technique, (2) there was significant difference in writing achievement between the students who have high motivation by using TBLT and conventional teaching technique, (3) there was significant difference in writing achievement between the students who have low motivation by using TBLT and conventional teaching technique, (4) there was significant difference in writing achievement between the students who have low and high motivation by using TBLT, and (5) there was an interaction effect of technique used and student’s motivation in improving writing achievement.
Bitcoin : users’ characteristics, motivations and investment behaviours

In less than a decade, the cryptocurrency known as Bitcoin has gone from a fringe phenomenon to a topic of increasing interest to academia and mainstream investors. However, despite the growing body of research seeking to understand Bitcoin, the pseudonymous, decentralised, and globally-diffused nature of its user base means that the individuals who use it remain poorly understood. In particular, the motivations, risk-appreciation, and investment behaviours of early adopters and innovators are subject to supposition in the absence of data derived from the user base. This thesis seeks to address this gap in knowledge by employing a multi-stage, mixed methodology approach and a theoretical framework to understand the Bitcoin user base. Utilising semantic analysis, a survey of online cryptocurrency communities, and econometric time-series analysis, this thesis addresses the extent and nature of Bitcoin in hedging; how individual users perceive their own motivations, uses, and risks that have driven their behaviour; and the nature of the relationship between the prices of cryptocurrency and indices of confidence. Analysis of the data determined that the use of Bitcoin as an instrument of hedging is limited, and influenced by political and institutional factors. Likewise, its motivations, uses, and risks are reflective of the users’ political ideology, with the community and marketplace becoming more sophisticated as they evolve over time. Additionally, despite several case studies demonstrating risk-averse adoption of Bitcoin, there is no relationship between its prices and confidence.%%%%Doctor of Philosophy
Storm Scheduling Based on Non-cooperative Game

Abstract With the continuous development of Internet technology, a large amount of data with rich value has been generated, and lagging data analysis will affect the timeliness of data, so real-time streaming data processing is becoming increasingly important. Storm is a pure streaming data processing framework, but it uses the polling scheduling algorithm by default. This algorithm ignores the network communication overhead between workers and cluster load balancing. Aiming at Storm’s default scheduling problem, a non-cooperative game-based Storm scheduling algorithm (G-Storm) was proposed. Storm extracts the source data in real time through the component “Spout”, passes it to the logical processing component “Bolt”, and finally loads it into the target warehouse. The experimental results show that the game scheduling algorithm proposed in this paper reduces the system processing delay by 28.6% compared with the default scheduling algorithm.
DIKSI DAN GAYA BAHASA PADA CERPEN ‘ANAK INI MAU MENGENCINGI JAKARTA?’ DAN RELEVANSINYA DENGAN MATERI AJAR DI SMA

ABSTRACT : The purpose of this study is to describe the diction, figure of speech and the relevance of Antologi Cerpen Pilihan Kompas 2015 ‘Anak Ini Mau Mengencingi Jakarta?’ And It’s Relevance to the Teaching Materials of Grade XI of Senior High School in the Curriculum of 2013. This research is a descriptive qualitative shaped with describe or illustrate the problems occurred and analyze the data in the form of words or sentences. Sampling techniques using is purposive sampling method. Engineering data collection using the technique of the analysis of the documents and intervie ws with informan . The validity used is sources and theory triangulation. Data analysis technique used is flow model of analysis. Procedure research conducted several different stages namely the preparation phase, the phase of implementation, and the stage of the preparation of the report. The results of these studies were found (1) utilization of diction with a total of 238 overall data; (2 the form of language stylistics with a total of 148 overall data; and (3) the relevance of Antologi Cerpen Pilihan Kompas 2015 Anak Ini Mau Mengencingi Jakarta? And It’s Relevance to the Bahasa Indonesia’s Teaching Materials of Grade XI of Senior High School in the Curriculum of 2013.
PERANCANGAN SISTEM PERANCANGAN SISTEM INFORMASI PEMASARAN BERBASIS DIGITAL PADA HOME INDUSTRY JAJANAN TRADISIOANAL

Pak Dicky's traditional snacks home industry is a UKM engaged in selling traditional culinary snacks which is also well-known by the name of market snacks. In increasing marketing and sales of products to consumers, it is necessary to implement a surefire business strategy to increase new market share. The problem experienced by Pak Dicky's traditional snacks home industry is the limited resources and time in serving every customer / consumer needs. Marketing information system design uses information systems modeling context diagrams, data flowchart diagrams, entity relationship diagran, and e-commerce website design applications by designing fast and appropriate information systems to customers, providing convenience for potential customers, and providing site-based applications web e-commerce that is easy to use by customers based on the design of marketing information systems capable of managing such as making reservations online, providing discounts and promos via the website and searching for product data using the results of application-based marketing information systems e-commerce website is able to provide options / options buying and selling transactions to consumers so that data management is more effective and the presentation of information is fast and flexible. This marketing information system was created using Visual Studio Code as a code editor and database using phpMyAdmin and MySQLi.
Word pattern prediction using Big Data frameworks

