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作者： Sprager, Sebastijan Zazula, Damjan System Software Laboratory University of Maribor Faculty of Electrical Engineering and Computer Science Smetanova ulica 17 2000 Maribor Slovenia

ISBN: (纸本)9789604741359

This paper describes gait identification using cumulants of accelerometer data. Accelerometer data of three different walking speeds for each subject (normal, slow and fast) was acquired by a cell phone placed on the person's hip. Data analysis was based on gait cycles that were detected first. Cumulants of order from 1 to 4 with lags from 0 to 10 for second, third and fourth order cumulants were calculated from the cycles and used as feature vectors for classification which was accomplished by support vector machines (SVM). Six healthy young subjects participated in the experiment. According to their gait classification the average recognition rate was 93.1%. A similarity measure for discerning different walking types of the same subject was also introduced using principal component analysis (PCA).

关键词： Accelerometers

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Creating granular learning object towards reusability of Learning Object in e-learning context

Creating granular learning object towards reusability of Lea...

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2011 International Conference on Electrical engineering and Informatics, ICEEI 2011

作者： Noor, Siti Fadzilah Mat Yusof, Norazah Hashim, Siti Zaiton Mohd School of Information Technology Faculty of Technology and Information Science National University of Malaysia Malaysia Software Engineering Department Faculty of Computer Science and Information System University Technology of Malaysia Malaysia

ISBN: (纸本)9781457707520

Learning Object (LO) is one of the main research topics in the e-learning community in the recent years, and most researchers pay attention to the issue of Learning Object Reusability. The most obvious motivation is the economic interest of reusing learning material instead of repeatedly authoring it. In this paper we present the process of creating granular learning object for enabling the reusing of LO in e-Learning context. Reusability requires the LO to be in a fine-grain form because raw media elements are often much easier to reuse then aggregate assemblies. In other words, as the LO size decreases (lower granularity), its potential for reuse increases. A prototype of learning objects repository that contain granular LO has been developed to show the process of granularizing LO. Each of existing LO will be extracted into granular element with the metadata and the system generated unique id for each LO based on its identifier (URL of LO) and save automatically the metadata contain in the LO. These metadata will be used for searching and retrieval process of the granule LO. © 2011 IEEE.

关键词： Metadata

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Performance analysis on the effect of G.729, speex and GSM speech codec on 802.11g wireless local area network over VoIP using packet jitter

International Journal of Control and Automation

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International Journal of Control and Automation 2013年第4期6卷 387-396页

作者： Kamarudin, Imran Edzereiq Md Sharif, Syahrizal Azmir Herawan, Tutut Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Lebuh Raya Tun Razak Gambang 26300 Kuantan Pahang Malaysia Department of Mathematics Education Universitas Ahmad Dahlan Jalan Prof Dr Soepomo 55166 Yogyakarta Indonesia

In this paper, three speech codecs;G.729 (8 kbps), Speex (8kbps) and GSM (13kbps) were tested together with several predetermined SNR value ranging from 10dB to 45dB with a sample of 8 second speech. VoIP QoS such as packet jitter is analyzed in order to make a comparison of speech quality of those three speech codecs in wireless LAN 802.11g environment. Result showsthat at lower SNR, GSM achieve higher packet jitter than that G.729 and Speex. At higher SNR, GSM achieves lower packet jitter as compared than that G.729 and Speex.

关键词： Wireless local area networks (WLAN)

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Managing the software process with a software process improvement tool in a small enterprise

Managing the software process with a software process improv...

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作者： García, Iván Pacheco, Carla Mendoza, Eloy Calvo-Manzano, Jose A. Cuevas, Gonzalo Feliu, Tomás San Postgraduate Department Technological University of the Mixtec Region Mexico Languages and Information System and Software Engineering Department Faculty of Computer Science Polytechnic University of Madrid Spain

Top-down process improvement approaches provide a high-level model of what the process of a software development organization should be. Such models are based on the consensus of a designated working group on how software should be developed or maintained. They are very useful in that they provide general guidelines on where to start improving, and in which order. However, the majority of them have only worked in scenarios within large companies. We aim to help small software development organizations to adopt an iterative approach by providing a Process Improvement Web-based Tool (SysProVal). This paper presents research into the proposal that a small organization may use this tool to define and implement a set of project management practices that can be strengthened using the CMMI-DEV 1.2 model as reference. Copyright © 2010 John Wiley & Sons, Ltd.

