Earticle

Automatic human fall detection based on video monitoring plays an important role in protecting vulnerable people especially the seniors whose falls could cause severe injuries and need attentions from others immediately. In this paper, an automatic human fall detection method based on human motion tracking and shape aspect ratio in real-time video is proposed. While most existing methods detect falls in homes, the proposed method is suitable for both outdoor and indoor environments. The method first detects human objects in general environment, then tracks their motions, meanwhile calculating and recording the motion characteristics of each person. Comparing with the existing fall detection method using shape aspect ratio, the proposed method has advantages of employing the shape aspect ratio together with the moving speed and direction to better detect human falls, as well as being able to detect falls toward different directions. Experiment results demonstrate that the proposed method can effectively detect human falls in general environments including outdoor places.

The number of incidents involving disconnections and damages of undersea cables caused by ships’ anchors, fishing nets, sudden current changes or other heavy objects thrown overboard has increased recently around the waters of the Republic of Korea. To deal with this situation, the Korean government and its affiliated organizations are providing GPS-assisted alarm units which inform the coordinates of the cables, their routes, and other relevant information, in addition to operating the surveillance ships regularly. Despite such efforts, the number has not decreased widely. Thus, in this paper, we are introducing a Graphic-based Maintenance System developed by the SUNCOM Co. (a venture company) and delivered to KT (Korea Telecom). The system assists in maintaining and managing the undersea cables and its application uses C++ and Visual Basic. Through field tests, the systems have been proven to be effective and efficient in preventing many accidents that could have been caused by human errors and reducing the social and monetary costs involving restoration works and business disruptions.

Because the software reverse analysis method which combined the dynamic and static analyses lacks normative interactive mode, the work of the software reverse analysis is inefficient, and its reusability is poor. Based on dynamic and static analysis process of the embedded software,three kinds of interactive mechanismare proposed, including Static To Dynamic (STD), Dynamic To Static (DTS), Static and Dynamic simultaneous (SDM), and has also presented the method of realizing these three interaction mechanisms in detail. The test results show that interactive mechanisms of STD, DTS and SDM are suitable for correction of abnormal nodes in the results of static analysis, optimization of dynamic information extraction, identification of hidden codes and so on. It can greatly improve work efficiencyof the embedded software reverse analysis.

In this paper, a new fractional-order chaotic system was studied, and the basic dynamic properties of the new system were analyzed. The control of the new system in unstable equilibrium point was realized by designing the reasonable nonlinear controller. Further, we investigated the projective synchronization problem about fractional order chaotic systems with different dimensions, the appropriate controller was designed to achieve the projective synchronization of a four-dimensional drive system and a three-dimensional response system by reducing the dimension. With the numerical simulation of Matlab, the feasibility of the scheme was verified.

This paper designed XMDR-DAI-based hospital information system in mobile cloud environment. The system supported data interoperability service between systems in the process of transmitting data collated from BSN (Body Sensor Network) environment to the hospital information system. This study suggested XMDR-DAI-based MCBS (Mobile Body Cloud System) in the mobile cloud environment. The system integrated sensor information obtained from BSN to support interoperability service for medical information between HIS (Hospital Information System).

Aiming at the problems such as the HIM algorithm has a very high time complexity and cannot be applied in the large social networks and so on, and this paper puts forward the hybrid influence maximization algorithm. The algorithm carries out the detailed experiments on 6 real data sets with different characteristics. The experiments show that compared with the HIM algorithm, the algorithm in this paper has great improvement in the scope of influence.

Writing in its different forms, printed and manuscript has always been a tool essential in human communication, and as ubiquitous in most areas of its operations. It is used to store and archive knowledge. Thereby, human has always developed techniques for sustainability across generations. Indeed, with the advent of new information technologies and electronics computers, and further increase the power of machines, automated processing. Besides, one of the important system is the handwriting recognition. Handwriting text recognition system based on efficient segmentation, DCT and HOG Features is proposed. The proposed system depends on the segmentation of the text into words only. Moreover, the system achieved best recognition accuracy 96.317% based on the used methods and SVM classifier.

Aiming at such shortcomings of traditional Bat algorithm as low precision convergence, premature convergence, slow convergence, an improved BA based on inertia weight factor and Lévy flight (ILBA) has been proposed, which has made two modifications on update equations of bat flying position in BA, using inertia weight factor to keep the flight inertia of bat individual, adaptively adjust the exploitation mechanism of the algorithm in different iteration periods, make the algorithm achieve better convergence precision and altering the strategy about position update of bats from Brownian random walks into Lévy flights strategy to effectively avoid local optimism of the algorithm and guarantee its exploration mechanism while taking advantage of heavy-tailed effect of Lévy flight to speed up the convergence. By means of 4 typical test functions simulation, the results show that ILBA boasts faster convergence and superior optimal performance compared to traditional BA and LBA.