Abstract Using software applications or services, which provide word or even word pattern recommendation service has become part of our lives. Those services appear in many form in our daily basis, just think of our smartphones keyboard, or Google search suggestions and this list can be continued. With the help of these tools, we can not only find the suitable word that fits into our sentence, but we can also express ourselves in a much more nuanced, diverse way. To achieve this kind of recommendation service, we use an algorithm which is capable to recommend word by word pattern queries. Word pattern queries, can be expressed as a combination of words, part-of-speech (POS) tags and wild card words. Since there are a lot of possible patterns and sentences, we use Big Data frameworks to handle this large amount of data. In this paper, we compared two popular framework Hadoop and Spark with the proposed algorithm and recommend some enhancement to gain faster word pattern generation.
Fuzzy BP neural network in radar intelligence quality evaluation

Abstract This paper presents a novel approach of radar station intelligence quality evaluation which based on fuzzy Backpropagation neural network (BPNN). Firstly, the index system of the radar station intelligence quality evaluation is established according to the analysis of the process, the characteristics, and the main influencing factors of the radar station intelligence production. And then the factor set, comment set and the membership matrix are structured, the fuzzy BPNN for evaluating the quality of the radar station intelligence is designed referring to the index system. Finally, the experiment shows that the accuracy and stability can be improved effectively by using fuzzy BPNN to evaluate the radar station intelligence quality
UCC Library: Digitised Course Readings - Academic Staff: Home

How the library can digitise essential items for your module reading list using the Digital Content Store (DCS)
TCO and performance optimization for large scale public and Hybrid cloud environment.

Saving money and to increase the performance is one of the main reasons for moving workloads to the cloud. With the Click2Cloud multi cloud management platform, the cloud infrastructure can reduce total cost of ownership (TCO) as compared to on-premise infrastructure. Cloud brain helps to choose the best hybrid cloud solution that involves careful consideration of how each cloud implementation option would meet the needs of the overall organization and its specific workloads. A hybrid cloud approach offers the best path to the cloud, and a way to optimize your existing assets offers the best path to the cloud, and a way to optimize your existing assets. Using on demand resources in the cloud, you can leverage the power of the cloud and provide services that complement your existing on-premises datacentre. Cloud brain platform also provides consistency across the key areas like; identity; management, security, infra automation, and DevOps. It also simplifies complexities as user can comfortably choose instance sizes, operating systems, database, application framework among other applications as per their business needs and usage.
STUDENTS’ ABILITY IN USING PAIRED CONJUNCTION IN SIMPLE SENTENCE

The goal of this research is to know the students' ability in using paired conjunction in a simple sentence. Based on the limitation of the problem, the researchers limit the problem in using paired conjunction just focuses on the use of not only ..... but also, both ..... and, either ..... or, and neither ..... nor. Before doing the research, the researchers observed to know the number of classes in the eighth grade of SMP PGRI Tembilahan. The number of eighth-grade students just consists of one class, namely Class A. The population of this research was all of the eighth-grade students because the sample of population less than 100 the researcher used total sampling technique. The researchers used a quantitative method to get the data needed. The research instrument is tested and collected by students’ test scores where they were asked to identify the paired conjunction in a simple sentence with the total correct paired conjunction (30). So that, each correct paired conjunction was scored by 3.3. Based on the result of the test, the mean score of their ability in using paired conjunction is 70.62. It is categorized good level, which includes in the interval 61-80. Where there are no students who got in a very good score, five students obtained a good score and there is no gained in enough, poor, and very poor score. So, based on that explanation, it can be concluded that their ability in using paired conjunction in the simple sentence at eighth grade of SMP PGRI Tembilahan include in the average was enough and understanding to use paired conjunction.
Image Batik Classification Based using Ensemble Learning

Automatic feature descriptor is substantial part of component  in the textural image retrieval  and  classification.  Image  batik  has  its  unique  pattern  characteristic  such  as  color intensity,  ornament  visualisation  and  ornament  size.  In  motive  of  batik  classificatin  rneed feature  extraction  methods.  The  scale  invariant  feature  transform  (SIFT  )  can  be  used  for  feature descriptor in some applications. In this paper, we presents an efficient based on Bag of Words  (BoW)  with  features  of  scale  invariant  feature  transform  and  ensemble  classifier  for improving classification accuracy.
Bilders påverkan på webbplatsers informationsarkitektur : hur bildval kan påverka användarnas upplevelse i webbplatssammanhang

