236 research outputs found
Development of an Omni-directional distance sensing system for the Deci Zebro
No full textIn this thesis, we describe the design process of a distance sensing system for the Deci Zebro swarm robots. We use a technique that transmits a radio frequency message and a ultrasonic pulse concurrently. Due to the difference in propagation speed of both signals, the distance could be measured using time difference of arrival (TDOA). A cone shaped antenna is designed to create a 360 ultrasonic pulse coverage. At the end of this thesis we present a prototype with a range of 7 m. We find a linear relation between the TDOA and the actual distance between the modules. We thus conclude that our prototype is suitable for range measurements on roving swarm robots.Zebro ProjectElectrical Engineerin
Comparative Analysis of K-Nearest Neighbors and Decision Tree Methods in Determining Students’ Purchase Interest in MacBook Laptops
No full textIn the context of increasingly competitive technology markets, companies need to know consumer preferences accurately to optimize product offerings and increase sales. Two classification methods that are often used in data mining, namely K-Nearest Neighbors and Decision Tree, have their own advantages and disadvantages. This study proposes a solution that involves processing student data using both classification methods to identify the most accurate and effective method for identifying purchase intentions. This study aims to compare the performance of the two methods in determining student purchase intentions for MacBook laptops. The research methodology includes collecting data from 100 students covering various factors such as user experience, design and portability, technical specifications, price, and security. This data is then classified using the K-Nearest Neighbors and Decision Tree methods. Furthermore, a confusion matrix is used to provide a more detailed picture of the performance of the two methods. The results of the study show that the Decision Tree method has a higher accuracy (91%) compared to K-Nearest Neighbors (88%). In addition, Decision Tree excels in other metrics such as precision (87.18% vs. 85.71%), recall (89.47% vs. 85.71%), specificity (91.94% vs. 89.66%), and F1-Score (88.31% vs. 85.71%). The decision tree also has a higher NPV value and lower FPR and FNR rates than K-Nearest Neighbors, indicating that it is superior in avoiding misclassification. The study's conclusion is that the Decision Tree method is more effective and accurate than K-Nearest Neighbors in determining students' purchase intentions for MacBook laptops. The decision tree shows better performance in almost all evaluation metrics, making it a more reliable method to use in consumer data analysis. The results of this study are expected to help companies choose a more appropriate and effective analysis method for their marketing strategies, as well as provide a basis for further research in the field of consumer purchase intention classification
DECI: A Tutorial on Designing Effective Conversational Interfaces
No full textConversational User Interfaces (CUIs) have been argued to have advantages over traditional GUIs due to having a more human-like interaction. The growing popularity of conversational agents has enabled humans to interact with machines more naturally. There is an increasing familiarity among people with conversational interactions mediated by technology due to the widespread use of mobile devices and messaging services and a hungry market for conversational agents. Based on the recent advances in conversational AI, as a result of the proliferation of large language models, the signs are that the future of human-computer interaction will have a significant conversational component. Today, over two-thirds of the population on our planet has access to the Internet, with ever-lowering barriers to accessibility. This tutorial will showcase the benefits of employing novel conversational interfaces for crowd computing, human-AI decision making, health and well-being, and information retrieval. Given the widespread adoption of AI systems across several domains, we will discuss the potential of conversational interfaces in facilitating and mediating people's interactions with AI systems. The tutorial will include interactive elements and discussions and provide participants with insights to inform the design of effective conversational interfaces. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Web Information System
Obstacle and Cliff Detection for Robotics Applications Using Miniturized Sonar and IR Distance Triangulation: Environment Observation Module For The Deci Zebro
No full textThis is a bachelor thesis about the design and development of an observation and sensing module for the Deci Zebro robot that is being developed at the EEMCS faculty of Delft University of Technology.This part of the thesis is about the development of a cliff- and obstacle detection system, as well as the designanddevelopmentofafittingplasticenclosureforthemoduleandthedesignofaPCBthatintegrates the module’s electronics.The report explores and compares different types of distance sensors and concludes that the best option is to use two infrared-based distance sensors on the left and the right of the robot for cliff detection, and a rotating ultrasonic transceiver on a servo motor to detect obstacles. For easy debugging and to allow communication with nearby humans, a LED ring was also fitted to the top of the module. The design process and the implementation of these components is described in detail.The module’s enclosure is designed using SolidWorks software and afterwards printed using a 3D-printer. The PCB is designed using the opensource KiCad software.Zebro Projec
UNSCHOOLING: A DIRECT EDUCATIONAL APPLICATION OF DECI AND RYAN’S (1985) SELF DETERMINATION THEORY AND COGNITIVE EVALUATION THEORY