关键词： software design

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Recurrent neural network with backpropagation through time for speech recognition

Recurrent neural network with backpropagation through time f...

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IEEE International Symposium on Communications and Information Technologies: Smart Info-Media systems, ISCIT 2004

作者： Ahmad, Abdul Manan Ismail, Saliza Samaon, Den Fairol Universiti Teknologi Malaysia Department of Software Engineering Faculty of Computer Science and Information System Universiti Teknologi Malaysia 81310 Skudai Johor Darul Takzim Malaysia

ISBN: (纸本)0780385934

The study on speech recognition and understanding has been done for many years. In this paper, we propose a fully-connected hidden layer between the input and state nodes and the output. Besides that, we also investigate and show that this hidden layer makes the learning of complex classification tasks more efficient. We also investigate difference between LPCC and MFCC in feature extraction process. The aim of the study was to observe the difference of Arabic's alphabet like "alif" until "ya". The purpose of this research is to upgrade the people's knowledge and understanding on Arabic's alphabet or word by using Fully-Connected Recurrent Neural Network (FCRNN) and Backpropagation through Time (BPTT) learning algorithm. 6 speakers (a mixture of male and female) are trained in quiet environment. Neural Network is well-known as a technique that has the ability to classified nonlinear problem. Today, lots of researches have been done in applying Neural Network towards the solution of speech recognition [1] such as Arabic. The Arabic language offers a number of challenges for speech recognition [2]. Even though positive results have been obtained from the continuous study, research on minimizing the error rate is still gaining lots of attention. This research utilizes Recurrent Neural Network, one of Neural Network technique to observe the difference of alphabet "alif" until "ya".

关键词： Neural networks

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A Lightweight Deep Learning-Based Model for Tomato Leaf Disease Classification

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computers, Materials & Continua 2023年第12期77卷 3969-3992页

作者： Naeem Ullah Javed Ali Khan Sultan Almakdi Mohammed S.Alshehri Mimonah Al Qathrady Eman Abdullah Aldakheel Doaa Sami Khafaga Department of Software Engineering University of Engineering and TechnologyTaxila4400Pakistan Department of Computer Science Faculty of PhysicsEngineeringand Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Departments of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Tomato leaf diseases significantly impact crop production,necessitating early detection for sustainable *** Learning(DL)has recently shown excellent results in identifying and classifying tomato leaf ***,current DL methods often require substantial computational resources,hindering their application on resource-constrained *** propose the Deep Tomato Detection Network(DTomatoDNet),a lightweight DL-based framework comprising 19 learnable layers for efficient tomato leaf disease classification to overcome *** Convn kernels used in the proposed(DTomatoDNet)framework is 1×1,which reduces the number of parameters and helps in more detailed and descriptive feature extraction for *** proposed DTomatoDNet model is trained from scratch to determine the classification success rate.10,000 tomato leaf images(1000 images per class)from the publicly accessible dataset,covering one healthy category and nine disease categories,are utilized in training the proposed DTomatoDNet *** specifically,we classified tomato leaf images into Target Spot(TS),Early Blight(EB),Late Blight(LB),Bacterial Spot(BS),Leaf Mold(LM),Tomato Yellow Leaf Curl Virus(YLCV),Septoria Leaf Spot(SLS),Spider Mites(SM),Tomato Mosaic Virus(MV),and Tomato Healthy(H).The proposed DTomatoDNet approach obtains a classification accuracy of 99.34%,demonstrating excellent accuracy in differentiating between tomato *** model could be used on mobile platforms because it is lightweight and designed with fewer *** farmers can utilize the proposed DTomatoDNet methodology to detect disease more quickly and easily once it has been integrated into mobile platforms by developing a mobile application.

关键词： CNN deep learning DTomatoDNet tomato leaf disease classification smart agriculture

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Study on Potability Water Quality Classification Based on Integrated Learning 16

Study on Potability Water Quality Classification Based on In...