The proverb ’a picture is worth a thousand words’ expresses the effective use of imagery as a mode of communication. An image has the advantage of being able to convey difficult to express informat ...
IMPLEMENTASI SISTEM INFORMASI IMPLEMENTASI SISTEM INFORMASI PEMASARAN BERBASIS DIGITAL PADA HOME INDUSTRY JAJANAN TRADISIONAL

This study aims to determine the description of marketing information systems that are applied to the traditional home snacks of Pak Dicky and analyze the problems of the current system to be developed in the form of marketing information system design to promote traditional snacks that are being forgotten. This research was carried out in the marketing section of Pak dicky's traditional home industry snacks located in the district of cotton - Bojonegoro. This type of research is a qualitative research with action research approach. Data sources used are primary data and secondary data obtained using data collection methods in the form of observation, interviews, and documentation. The results showed that the marketing information system in the traditional home snacks of Pak Dicky still uses a conventional model that still has various weaknesses and lacks efficiency. These weaknesses include the promotion of social media that is less effective and efficient in providing information to prospect customers. Recommendations from existing customers are not supported by complete information sources that can be given when needed. limited marketing reach. Digital models and existing networks have not yet been utilized. The design of the implementation of marketing information systems for digital-based promotions can be implemented by Pak Dicky's traditional hawker industry as an effort to overcome the ongoing marketing problems in providing information about traditional hawker products offered.
UIC participated in the 3rd General Assembly of the European Rail ISAC on 26 June 2020 – UIC Communications

Last week, UIC participated in the 3rd General Assembly of the European Rail ISAC (ER-ISAC), co-hosted by the European Union Agency for Cybersecurity, ENISA. The ISAC (Information Sharing and…
Evaluasi Usabilitas Aplikasi SIAKAD Fakultas Ilmu Komputer Universitas Katolik Santo Thomas menggunakan Metode Heuristik

The number of systems that have developed at this time has good quality for users. But some of the existing systems have not yet been measured for usability. Case study of the Catholic Computer Science Faculty academic information system of Saint Thomas North Sumatra. This study aims to determine the evaluation of information systems in case studies in terms of their usefulness, effectiveness, efficiency, and user satisfaction in using the Academic Information System. The method used is the heuristic method. Data collection in this study with direct research to the location and see journal references, documentation and previous research. This study also uses a questionnaire to measure user satisfaction. Based on the results of testing data collection, the use of the siakad information system as a recommendation to design the development of the system can produce a system with high usability, so that the system is expected to be in accordance with the objectives so that it can be accepted by the user.
Training Deep Convolutional Neural Networks on the GPU Using a Second-Order Optimizer

Deep Convolutional Neural Networks (CNNs) are a prominent class of powerfuland flexible machine learning models. Training such networks requires vast computeresources: due to the large amount of training data and due to the many training it-erations. To speed up learning, many specialized algorithms have been developed.First-order methods (using just the gradient) are the most popular, but second-orderalgorithms (using Hessian information) are gaining importance. In this thesis we givean overview over the most common first-order optimizers and how they are used totrain networks. Then we build upon a sample second-order algorithm which we callEHNewton (Efficient Hessian Newton). We have integrated this into the TensorFlowplatform, such that the new method can act as a drop-in replacement to standard algo-rithms. We make use of this, by training one CNN model each out of the (1) Inception,(2) ResNet and (3) MobileNet architectures. Due to technical limitations we limit thisstudy to last layer training on a single NVIDIA Titan GPU.EHNewton shows speed-up and accuracy benefits compared to first-order trainingalgorithms on all three CNNs using the ImageNet database.
Macdonald-Kelce Library Homepage: Cybersecurity: Databases

Resources to assist with the successful completion of a Cybersecurity degree at UT Find articles, statistics, and reports for your research in library databases
Expanding KTH's Canvas ecosystem to support additional automated services : Automating the injection of theses and their metadata into a digital archive

Whenever a student submits their final version of their thesis, a series of processes is triggered to finalize and archive the report. These processes are often handled in a less than efficient way ...
LibGuides: First Year Experience: Meet Your Librarians

This LibGuide was created to provide information on library resources for first-year students and their instructors.
LibraryGuides: Borrowing Books, DVDs, etc.: Borrowing Books, DVDs, etc.

