Miracle-dz/UniFAR-FTUs huggingface dataset:
ANALISIS PROSES SCAFFOLDING PADA PEMBELAJARAN MATEMATIKA DI KELAS VIII SMP NEGERI 4 KARANGANYAR

A bstract : This research was aimed to describe scaffolding process in mathematics learning in the learning material of straight line equation at grade VIII Junior High School Number 4 in Karanganyar Regency in the Academic Year of 2013/2014 for conceptual and procedural knowledge. This research was a descriptive qualitative research. The main subject of this research was a mathematics teacher grade VIII Junior High School Number 4 in Karanganyar Regency. Meanwhile, the minor subject in this research was students getting scaffolding from teachers in the learning process. The selection of research subject was by purpossive sampling technique . In this research, researcher used passive participation observation and not structured interview recorded by using handycam . In this research, the data validity technique was triangulation technique. The result of research showed as follows. 1) The scaffolding process of learning activities in the learning material of straight line equation for conceptual knowledge given by teacher was to keep students on task, and provide clear direction and reduce students confusion. It was scaffolding process given often by teachers. While the scaffolding process given occasionally by teachers was presenting the conducting questions, clarifies expectations and incorporates assessment, and presented the information clearly. 2) The scaffolding process of learning activities in the learning material of straight line equation for procedural knowledge given by teachers was to present the information clearly and present the conducting questions. It was scaffolding process given often by teachers. While the scaffolding process given occasionally by teachers was directed students against reference, keeps students on task, involved student’s participation, provides clear direction and reduces students’ confusion, and clarifies expectations and incorporates assessment. Keywords : scaffolding, conceptual knowledge, procedural knowledge
SymPLFIED: Symbolic Program-Level Fault Injection and Error Detection Framework

This paper introduces SymPLFIED, a program-level framework that allows specification of arbitrary error detectors and the verification of their efficacy against hardware errors. SymPLFIED comprehensively enumerates all transient hardware errors in registers, memory, and computation (expressed symbolically as value errors) that potentially evade detection and cause program failure. The framework uses symbolic execution to abstract the state of erroneous values in the program and model checking to comprehensively find all errors that evade detection. We demonstrate the use of SymPLFIED on a widely deployed aircraft collision avoidance application, tcas. Our results show that the SymPLFIED framework can be used to uncover hard-to-detect catastrophic cases caused by transient errors in programs that may not be exposed by random fault injection-based validation. Further, the errors exposed by the framework help us formulate a set of error detectors for the application to avoid the catastrophic case and other incorrect outcomes.
Two-dimensional Model of Financial Accounting System Implementation Based on Customer Awareness in China

The advent of the information age ushers enterprise informationization into a period of rapid development. As the key to enterprise informationization, the financial accounting system serves as an important link between business accounting and business operation. In the course of enterprise information integration in mainstream ERP software, project implementation of the financial accounting system can hardly achieve the desired results due to risks in project management and implementation. It is thus evident that the principle problems with current financial accounting system implementation are to diminish the risks in the system's project implementation and formulate reasonable and scientific project implementation plans. This paper analyzes the implementation methods adopted by mainstream financial accounting systems at both home and abroad, attempts to improve the implementation methods of the current financial accounting system, and puts forward a two-dimensional implementation method model of the financial accounting system based on customer awareness.
Coverage Improvement for Wireless Mobile Sensor Networks Using Particle Swarm Optimization

In this paper, an algorithm that aims at improving the coverage of Wireless Sensor Networks (WSN) is proposed. The coverage is improved in random deployment regions by employing some mobile nodes, which can actively move to desired locations. Coverage improvement is attained by incorporating Particle Swarm Optimization (PSO) algorithm tomaximize the sensing coverage area by finding the optimal placement for the mobile sensors that minimizes the overlap between the coverage regions of sensors. The continuous redeployment of the mobile sensor will decrease the uncovered regions and consequently improve the Quality of Service (QoS) of the network. Simulation results demonstrate the effectiveness of the proposed algorithm in increasing the coverage area.The performance of the proposed algorithm is compared with that of the exhaustive search gird based algorithm and results demonstrate that the proposed algorithm is competent for the dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the grid quorum based node mobility algorithm.
Multilingual Unsupervised NMT using Shared Encoder and Language-Specific Decoders