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16th IEEE International Conference on Intelligent systems and Knowledge engineering, ISKE 2021

作者： Fen, Li Fen Lei, Zhou Ting, Chen Huaiyin Institute of Technology Faculty of Computer and Software Engineering Research Center for Logic and Intelligent Computation National-Local Joint Engineering Lab of System Credibility Automatic Verification Huaian China

ISBN: (纸本)9781665405539

Aiming at the problem of low accuracy of simple classification model, based on the drinking water data set of kaggle official website, integrated learning models is proposed, which improves the precision and accuracy of binary classification of drinking water quality. K-fold cross validation was performed to measure model consistency. The effect of set classifier is higher than that of simple classifier. © 2021 IEEE.

关键词： Water quality

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Fast Division Algorithm for Finite Real Number 16

Fast Division Algorithm for Finite Real Number

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16th IEEE International Conference on Intelligent systems and Knowledge engineering, ISKE 2021

作者： Chen, Ting Li, Fenfen Lin, Jinbao National-Local Joint Engineering Lab of System Credibility Automatic Verification Huaiyin Institute of Technology Faculty of Computer and Software Engineering Research Center for Logic and Intelligent Computation Huai'an China

ISBN: (纸本)9781665405539

The data representation and division for finite real number in computers has always been a hot topic in the fields of scientific research and engineering technology. With the research of existing real number division algorithm, design, improvement and adjustment for data structure, algorithm and programming language, and realize the fast division for finite real number. The algorithm can apply to the engineering requirement of finite real number of 506 bits. It replaces the commonly used trial division method with a comparison method, reducing the time complexity of the algorithm. The experimental results demonstrate the correctness and efficiency of the algorithm. The division of the algorithm uses comparison instead of trial division, which reduces the time complexity of the algorithm from O(n2) to O(n). The experimental results show that the algorithm is correct and efficient. © 2021 IEEE.

关键词： Computational complexity

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Narrowband-internet of things (NB-IoT) system for elderly healthcare services 5

Narrowband-internet of things (NB-IoT) system for elderly he...

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5th International Conference on engineering, Applied Sciences and Technology, ICEAST 2019

作者： Manatarinat, Wiraphon Poomrittigul, Suvit Tantatsanawong, Panjai Electrical Engineering Department Faculty of Engineering Pathumwan Institute of Technology Bangkok Thailand Software Engineering and Information System Department Faculty of Science and Technology Pathumwan Institute of Technology Bangkok Thailand Computer Technology Department Faculty of Science Silpakorn University Bangkok Thailand

ISBN: (纸本)9781728100678

3G and 4G wireless communication technology, which requires broad network resources and large amounts of available electricity, was designed for high-speed Internet usage. Most narrowband-Internet of Things (NB-IoT) devices do not require high-speed Internet because most IoTs work by sending commands to and receiving commands from a server only. NB-IoT is a low-power wide area (LPWA) technology that was developed to accommodate a broad variety of new IoT devices. A low-power wide area network (LPWAN) uses narrow frequencies that support the use of devices in the 900 MHz frequency range that are inexpensive and that can be used in both buildings and wide areas. NB-IoT devices can also be used to assist medical patients, the elderly, and disabled people that are susceptible to falling. Our newly developed monitoring system has the ability to immediately recognize a fall, and then automatically alert up to 4 contacts via the LINE application. If dispatch of a medical unit is required, the patient's location is automatically available without the need for voice contact by the patient. © 2019 IEEE.

关键词： Internet of things

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Smart cane: Assistive cane for visually-impaired people

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International Journal of computer Science Issues 2011年第4 4-2期8卷 21-27页

作者： Wahab, Mohd Helmy Abd Talib, Amirul A. Kadir, Herdawatie A. Johari, Ayob Noraziah, A. Sidek, Roslina M. Mutalib, Ariffin A. Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia 86400 Batu Pahat Johor Malaysia Faculty of Software Engineering and Computer System Universiti Malaysia Pahang 26300 Kuantan Pahang Malaysia College of Arts and Sciences Universiti Utara Malaysia 06010 Sintok Kedah Malaysia

This paper reports on a study that helps visually-impaired people to walk more confidently. The study hypothesizes that a smart cane that alerts visually-impaired people over obstacles in front could help them in walking with less accident. The aim of the paper is to address the development work of a cane that could communicate with the users through voice alert and vibration, which is named Smart Cane. The development work involves coding and physical installation. A series of tests have been carried out on the smart cane and the results are discussed. This study found that the Smart Cane functions well as intended, in alerting users about the obstacles in front.

关键词： Assistive technology

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