Peningkatan Kemampuan Berbicara dengan Menerapkan Model Pembelajaran Kooperatif TIME Token Arends di Sekolah Dasar

This research aims to describe that improving the speaking skill using cooperative learning model Time Token Arends at V grade student\u27s in SDN 34 South Pontianak West Borneo province. The research methodology that used is a descriptive. The research design that used is a Classroom Action Research and also the character that used is collaborative. The research setting was in SDN 34 South Pontianak, the subject of this research was student at V grade and the total of the student in the class was 32 student\u27s and the Bahasa Indonesia teacher. The result of the data analysis in the baseline phase showed speaking skill of student\u27s in aspects of language reached 61,45% and the aspects of nonlanguage reached 47,39%, so that the action is given by implementing cooperative learning model Time Token Arends to improve their speaking skill

Evaluation of a token economy in a school for disruptive children

The "medical" approach to the treatment of "behavioural problems is first considered, and dismissed as being an inappropriate conceptual framework for applications in education. Behaviour modification is presented as a more appropriate approach to intervention, and the advantages that pertain to the classroom teacher are discussed. Controversial issues are summarily reviewed, and include a discussion of the ethics of behavioural intervention and the polemics of behaviour therapy. Further discussion of the literature is mainly concerned with the procedural aspects of implementing behavioural programmes, and includes reference to methodology, functional analysis, and techniques of accelerating/facilitating and eliminating behaviours in the classroom. Particular emphasis is placed on the application of token economies to improve social and academic behaviours. The research report describes how a token economy was implemented in a classroom of six disruptive children. An intra-subject, reversal design was used within a phenomenal/ behavioural framework. Points were given contingent upon appropriate targeted classroom behaviour, and these could be exchanged for back-up reinforcers at a later time. Inappropriate target behaviours decreased significantly during the token phases but increased again during reversal phases. Assignment and on-task behaviours increased significantly during the token phases. Data suggests that some generalization occurred from morning to afternoon sessions for assignment behaviour, and from target behaviour to non-target behaviours. There was no evidence of generalization from token phases to non-token phases. Anecdotal evidence suggested that the students became very intransigent when the token system was removed; they "enjoyed" school more during the token phases. In the discussion a number of methodological and procedural aspects of the study are explored, and alternative strategies presented. The study shows that it is possible to effectively implement a phenomenal/behavioural programme in a classroom of disruptive students for minimal cost and time, with maximal benefits accruing to both teachers and students

Codesigning with blockchain for synergetic landscapes: the cocreation of blockchain circular economy through systemic design

The paper is exploring methodology within the work in progress research by design through teaching project called ‘Synergetic Landscapes’. It discusses codesign and cocreation processes that are crossing the academia, NGOs and applied practice within so called ‘real life codesign laboratory’ (Davidová, Pánek, & Pánková, 2018). This laboratory performs in real time and real life environment. The work investigates synergised bio-digital (living, non-living, physical, analogue, digital and virtual) prototypical interventions in urban environment that are linked to circular economy and life cycles systems running on blockchain. It represents a holistic systemic interactive and performing approach to design processes that involve living, habitational and edible, social and reproductive, circular and token economic systems. Those together are to cogenerate synergetic landscapes

Desynchronization: Synthesis of asynchronous circuits from synchronous specifications

Asynchronous implementation techniques, which measure logic delays at run time and activate registers accordingly, are inherently more robust than their synchronous counterparts, which estimate worst-case delays at design time, and constrain the clock cycle accordingly. De-synchronization is a new paradigm to automate the design of asynchronous circuits from synchronous specifications, thus permitting widespread adoption of asynchronicity, without requiring special design skills or tools. In this paper, we first of all study different protocols for de-synchronization and formally prove their correctness, using techniques originally developed for distributed deployment of synchronous language specifications. We also provide a taxonomy of existing protocols for asynchronous latch controllers, covering in particular the four-phase handshake protocols devised in the literature for micro-pipelines. We then propose a new controller which exhibits provably maximal concurrency, and analyze the performance of desynchronized circuits with respect to the original synchronous optimized implementation. We finally prove the feasibility and effectiveness of our approach, by showing its application to a set of real designs, including a complete implementation of the DLX microprocessor architectur

An empirical analysis of smart contracts: platforms, applications, and design patterns

Smart contracts are computer programs that can be consistently executed by a network of mutually distrusting nodes, without the arbitration of a trusted authority. Because of their resilience to tampering, smart contracts are appealing in many scenarios, especially in those which require transfers of money to respect certain agreed rules (like in financial services and in games). Over the last few years many platforms for smart contracts have been proposed, and some of them have been actually implemented and used. We study how the notion of smart contract is interpreted in some of these platforms. Focussing on the two most widespread ones, Bitcoin and Ethereum, we quantify the usage of smart contracts in relation to their application domain. We also analyse the most common programming patterns in Ethereum, where the source code of smart contracts is available.Comment: WTSC 201

A Programming Environment Evaluation Methodology for Object-Oriented Systems

The object-oriented design strategy as both a problem decomposition and system development paradigm has made impressive inroads into the various areas of the computing sciences. Substantial development productivity improvements have been demonstrated in areas ranging from artificial intelligence to user interface design. However, there has been very little progress in the formal characterization of these productivity improvements and in the identification of the underlying cognitive mechanisms. The development and validation of models and metrics of this sort require large amounts of systematically-gathered structural and productivity data. There has, however, been a notable lack of systematically-gathered information on these development environments. A large part of this problem is attributable to the lack of a systematic programming environment evaluation methodology that is appropriate to the evaluation of object-oriented systems

Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks

Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady state (the throughput) is important for both compiler designers and performance engineers. Building an analytical model to do so is especially complicated in modern x86-64 Complex Instruction Set Computer (CISC) machines with sophisticated processor microarchitectures in that it is tedious, error prone, and must be performed from scratch for each processor generation. In this paper we present Ithemal, the first tool which learns to predict the throughput of a set of instructions. Ithemal uses a hierarchical LSTM--based approach to predict throughput based on the opcodes and operands of instructions in a basic block. We show that Ithemal is more accurate than state-of-the-art hand-written tools currently used in compiler backends and static machine code analyzers. In particular, our model has less than half the error of state-of-the-art analytical models (LLVM's llvm-mca and Intel's IACA). Ithemal is also able to predict these throughput values just as fast as the aforementioned tools, and is easily ported across a variety of processor microarchitectures with minimal developer effort.Comment: Published at 36th International Conference on Machine Learning (ICML) 201