In this paper, we propose a multilingual unsupervised NMT scheme which jointly trains multiple languages with a shared encoder and multiple decoders. Our approach is based on denoising autoencoding of each language and back-translating between English and multiple non-English languages. This results in a universal encoder which can encode any language participating in training into an inter-lingual representation, and language-specific decoders. Our experiments using only monolingual corpora show that multilingual unsupervised model performs better than the separately trained bilingual models achieving improvement of up to 1.48 BLEU points on WMT test sets. We also observe that even if we do not train the network for all possible translation directions, the network is still able to translate in a many-to-many fashion leveraging encoder’s ability to generate interlingual representation.
Performance Analysis of Linear Precoded MU-MIMO-OFDM Systems With Nonlinear Power Amplifiers and Correlated Channel

In this paper, we investigate the effect of power amplifier (PA) nonlinearity on a multi user multiple-input multiple-output orthogonal frequency division multiplexing (MU-MIMO-OFDM) system where the base station (BS) uses linear precoding to transmit data for single antenna users through a correlated channel. The signal to distortion, interference and noise ratio is derived for any order of PA nonlinearity. Our analysis shows that a correlated channel can result in correlated distortions at the output of PAs which increase the received distortion power of users. Approximations for the ergodic achievable rate of the users are provided when the BS transmits data through a correlated channel using maximum ratio transmission or zero forcing precodings and number of BS antennas and users are large. Also, closed form approximations for the ergodic achievable sum rate of the system are provided when the channel is not correlated. The simulation results agree with the derived approximations even when the number of transmit antennas and users are relatively small. The approximations can be used to find the achievable sum rate maximizing number of users or transmit power of the system.
Fiber optic gyroscope threshold denoising based on EMD-LWT

Fiber optic gyroscope (FOG) drift data is often submerged in various noises backgrounds. It is very difficult to compensate for modeling drift signals directly. In order to better eliminate the noise mixed in the FOG temperature drift data, a hybrid EMD-LWT filtering algorithm based on empirical mode decomposition (EMD) and lifting wavelet transform (LWT) threshold denoising was proposed for gyro signals preprocessing. Firstly, the noise signal of fiber optic gyro is decomposed by EMD, and the noise term and the mixed modal term of the intrinsic mode functions (IMF) are judged according to the information entropy. Then the noise term is de-noised by LWT and the mixed modal term is denoised by wavelet transform (WT). A static test was performed on an interferential FOG to verify the effectiveness of the algorithm and compared with WT and LWT. The experimental results show that the proposed EMD-LWT filtering algorithm has better filtering effect. After processing, the root mean square error (RMSE) of the reconstructed signal is reduced by 63%, which effectively removes the noise in the FOG output.
Kinect-Controlled Game to Improve Space and Depth Perception

Space perception is one of the most important skills of human life. Space perception is not a congenital faculty of human beings, but it evolves during the first few years of life. Experts are of the opinion that depth perception can be improved during the first 15-16 years of life. It is essential to perform depth perception in several occupations. We have developed virtual reality game with animations that were used by students to practice space perception tasks and to acquire better space perception. The game is controlled via Kinect sensor.
Shadow Detection and Removal based on Automatic Threshold and Boundary Analysis

The objects extraction from their background could be a difficult assignment. Since one threshold or structure threshold certainly fails to resolve doubt , in this paper, we have proposed a brand new technique that automatically observe the edge to exactly discriminate pixels as foreground or background using automatic threshold mechanism. By ﬁrst distinguishing boundary, its associated curvatures, and edge response, used as benchmark to gauge the possible location of the boundary.Results show that the projected technique systematically performs well in various illumination conditions, as well as indoor, outdoor, moderate, sunny, and rainy cases. By an examination with an empirical evidence in every case, the error rate and the shadow detector index indicate a correct detection, that shows substantial improvement as compared with alternative existing ways.
Determining the number of dimensions underlying customer-choices with a competitive neural network

More and more data about consumer-behaviour is becoming available through the use of database systems and electronic-banking systems. In this paper we describe a neural network (NN)-based technique to extract some useful information from a database holding data about customers of an insurance-company. Using this NN, we try to learn more about the needs and wishes that lead consumers towards specific behaviour, so that better service can be provided in the future. We formulate a more formal version of this problem, describe the NN used, and show results on artificial and real data.
An Adaptive Energy Management System Using Heterogeneous Sensor/Actuator Networks