How to borrow physical items from the library for delivery by mail How to request a book delivered by mail
LibGuides: Library Events: Check out these Monthly Recommendations

Want to know what is going on at the Library? Check out all of our past and upcoming events here! Once a month from now on we'll give you a new book recommendation!
안구운동을 포함한 컴퓨터 기반 주의력 훈련프로그램이 장애아동의 주의력에 미치는 효과 : 임상증례보고

Objective: The purpose of this study was to identify some influences on improving attention abilities of disabled children through a computer-based attention program with eye movement (saccade, pursuit, and visual fixation). Method: For this purpose, four children with attention problems participated in a clinical experiment. All participants were evaluated based on a Comprehensive Attention Test (CAT) and Star cancellation test before and after the planned intervention sessions. The intervention tool was a computer–based cognitive rehabilitation program using an input system with eye movement. Interventions were intensively carried out for eight weeks, half an hour per session, three times a week. Results: The results were as follows. Selective attention, flanker task, and sustained attention were improved compared to before the intervention. The attention quotients showed positive changes in attention areas after intervention. The various attention quotients after intervention were higher than before. Furthermore, there were improvements in the attention quotients for the divided attention and working memory areas. All participants increased their response speed AQ in all attention areas. Conclusions: These results indicate that attention training using an eye movement program has an effect on improving the selective attention, sustained attention, and flanker task. In particular, positive influences were shown on divided attention, working memory, and response speed for children with poor attention.
What Does a Scientific Paper Say?

This chapter looks at how and when a group of researchers decide the time is right to write a paper, the reasons for writing a paper, and what the paper must say. Key characteristics of a scientific paper that inform its structure are used to introduce the sections of a modern paper and explain their functions. This approach allows a logical exploration of the sections of a scientific paper and their function. In addition, this chapter considers the effective presentation of scientific evidence, in terms of construction of effective figures and tables.
Neural architecture search: a probabilistic approach

In this project, we introduce the Bayesian Optimization (BO) implementation of the NAS algorithm that is exploiting patterns found in most optimal unique architectures sampled from the most popular NAS dataset and benchmarking tool NASbench-101 (Dong and Yang, 2020a). The proposed solution leverages a novel approach to path-encoding and is designed to perform reproducible search even on a relatively small initial batch obtained from the random search. This implementation does not require any special hardware, it is publicly available.
REDEFINING THE PURPOSE OF TIBETIAN ARTS AND CRAFTS IN INTERIORS

Tibetan crafts are the inventive practices the area unit influenced by Buddhism. It includes art media that depict Buddhas, Bodhisattva, and alternative entities; notable Buddhist figures, each historical and mythical; narrative scenes from the lives of all of these; mandalas and alternative graphic aids to apply; furthermore as physical objects related to Buddhist practice, like Vajras, bells, Stupas, Prayer wheels and Buddhist temple design.Buddhist craft originated on the Indian landmass following the historical lifetime of Siddhartha Gautama, sixth to fifth century BCE, and therefore thereafter evolved by contact with alternative cultures because it unfolds throughout Asia and the world. Buddhist art followed believers because the Dharma unfold, adapted, and evolved in every new host country. It developed to the North through Central Asia and into Japanese Asia to create the Northern branch of Buddhist art, and to the east as so much as Southeast Asia to create the Southern branch of Buddhist art. In India, Buddhist art flourished and co-developed with Hindu and faith art, with cave temple complexes engineered along, every possible influencing the opposite.The purpose of paper is to push and preserve crafts of Ladakh and to inspire the young generations to continue and style the inside parts from the crafts.
Training of Mixed-Signal Optical Convolutional Neural Networks With Reduced Quantization Levels

Analog computing paradigms are promising solutions to the growing computational demands of machine learning applications. Despite being susceptible to errors, analog and mixed-signal platforms have the potential to achieve higher speed and power efficiency for artificial neural network (ANN) applications than digital computers. Driven by the development of digital fixed-point ANN accelerators, low-precision ANN models have proven to be successful in compressing the size of ANNs and conforming the models to the data format of digital accelerators. While the inputs and weights of these digital, fixed-point ANN models can have low bit widths, the intermediate results (e.g., activations) must be preserved in high precision. As a result, these digital fixed-point models and training algorithms cannot be migrated easily to analog accelerators, because the analog intermediate results typically suffer from reduced precision due to noises and device imperfections. Here, we report on a training method for mixed-signal ANNs that considers two types of analog impairments, namely, random noise and distortion (deterministic in nature). The results show that mixed-signal ANN trained with our method can achieve the same classification accuracy as the digital fixed-point model with noise levels up to 50% of the ideal quantization step size. We demonstrate our training method on a mixed-signal, convolutional neural network based on diffractive optics.
Research Guides: ADV 208: The Big Idea in Advertising (Fall 2020): Librarian

An SU Libraries research starting points guide for students enrolled in ADV 208 (course sections taught by Profs Brian Sheehan and Mel White)