• • Part of the book series (LNCS, volume 10752) Abstract Our world is becoming more interconnected and intelligent, huge amount of data has been generated newly. Home appliances’ energy usage is the basis of home energy management and highly depends on weather condition and environment. Using weather in context, it is theorized that usage of home energy would be higher in cold days. Time series and contextual data collected from sensors can be monitored and controlled in home appliances network. The aim of this work is to propose a deep neural network architecture and apply it to a contextual and multivariate time series data. Long short-term memory (LSTM) models are powerful neural networks based on past behaviours in long sequences.

LSTM networks have been demonstrated to be particularly useful for learning sequences containing longer-term patterns of unknown length, due to their ability to maintain long-term memory. In this work, we incorporate contextual features into the LSTM model because of ability of keeping context of data for a long-time, and for analysing it we integrated two different datasets; the first dataset contains measurements about house temperature and humidity measured over a period of 4.5 months by a 10 min intervals using a ZigBee wireless sensor network. The second dataset contains measurements about individual household electric power consumptions gathered over a period of 47 months. From the wireless network, the data from the kitchen, laundry and living room were ranked the highest in importance for the energy prediction. Li, D., Park, H.W., Ishag, M.I.M., Batbaatar, E., Ryu, K.H.: Design and partial implementation of health care system for disease detection and behavior analysis by using DM techniques. In: 2016 IEEE 14th International Conference on Dependable, Autonomic and Secure Computing, 14th International Conference on Pervasive Intelligence and Computing, 2nd International Conference on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech), pp. IEEE, August 2016 Copyright information.

A lightweight C library for artificial neural networks neural-network deep-learning 516 commits 1 branch. KANN is a standalone. Prediction of Disease Level Using Multilayer Perceptron of Artificial Neural Network for Patient Monitoring. Development of appropriate project management factors for the construction industry in Kenya. International Journal of Soft Computing and Engineering (IJSCE), ISSN:2231-2307,Vol 4,Issue 1. Zurada, J.M., Introduction to Artificial.

1 INTO BRAILLE USING NEURAL NETWORK 1 Assistant Prof. Hassan 2 Ahmed G. Mohammed 3 Abstract The Braille system is a method that is widely used by blind people to read and write. Braille generally consists of cells of raised dots arranged in a grid. The presence or absence of dots can be sensed by the blind people s fingertips to give them the coding for the symbol.

The electronic revolution is changing the way Braille is produced, stored and retrieved, making it easier to use in the work place. All kinds of materials can be put into Braille, from bank statements, bus timetables, maps to music. But it is still difficult to produce an error-free Braille for complex materials. In this paper, the ability of the neural networks will be tested to be used for translating scanned text pages, books or lectures from English language into Grade I Braille; so that blind people can deal with it. An artificial neural network is designed with minimum structure and tested to convert the English characters into grade I literary Braille code. Installing Php Windows. English characters will be assumed to be affected by noise of mean variant between 0 and 0.4.The output of the N.N can be stored in a data file that can be sent into a Braille printer or a Braille display. Hp And Compaq Windows Xp Home Edition Sp3 more.

Keywords: Neural Network, conversion, Braille, English characters. الخلاصة نظام بریل ھو الا سلوب الذي یستخدم على نطاق واسع من قبل المكفوفین لغرض القراءة والكتابة. تتا لف طریقة برایل عموما من خلایا نقاط رفع مرتبة في شبكة. إن وجود أو عدم وجود نقاط یمكن أن یتحسسھ الشخص الا عمى بواسطة رأس الا صبع لمنحھ الترمیز للرمز. غیرت الثورة الا لكترونیة طریقة إنتاج بریل وتخزینھا واستردادھا مما یجعل من السھل إستخدامھا في مكان العمل. ویمكن لجمیع أنواع المواد أن توضع في طریقة برایل أبتداءا من البیانات المصرفیة الى الجداول الزمنیة للحافلة وخراي ط الموسیقى. ولكن لا یزال من الصعب أن تنتج طریقة برایل خالیة من الا خطاء للمواد المعقدة.

سیتم في ھذا البحث إختبار قدرة الشبكات العصبیة المستخدمة لترجمة صفحات النص التي تم مسحھا ضوي یا أو كتب أو محاضرات من اللغة الا نكلیزیة إلى برایل من النوع الا ول بحیث یمكن للمكفوفین أن یتعاملوا معھ. تم تصمیم شبكھ عصبیھ اصطناعیة بالحد الا دنى للھیكل وتم اختبارھا لتحویل أحرف اللغة الا نكلیزیة الى برایل من النوع الا ول الا دبیھ. تم أفتراض أن الا حرف الا نكلیزیة تتا ثر بضجیج بمتوسط متغیر بین (0 و 0,4).ویمكن لخرج الشبكھ العصبیھ تخزینھا في ملف بیانات والتي یمكن إرسالھا إلى طابعة برایل أو عرضھا على شاشھ. 1 This paper was presented in the Engineering Conference of Control, Computers and Mechatronics On Jan /2011, University of Technology. 2 Control and Systems Eng. /University of Technology 3 Rimal Medical Services Company 30 2 1- Introduction: The Braille system is a method that is widely used by blind people to read and write; Figure (1). Braille generally consists of cells of six raised dots arranged in a grid of two dots horizontally by three dots vertically.