Global energy consumption has been increasing over the past half century, mainly due to increasing populations and economic development around the world. Although the development of low-consumption appliances, highly efficient heat pump systems (such as Ecocute), and smart meters that identify consumption in more detail than conventional meters contribute in no small part to reducing the emission of greenhouse gases in homes and office buildings, it is important to understand that the rapid growth in ubiquitous comfort services is resulting in higher power consumption. In the future, there may be more convenient appliances coming on the market to create a ubiquitous smart infrastructure. Even though individual appliances might be ultra-low power, the amount of energy consumption in buildings will increase as the number of these appliances increases. There has been research in the field of home/building energy management systems (HEMS/BEMS) (Cao et al., 2006; Inoue et al., 2003; Kushiro et al., 2003; Zhao et al., 2010), but integrating new devices on the market is not easy. Moreover, it is difficult to develop appropriate systems for different lifestyles. For example, a building's carbon footprint is the product of complex interplay between the buildings' structural and infrastructure characteristics, operational patterns and business processes, weather and climate dynamics, energy sources, and workforce commute patterns. Because these disparate factors can change daily, any recommendation based on a snapshot will rapidly become invalid. Therefore, we believe the key feature of next-generation HEMS/BEMS is adaptability. If the systems are able to use information from multi-vendor sensors/actuators in heterogeneous networks, we can develop more adaptable energy management systems for visualizing and controlling the living climate appropriately. We feel this would enable us to create ubiquitous services for a more convenient, eco-friendly lifestyle. We have developed an adaptive energy management system (A-EMS) for controlling energy consumption by converging heterogeneous networks (Mineno et al., 2010) such as power line communications (PLC), Wi-Fi networks, ZigBee, and future sensor networks. We created a prototype system that enables users to freely configure a cooperative network of sensors and home appliances from a mobile device. Although there are many similar technologies for integrating multi-vendor devices (IEEE 1451; Sensor Model Language; Device Kit; Chen, et al., 2009), we used P2P Universal Computing Consortium (PUCC)
Genetic Feature Construction Genetic Feature Construction: a parallel implementation of a genetic programming tool for feature construction

In this paper a parallel implementation of a recently introduced method for feature construction is described. This technique utilizes parallel genetic algorithms along with RBF neural networks to create new features from the original ones by discovering the hidden relations between patterns. The method is tested on series of classification problems from a variety of areas and the results are reported. The accompanied software is written entirely in ANSI C++ using the well established MPI library for parallelization.
Android Application Security Scanning Process

This chapter presents the security scanning process for Android applications. The aim is to guide researchers and developers to the core phases/steps required to analyze Android applications, check their trustworthiness, and protect Android users and their devices from being victims to different malware attacks. The scanning process is comprehensive, explaining the main phases and how they are conducted including (a) the download of the apps themselves; (b) Android application package (APK) reverse engineering; (c) app feature extraction, considering both static and dynamic analysis; (d) dataset creation and/or utilization; and (e) data analysis and data mining that result in producing detection systems, classification systems, and ranking systems. Furthermore, this chapter highlights the app features, evaluation metrics, mechanisms and tools, and datasets that are frequently used during the app’s security scanning process.
Analisis Kualitas Layanan Video Live Streaming pada Jaringan Lokal Universitas Telkom Quality of Service Analysis for Live Streaming Video Services on Telkom University Local Network

Streaming is one kind of technology that allows file to be operated immediately without waiting for download finished and continuous without any interruption. To apply video streaming into the network, it needs first to calculate the available bandwidth that supports data transmission. Bandwidth is the important parameter for streaming in the network. The bigger available bandwidth, the better video quality presented. The objective of this research is to know the bandwidth necessity for video live streaming service; the method used in this research is measuring the network performance directly from the field, Telkom University local network. Implementation of streaming server-client media in this research make use a different in file (video) based on the amount of frame (fps). This streaming video scenario is measured in different background traffic , to see its influence in network QoS parameter. Testing of Quality of Service ( QoS ) performance in video streaming implementation uses software network analyzer Wireshark. The result shows that video with frame rate bigger than 15 fps, gives bigger jitter and throughput.
Structuring operating systems using adaptive objects for improving performance

Programmers of high-performance applications often complain that the abstractions provided by the operating system (OS) hinder the optimal exploitation of the underlying hardware. We believe that this should not be the case with a well designed OS. The key is that OS subsystems must be customizable, adaptable and extensible, to permit an optimal match between the application needs and the hardware architecture. In the CHamelEon project, we seek to demonstrate the practical feasibility of dynamically customizing OSs in a distributed or clustered system. We intend to test our prototype with a small set of commercial applications. <<ETX>>
Comparative Analysis of Location Based Technologies Inorder To Develop IOT Applications

