A Question Answering System Using Graph-Pattern Association Rules (QAGPAR) On YAGO Knowledge Base

A question answering system (QA System) was developed that uses graph-pattern association rules on the YAGO knowledge base. The answer as output of the system is provided based on a user question as input. If the answer is missing or unavailable in the database, then graph-pattern association rules are used to get the answer. The architecture of this question answering system is as follows: question classification, graph component generation, query generation, and query processing. The question answering system uses association graph patterns in a waterfall model. In this paper, the architecture of the system is described, specifically discussing its reasoning and performance capabilities. The results of this research is that rules with high confidence and correct logic produce correct answers, and vice versa

Shesop Healthcare: Stress and influenza classification using support vector machine kernel

Shesop is an integrated system to make human lives more easily and to help people in terms of healthcare. Stress and influenza classification is a part of Shesop's application for a healthcare devices such as smartwatch, polar and fitbit. The main objective of this paper is to classify a new data and inform whether you are stress, depressed, caught by influenza or not. We will use the heart rate data taken for months in Bandung, analyze the data and find the Heart rate variance that constantly related with the stress and flu level. After we found the variable, we will use the variable as an input to the support vector machine learning. We will use the lagrangian and kernel technique to transform 2D data into 3D data so we can use the linear classification in 3D space. In the end, we could use the machine learning's result to classify new data and get the final result immediately: stress or not, influenza or not.

Design and implementation of audio communication system for social-humanoid robot Lumen as an exhibition guide in Electrical Engineering Days 2015

Social Robot Lumen is a humanoid robot created to act like human and be human friend. In this study, Lumen scenario is limited on Lumen as an exhibition guide in Electrical Engineering Days 2015, a seminar and exhibition of electrical engineering undergraduate and graduate student of Bandung Institute of Technology. To be an exhibition guide, Lumen is equipped by Nao robot, a server, and processing applications. Audio communication system is one of the processing applications. The purpose of the system is to create verbal communication that allow Lumen to receive human voice and respond naturally to it. To be able to communicate like a human, audio communication system is built with speech recognition module to transform speech data into text, speech synthesizer module to transform text data into speech, and gender identification module to distinguish adult female and male voice. Speech recognition module is implemented using Google Speech Recognition API, speech synthesizer module is implemented using Acapela engine, and gender identification module implemented by utilizing speech signal feature that is extracted using Fast Fourier Transform algorithm. Hardware used for implementation are Nao robot, computer, and wireless modem. ----- Lumen Robot Sosial Robot merupakan robot humanoid yang diciptakan agar dapat bersikap seperti manusia dan menjadi teman bagi manusia. Sistem komunikasi audio merupakan salah satu aplikasi pengolah yang bertujuan agar Lumen dapat menerima suara manusia dan meresponnya dengan natural, yaitu seperti cara manusia merespon manusia lainnya. Untuk dapat berkomunikasi seperti manusia, sistem komunikasi audio dilengkapi dengan tiga buah modul: speech recognition untuk mengubah data suara menjadi teks, speech synthesizer untuk mengubah data teks menjadi suara, dan gender identification untuk membedakan suara wanita dan pria.

Design and implementation of computational platform for social-humanoid robot Lumen as an exhibition guide in Electrical Engineering Days 2015

Social Robot Lumen is an Artificial Intelligence development project that aims to create an Artificial Intelligence (AI) which allows a humanoid robot to communicate with human being naturally. In this study, Lumen will be developed to be a tour guide in Electrical Engineering Days 2015 exhibition. In developing an AI, there are a lot of modules that need to be developed separately. To make the development easier, we need a computational platform which becomes basis for all developers to give easiness in developing the modules in parallel way. That computational platform that developed by the writer is called Lumen Server. Lumen Server has two main function, which are to be a bridge between all Lumen intelligence modules with NAO robot, and to be the communication bridge between those Lumen intelligence modules. For the second function, Lumen Server implements the AMQP protocol using RabbitMQ. Besides that, writer also developed a control system for robot movement called Lumen Motion. Lumen motion is implemented by modelling the movement of NAO robot and also by creating a control system using fuzzy logic controller. Writer also developed a program that connects all Lumen intelligence modules so that Lumen can act like a tour guide. The implementation of this program uses FSM and event-driven program. From implementation result, all the features which were designed are successfully implemented. By the developing of this computational platform, it can ease the development of Lumen in the future. For next development, it must be focused on creating integration system so that Lumen can be more responsive to the environment. ----- Sosial Robot Lumen adalah proyek pengembangan kecerdasan buatan yang bertujuan untuk menciptakan kecerdasan buatan atau artificial intelligence (AI) yang memungkinkan robot untuk dapat berkomunikasi dengan manusia secara alami.

