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1st International Conference on Medical engineering, Health Informatics and Technology, MediTec 2016

作者： Islam, Md. Ariful Alvi, Hassan Nomani Mamun, Khondaker Abdullah Al Advanced Intelligent Multidisciplinary Systems Lab Department of Computer Science and Engineering United International University Dhaka Bangladesh

ISBN: (纸本)9781509054213

Worldwide the number of diabetes patient is increasing and the rate is alarming in countries with low and middle income. Medication of a diabetes patient still costly which leads to high mortality in developing and low income countries. Considering the fact that diabetes is a non-curable disease, prevention and management is a big deal. However, proper lifestyle management requires awareness, knowledge and care. Information and Communication technology has made life easier as information can be found more easily. Smartphone based applications are also becoming more popular as prices are lowering every day. Sharing knowledge, creating awareness, disease management and even diagnosis is possible using smartphone applications. In this article we discussed possible solution of diabetes management and prevention through mobile application and also presented our intelligent application, DiaHealth for diabetes management and prevention. To do this, we added recent trends of diabetes based mobile application and compared DiaHealth with other popular applications. Then detailed feature is given in a structured manner. With the technological advancement, we believe DiaHealth will shed light to diabetes patients to manage their health and life style, consequently it will prevent health consequence and reduce healthcare cost. © 2016 IEEE.

关键词： Smartphones

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On the combination of local texture and global structure for food classification

On the combination of local texture and global structure for...

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IEEE Internaitonal Conference on Multimedia Information Processing and Retrieval

作者： Zong, Zhimin Nguyen, Duc Thanh Ogunbona, Philip Li, Wanqing Advanced Multimedia Research Lab. ICT Research Institute School of Computer Science and Software Engineering Australia

ISBN: (纸本)9780769542171

This paper proposes a food image classification method using local textural patterns and their global structure to describe the food image. In this paper, a visual codebook of local textural patterns is created by employing Scale Invariant Feature Transformation (SIFT) interest point detector with the Local Binary Pattern (LBP) feature. In addition to describing the food image using local texture, the global structure of the food object is represented as the spatial distribution of the local textural structures and encoded using shape context. We evaluated the proposed method on the Pittsburgh Fast-Food Image (PFI) dataset. Experimental results showed that the proposed method could obtain better performance than the baseline experiment on the PFI dataset. © 2010 IEEE.

关键词： Local binary pattern

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Research on improved full-factor deep information mining algorithm

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Cognitive Robotics 2022年 2卷 30-38页

作者： Man, Yun Fei, Xu Jun, Liu Qian, Zhang School of Computer Science and Engineering Xi'an Technological University Xi'an China Engineering Laboratory The State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control Xi'an China 63768 Unit of the Chinese People's Liberation Army

In the use of fire-fighting physics platform for fire alarm data correlation analysis, there are often problems such as too much data volume and insufficient accuracy of the analysis results. For such questions, this paper establishes a full-factor secondary mining mechanism for fire accidents based on the fire big data based on the correlation analysis algorithm and the clustering algorithm. The association algorithm is used to conduct full-factor primary mining on the fire-related factors in the data warehouse, and the common-sense accident attributes in the association rules are extracted. Then use the K-means clustering algorithm, where the cluster center is the relevant attribute in the fire accident record, and perform the second combined clustering of the accident elements to achieve in-depth information mining of all factors of the fire accident. Experimental results show that the improved full-factor deep information mining algorithm proposed in this paper can effectively filter 31.6% of meaningless mining results compared to the traditional single mining algorithm. It shows that the algorithm in this paper can more accurately dig out the relationship between data, and can provide more effective decision support for fire management and other work. © 2022

关键词： Fires

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Resonance based contactless energy transfer

Resonance based contactless energy transfer

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2012 3rd Power Electronics, Drive Systems and Technologies Conference, PEDSTC 2012

作者： Hasanzadeh, Saeed Vaez-Zadeh, Sadegh Advanced Motion Systems Research Lab. School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781467301114

In this paper, efficiency analysis and design of contactless electric energy transmission systems using inductive method are elaborated. Large leakage inductances of the systems are to be compensated to achieve resonance conditions for maximum efficiency in energy transfer from a launch side to a receiving side where compensating circuits are utilized in both sides. Considering the circuit models of a contactless electrical energy transmission system, the effects of different system parameters including the compensating capacitors are analyzed for a specified frequency range and coupling factor. An algorithm is proposed to determine the optimal compensating capacitors and system resonance frequency to achieve high efficiency. © 2012 IEEE.

关键词： Inductive power transmission

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Optimizing execution for pipelined-based distributed deep learning in a heterogeneously networked GPU cluster

Optimizing execution for pipelined-based distributed deep le...