Improvements in information and communication technologies have led to the development of Internet of Things (IoT). The Internet of Things is an emerging topic enabling everyday objects to communicate and exchange information from anyplace. Similarly, as a fast improvement in information technologies such as wireless communication and internet, location based technologies including Near Field Communication NFC, Radio Frequency Identification RFID, and Bluetooth Low Energy BLE have turned an engaging subject to researchers, organizations and commercial enterprises. Use of these technologies in IoT applications is beneficial for businesses, industries, environment and society. This paper consolidates the information on the state of-the-art Internet of Things abbreviated as IoT, from its structural design, system architecture and hardware requirements, to its standards and protocol stacks. This paper presents an insight into various location based technologies and highlights the proposed services to be provided by these location based technologies. This paper also makes a comparative analysis of various location based technologies in terms of power consumption, range, cost, data transfer rate and accuracy.
A Ferroelectric FET-Based Processing-in-Memory Architecture for DNN Acceleration

This paper presents a ferroelectric FET (FeFET)-based processing-in-memory (PIM) architecture to accelerate the inference of deep neural networks (DNNs). We propose a digital in-memory vector-matrix multiplication (VMM) engine design utilizing the FeFET crossbar to enable bit-parallel computation and eliminate analog-to-digital conversion in prior mixed-signal PIM designs. A dedicated hierarchical network-on-chip (H-NoC) is developed for input broadcasting and on-the-fly partial results processing, reducing the data transmission volume and latency. Simulations in 28-nm CMOS technology show <inline-formula> <tex-math notation="LaTeX">$115\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$6.3\times $ </tex-math></inline-formula> higher computing efficiency (GOPs/W) over desktop GPU (Nvidia GTX 1080Ti) and resistive random access memory (ReRAM)-based design, respectively.
MTS: Bringing Multi-Tenancy to Virtual Networking

Multi-tenant cloud computing provides great benefits in terms of resource sharing, elastic pricing, and scalability, however, it also changes the security landscape and introduces the need for strong isolation between the tenants, also inside the network. This paper is motivated by the observation that while multi-tenancy is widely used in cloud computing, the virtual switch designs currently used for network virtualization lack sufficient support for tenant isolation. Hence, we present, implement, and evaluate a virtual switch architecture, MTS, which brings secure design best-practice to the context of multi-tenant virtual networking: compartmentalization of virtual switches, least-privilege execution, complete mediation of all network communication, and reducing the trusted computing base shared between tenants. We build MTS from commodity components, providing an incrementally deployable and inexpensive upgrade path to cloud operators. Our extensive experiments, extending to both micro-benchmarks and cloud applications, show that, depending on the way it is deployed, MTS may produce 1.5-2x the throughput compared to state-of-the-art, with similar or better latency and modest resource overhead (1 extra CPU). MTS is available as open source software.
Implementation of Heuristical PID Tuning for Nonlinear System Control

Quadcopter based technology utilizes a hybrid structure that delivers the ultimate services for auto control system and managements. The main objective of this study is to identify PID parameters for real nonlinear system, which is a Quadcopter flying based on certain parameters via experiment method. The control law has been programmed in Teensy development board wired to 10-DOF IMU ‘Inertial Measurement Unit’ and other sensors in order to get a home-made autopilot. Accordingly, the procedure for PID controller is tuning the autopilot using ‘Ziegler-Nichols’ in order to identify the three parameters of PID which generate a stable response in lowest time-consuming. The Z-N ‘Ziegler-Nichols’ has been implemented in real time case for Quadcopter application through altitude stabilization in a nonlinear system. In conclusion, the results shows that, the significant contribution of Ziegler-Nichols implementation in nonlinear system of the altitude stabilization has been accurately defined as an alternative method of Ziegler-Nichols which has been originally designed for linear system only.
Memo: Implementing a small imperative language with safe dynamic allocation

In this memo, we discuss an implementation ofModula-X, a small imperative language with dynamic allocation and garbage collection. We first describe the language itself and its origins. We then describe our compilation model, and illustrate the front-end and the back-end. We analyse the implications of incorporating safe dynamic storage allocation. Finally we give some performance