No full textUnschooling is a variation of homeschooling where, instead of following a set curriculum, children learn through everyday life experiences. As an increasing number of families are choosing to unschool, it becomes important to further study the workings of this philosophical and educational choice. It is estimated that approximately 12% of families who homeschool, unschool their children. The unschooling environment itself tends to provide space for self-directed and intrinsically motivated learning, and seems to be a direct educational application of Deci and Ryan’s (1985) Self Determination Theory and Cognitive Evaluation Theory. Within this paper, the author describes and expands upon how the unschooling environment is a modern example of true, intrinsically motivated learning. The author also discusses how unschooling families tend to naturally provide the three psychological needs developed within Cognitive Evaluation Theory, specifically the needs of competence, autonomy, and relatedness. Article visualizations
ANALISA OPTIMASI DISTRIBUSI BARANG BANGUNAN MENGGUNAKAN METODE LEAST COST PADA UD . RAMA JAYA PERDAGANGAN
No full textMasalah transportasi adalah masalah pemrograman linier pada umumnya berhubungan dengan distribusi suatu produk dari beberapa sumber, dengan penawaran terbatas menuju beberapa tujuan dengan biaya tertentu pada biaya transportasi minimum. Tujuan dari model transportasi adalah merencanakan pengiriman suatu dari sumber tujuan sedemikian rupa untuk meminimalkan biaya transportasi. Beberapa teknik perhitungan sebagai bahan pertimbangan yang baik dalam membuat suatu kebijakan agar biaya pendistribusian minimal dapat tercapai oleh suatu usaha panglong, dalam hal ini untuk menentukan solusi awal yang layak digunakan metode Least Cost ( biaya minimum)
Prediksi Tweet Netizen Menggunakan Random Forest, Decision Tree, Naïve Bayes, dan Ensemble Algorithm
No full textGubernur DKI Jakarta saat ini, meski sudah terpilih sejak tahun 2017 selalu menarik untuk dibicarakan atau bahkan dikomentari. Komentar yang muncul berasal dari media secara langsung atau melalui media sosial. Twitter menjadi salah satu media sosial yang sering digunakan sebagai media untuk mengomentari gubernur terpilih bahkan bisa menjadi trending topic di media sosial Twitter. Netizen yang berkomentar pun beragam, ada yang selalu menge-Tweet kritik, ada yang berkomentar Positif, dan ada pula yang hanya me-retweet. Dalam penelitian ini, prediksi apakah Netizen aktif akan cenderung selalu menimbulkan komentar Positif atau Negatif akan dilakukan dalam penelitian ini. Model algoritma yang digunakan adalah Decision Tree, Naïve Bayes, Random Forest, dan juga Ensemble. Data Twitter yang diolah harus melalui preprocessing terlebih dahulu sebelum dilanjutkan menggunakan Rapidminer. Dalam uji coba menggunakan Rapidminer dilakukan dalam empat kali uji coba dengan membagi menjadi dua bagian yaitu data testing dan data latih. Perbandingan yang dilakukan adalah 10% data pengujian: 90% data pelatihan, kemudian 20% data pengujian: 80% data pelatihan, kemudian 30% data pengujian: 70% data pelatihan, dan yang terakhir adalah 35% data pengujian: 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini. 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini. 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini
Analysis Of Public Interest In Smartfren SIM Cards Using The K-Nearest Neighbors Method
No full textThe use of Smartfren SIM cards is increasing along with the public's need for fast and stable internet services. However, a deep understanding of public interest in the SIM card is necessary to optimize marketing strategies and increase sales. Proper analysis can help companies identify potential target markets and develop effective marketing strategies. We chose the K-Nearest Neighbors method to analyze public interest in using Smartfren SIM cards. This study aims to develop and evaluate the K-Nearest Neighbors model in predicting public interest in using Smartfren SIM cards. This study uses a dataset containing information about Smartfren SIM card users. We divide the data into two sets: a training set for model building and a test set for evaluating model performance. We apply the K-Nearest Neighbors method to classify the data into two categories: interested and not interested. We evaluate the model performance using accuracy, precision, recall, and F1-score metrics. We present the evaluation results as a confusion matrix. The developed K-Nearest Neighbors model showed excellent performance with an accuracy of 94.29%, a precision of 94.20%, a recall of 100%, and an F1-score of 97.01%. These results indicate that the K-Nearest Neighbors model is effective in predicting people's interest in Smartfren SIM cards. The high recall value indicates that the model is able to identify all interested individuals without missing any, while the high precision value indicates that the model rarely makes false positive prediction errors. This study concludes that the K-Nearest Neighbors method is very effective for use in analyzing people's interest in using Smartfren SIM cards. We can rely on the developed model's strong performance for real-world applications in marketing strategies
Analysis Of Student Satisfaction Level In The Faculty Of Science And Technology Using The Convolution Neural Network Method
No full textThe Faculty of Science and Technology at Labuhanbatu University is one of the leading faculties that focuses on the development of science and technology. This faculty offers various study programs designed to prepare students to face the challenges of the digital era and industrial revolution 4.0. This research, using survey and interview methods, aims to collect accurate and objective data regarding student perceptions and experiences in various aspects, such as the quality of educational services, quality of teaching, and available supporting facilities such as extracurricular activities, seminars and research projects, ease of access. information and academic support from optimal staff and teaching staff
O(100 GeV) deci-weak W '/Z ' at Tevatron and LHC
No full textRecently, Tevatron released their measurements on the invariant mass spectrum of electron and positron, as well as the dijet arising from WW + WZ production, with one W decaying leptonically. Although the statistics are not significant, there are two bumps around 240 GeV and 120-160 GeV, respectively. We proposed that the two bumps correspond to the extra-light gauge bosons Z' and W', which couple with quarks with deci-weak strength. In this brief report, we also simulated dijet invariant mass distribution at the current running LHC.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000291312200003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Astronomy & AstrophysicsPhysics, Particles & FieldsSCI(E)19ARTICLE11null8
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