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作者： Zhang, Jinghui Zhan, Jun Li, Jiange Jin, Jiahui Qian, Lei School of Computer Science and Engineering Southeast University Nanjing China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi China

Exorbitant resources (computing and memory) are required to train a deep neural network (DNN). Often researchers deploy an approach that uses distributed parallel training to acquire larger models faster on GPUs. This approach has its detriments, though;on one hand, a GPU's expanded capacity to compute also produces bigger bottlenecks in inter-GPU's communications during model training, and multi-GPU systems lead to complex connectivity. Workload schedulers then end up having to consider hardware topology and requirements for workload communication, in hopes of allocating GPU resources to optimize execution time and improve usage in a heterogeneous environment. On the other hand, the high memory requirements to train a DNN model make running the training processes on GPUs onerous. To contend with this, we introduce two execution optimization methods based on pipeline-hybrid parallelism (using both data and model parallelism) in a GPU cluster with heterogeneous networking. First, we propose a model partition algorithm that accelerates pipeline-hybrid parallelism training between heterogeneously network-connected GPUs. Second, we introduce a cost-balanced recomputing algorithm to reduce memory usage in the pipeline mode. Experiments show that our solution (Pipe-Torch) averages a speedup of 1.4× compared with data parallelism, and reduces the memory footprint while maintaining pipelined load-balanced training. © 2020 John Wiley & Sons Ltd

关键词： Pipelines

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Extended UML with Role Modeling

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Wuhan University Journal of Natural Sciences 2001年第Z1期6卷 175-182页

作者： He Ke\|qing 1, Jiang Hong 1, He Fei 2, Ying Shi 3 1 School of computer Science,Wuhan University,Wuhan 430072,China 2.Japan advanced Institute of Science and Technogy,923\|1292,Japan 3.Stae Key lab. of Software engineering, Wuhan University,Wuhan School of Computer Science Wuhan University Wuhan China Japan Advanced Institute of Science and Technogy Japan Stae Key Lab. of Software Engineering Wuhan University Wuhan China

UML is widely accepted and applied by the international software industry. UML is a powerful language for Object oriented modeling, designing, and implementing software systems, but its Use Case method for requirement analysis and modeling software patterns has some explicit drawbacks. For more complete UML, this paper proposes the Role Use Case modeling and its glyphs, and provides an instance of requirement analysis using Role Use Case method. Uses the Role Model to modeling software pattern at knowledge level. This paper also extends the UML Meta Model and accentuates “RM before UML's class Modeling”.

关键词： UML role role modeling software pattern use case

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A vision based voice controlled indoor assistant robot for visually impaired people

A vision based voice controlled indoor assistant robot for v...

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2020 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2020

作者： Mahmud, Saifuddin Haque Sourave, Redwanul Islam, Milon Lin, Xiangxu Kim, Jong-Hoon Kent State University Advanced Telerobotics Research Lab Computer Science KentOH United States Khulna University of Engineering Technology Computer Science and Engineering Khulna Bangladesh

ISBN: (数字)9781728196152

ISBN: (纸本)9781728196152

Due to ever-increasing number of visually impaired people, the demands of assistant robots have been growing significantly. For the visually impaired, "independent living"which is the key to rebuild the dignity and self-confidence that can be achieved by assistant robot. This paper describes the design and development of a personal assistant robot, which is controlled by voice commands to find and determine the relative location of the object in the indoor environment with a corelation factor (CRF) algorithm developed in this study. The proposed assistant robot is a semi-humanoid robot consists of several cameras on the different location of its body. The cameras are used for autonomous movement, object detection, distance measurement, and motion planning. In addition, the robot keeps the user informed about the outcomes of its actions increases the usefulness of the robot. To justify the proposed system and measure its performance, successful experiments were conducted in indoor environments. The experimental results demonstrate that the proposed assistant robot performs all of its actions with high accuracy which will make visually impaired people feel the indoor environment safe, convenient and comfortable. © 2020 IEEE.