Design and implementation of image processing system for Lumen social robot-humanoid as an exhibition guide for Electrical Engineering Days 2015

Lumen Social Robot is a humanoid robot development with the purpose that it could be a good friend to all people. In this year, the Lumen Social Robot is being developed into a guide in the exhibition and in the seminar of the Final Exam of undergraduate and graduate students in Electrical Engineering ITB, named Electrical Engineering Days 2015. In order to be the guide in that occasion, Lumen is supported by several things. They are Nao robot components, servers, and multiple processor systems. The image processing system is a processing application system that allows Lumen to recognize and determine an object from the image taken from the camera eye. The image processing system is provided with four modules. They are face detection module to detect a person's face, face recognition module to recognize a person's face, face tracking module to follow a person's face, and human detection module to detect humans based on the upper parts of person's body. Face detection module and human detection module are implemented by using the library harcascade.xml on EMGU CV. Face recognition module is implemented by adding the database for the face that has been detected and store it in that database. Face tracking module is implemented by using the Smooth Gaussian filter to the image. ----- Lumen Sosial Robot merupakan sebuah pengembangan robot humanoid agar dapat menjadi teman bagi banyak orang. Sistem pengolahan citra merupakan sistem aplikasi pengolah yang bertujuan Lumen dapat mengenali dan mengetahui suatu objek pada citra yang diambil dari camera mata Lumen. System pengolahan citra dilengkapi dengan empat buah modul, yaitu modul face detection untuk mendeteksi wajah seseorang, modul face recognition untuk mengenali wajah orang tersebut, modul face tracking untuk mengikuti wajah seseorang, dan modul human detection untuk mendeteksi manusia berdasarkan bagian tubuh atas orang

Penambahan emosi menggunakan metode manipulasi prosodi untuk sistem text to speech bahasa Indonesia

Adding an emotions using prosody manipulation method for Indonesian text to speech system. Text To Speech (TTS) is a system that can convert text in one language into speech, accordance with the reading of the text in the language used. The focus of this research is a natural sounding concept, the make "humanize" for the pronunciation of voice synthesis system Text To Speech. Humans have emotions / intonation that may affect the sound produced. The main requirement for the system used Text To Speech in this research is eSpeak, the database MBROLA using id1, Human Speech Corpus database from a website that summarizes the words with the highest frequency (Most Common Words) used in a country. And there are 3 types of emotional / intonation designed base. There is a happy, angry and sad emotion. Method for develop the emotional filter is manipulate the relevant features of prosody (especially pitch and duration value) using a predetermined rate factor that has been established by analyzing the differences between the standard output Text To Speech and voice recording with emotional prosody / a particular intonation. The test results for the perception tests of Human Speech Corpus for happy emotion is 95 %, 96.25 % for angry emotion and 98.75 % for sad emotions. For perception test system carried by intelligibility and naturalness test. Intelligibility test for the accuracy of sound with the original sentence is 93.3%, and for clarity rate for each sentence is 62.8%. For naturalness, accuracy emotional election amounted to 75.6 % for happy emotion, 73.3 % for angry emotion, and 60 % for sad emotions. ----- Text To Speech (TTS) merupakan suatu sistem yang dapat mengonversi teks dalam format suatu bahasa menjadi ucapan sesuai dengan pembacaan teks dalam bahasa yang digunakan.