关键词： Anthropomorphic robots

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OSM2Net: A Robust Road Network Extraction Framework from Noisy Indoor Parking OpenStreetMap

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IEEE Internet of Things Journal 2025年

作者： Cao, Yu Guo, Xiansheng Boateng, Gordon Owusu Ansari, Nirwan Si, Haonan Qian, Bocheng Liu, Xinhao Xia, Huang Liu, Yinong University of Electronic Science and Technology of China Department of Electronic Engineering Chengdu 611731 China Xi'an Jiaotong-Liverpool University Department of Communications and Networking Suzhou 215123 China New Jersey Institute of Technology Advanced Networking Lab Department of Electrical and Computer Engineering Newark 07102 NJ United States

Intelligent Transportation Systems (ITS) rely on high-precision road networks, which are particularly scarce in indoor parking. Existing methods depend on expensive hardware (e.g., LiDAR) or manual mapping, both of which are costly and inefficient. The rise of the Internet of Things (IoT) has enabled large-scale data collection and connectivity, offering new opportunities for automated road network extraction. OpenStreetMap (OSM), as a crowdsourced IoT-driven platform, provides multi-layer geospatial data, including the Road Network Layer (RNL), Lane Boundary Layer (LBL), and Turn Sign Layer (TSL). However, OSM data often suffers from incompleteness and noisy connectivity, affecting the continuity and accuracy of road networks. This paper introduces OSM2Net, a novel framework designed to extract road networks from individual layers and leverage multi-layer data to construct directed road networks. Specifically, OSM2Net rasterizes noisy OSM data into bitmaps for image processing and multi-layer fusion. By leveraging the topology relationship between lane boundaries and road networks, a Lane-Road Map Generator (LRMG) creates a simulated dataset for training. Then, utilizing the simulated dataset, a Lane2Net model is designed to extract road networks from sparse lane boundary images. The framework then vectorizes bitmaps into a lightweight, undirected road network and refines it into a directed network by extracting and matching turn sign information. Experimental results show that Lane2Net achieves Intersection over Union (IoU) of 93% and 92% using simulated and real-world datasets, respectively. Extensive experiments on real-world datasets confirm that OSM2Net delivers robust completeness and high-quality road network extraction. © 2014 IEEE.

关键词： indoor parking lane-road map generator OpenStreetMap Road network extraction

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Solder Joint Reliability Comparison Under JEDEC Drop and System-Like Drop Test Conditions 23

Solder Joint Reliability Comparison Under JEDEC Drop and Sys...

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23rd International Conference on Electronics Packaging, ICEP 2024

作者： Shih, Meng-Kai Ke, Zih-Jun Yen, Chun-Yu Lai, Wei-Hong Kao, Chin-Li National Formosa University Department Of Mechanical And Computer-Aided Engineering Taiwan Advanced Semiconductor Engineering Inc. Stress Lab. Taiwan

ISBN: (纸本)9784991191176

The desire for consumer electronics such as handheld and wearable devices, along with Internet-of-Things (IoT) gadgets like smart TVs, speakers, and toys, has surged significantly in recent times and continues to expand. Concurrently, drop shock failure emerges as a prevalent and crucial issue for these handheld and portable electronic devices. In this study, a computational model is developed to evaluate the solder joint stress of the WLCSP under both JEDEC drop and system-like drop conditions. Subsequently, Taguchi experiments are conducted to assess the impact of three control factors on solder joint stress post system-like drop testing: (1) die thickness, (2) PI elastic modulus, and (3) PCB elastic modulus. Ultimately, the findings from the Taguchi analysis guide the identification of the optimal packaging design that effectively minimizes solder joint stress in the WLCSP package. © 2024 Japan Institute of Electronics Packaging.

关键词： Finite element method

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NEXT:a neural network framework for next POI recommendation

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Frontiers of computer Science 2020年第2期14卷 314-333页

作者： Zhiqian ZHANG Chenliang LI Zhiyong WU Aixin SUN Dengpan YE Xiangyang LUO Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of EducationSchool of Cyber Science and EngineeringWuhan UniversityWuhan 430072China Department of Computer Science The University of Hong KongPokfulam RoadHong Kong 999077China School of Computer Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore State Key Lab of Mathematical Engineering and Advanced Computing Zhengzhou 450001China

The task of next POI recommendations has been studied extensively in recent ***,developing a unified recommendation framework to incorporate multiple factors associated with both POIs and users remains challenging,because of the heterogeneity nature of these ***,effective mechanisms to smoothly handle cold-start cases are also a difficult *** by the recent success of neural networks in many areas,in this paper,we propose a simple yet effective neural network framework,named NEXT,for next POI *** is a unified framework to learn the hidden intent regarding user's next move,by incorporating different factors in a unified ***,in NEXT,we incorporate meta-data information,e.g.,user friendship and textual descriptions of POIs,and two kinds of temporal contexts(i.e.,time interval and visit time).To leverage sequential relations and geographical influence,we propose to adopt DeepWalk,a network representation learning technique,to encode such *** evaluate the effectiveness of NEXT against other state-of-the-art alternatives and neural networks based *** results on three publicly available datasets demonstrate that NEXT significantly outperforms baselines in real-time next POI *** experiments show inherent ability of NEXT in handling cold-start.

关键词： POI neural networks POI recommendation

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