This paper presents the impact of the change of cutting parameters on cutting force and cutting vibration by the milling experiment of PE WPC. In the text, 60% wood flour content and 70% wood flour content WPC are compared in up milling and down milling. The result shows that cutting force shows a progressive increasing trend as the feed speed increasing. The cutting force in up milling is totally smaller than in down milling with the change of cutting speed. Cutting force shows an increasing trend with the cutting width increasing. The impact of feed speed on cutting vibration is more obvious. The cutting vibration of 60% wood flour content is more susceptible than 70% wood flour content. In the cutting speed experiment, the cutting vibration in up milling is obviously bigger than in down milling. The cutting vibration of 60% and 70% wood flour content is almost the same in down milling. However, it is opposite in up milling. The cutting vibration shows a progressive increasing trend in down milling and steady in up milling as the cutting width increases.

In this paper we describe the development of a web-based framework of vessel information system using AIS data to monitor the movement of ship or vessel. The system consist of data acquisition module, data storage module, data management module, visualization and monitoring module. The data acquisition module functions to receive AIS data from all vessels within certain radius and stored in the database by storage module and data management module. Then, the visualization module will display interactively the movement of the vessels. The results show that marine traffic can be visualized by the system and information can be provided in a real time manner through web technology.

Visual sentiment analysis which aims to understand the emotion and sentiment in visual content has attracted more and more attention. In this paper, we propose a hybrid approach for visual sentiment concept classification with an unsupervised feature learning architecture called convolutional autoencoder. We first extract a representative set of unlabeled patches from the image dataset and discover useful features of these patches with sparse autoencoders. Then we use a convolutional neural network (CNN) to obtain feature activations on full images for sentiment concept classification. We also fine-tune the network with a progressive strategy in order to filter out noisy samples in the weakly labeled training data. Meanwhile, we use low-level visual features to classify visual sentiment concepts in a traditional manner. At last the classification results with unsupervised feature learning and that with traditional features are taken into account together with a fusion algorithm to make a final prediction. Extensive experiments on benchmark datasets reveal that the proposed approach can achieve better performance in visual sentiment analysis compared to its predecessors.

In this paper raw milk was taken as the research object, using mid-infrared spectrum analysis method rapidly tests protein and fat content in raw milk through establishing quantitative analysis model. First of all, researchers collect 84 kinds of raw milk which is different areas and varieties in Heilongjiang province, and classify 84 samples into calibration sets and validation sets by standard chemical testing and spectral scanning on protein and fat, and calibration sets contain 64 samples, and validation sets contain 20 samples. Then, denoising by second derivative method which window size is 17 points, and selecting method by comparing SPA and GA characteristic wavelength respectively, and establishing PLS model and model demonstration. Eventually, researchers draw the conclusion that SPA wavelength selection method which value of m_max is 10 and GA wavelength selection method which value of Evaluat is 10d can effectively improve validation set model precision, but precision of the former is higher and characteristic wavelength is least, and its characteristic wavelength point reduces from 220 to 4, R2 of protein model validation set is 0.8010929, RMSEP is 0.0207505, R2 of fat model validation set is 0.91007989, RMSEP is 0.045329, relative standard deviation RSD<3%. These prove that the method for rapid testing of raw milk components is feasible.

E-Learning industry, since 2008, while record high suit rate of 9.5 percent annually, was rapidly emerging in high value-added service industry of the next generation [1-2]. As information technology develops, several types of e-learning have changed. In recent years, smart learning using mobile devices has become a trend [3-4]. However, problems occur when the contents, solutions, or services implemented on existing PC-based systems are applied to a mobile environment [5]. Existing e-learning mainly differs as was desktop PC-based operations, the internet connection as well, such as location-based services and augmented reality, can be applied a variety of techniques, it takes advantage of smart devices, and then, the existing e-learning became to provide differentiated services [6-7]. Most domestic technologies are developed using Flash and ActiveX, depending on the vendor. Cloud storage system that cloud computing providers provides large amounts of data storage and processing of cloud computing is a key component [10]. Most of the e-learning systems that use these same technologies are problematic to use in a smart-learning environment [8]. To solve these problems, we implemented a user-oriented contents authoring tool which is appropriate for smart-learning [9]. By providing this mobile device-based authoring tool, users are able to create real-time content. Furthermore, we aim to use HTML5 technology to create a cross-platform tool and to improve the user-oriented environment and e-learning services available for smart phones. Our tool provides additional convenience to many users by building a mobile device, web, and user-log-server. Using this approach, the real “smart” form of the contents used in smart phones expected.

Gesture recognition is an important and challenging task in the field of computer vision. Starting from the 3D shape of coding gestures, it puts forward a new kind of gesture recognition framework based on depth image. It extracts the space characteristics of a variety of 3D point cloud based on Kinect, including local principal components analysis on point cloud to get the histogram of main component, gradient direction histogram based on local depth difference and depth distribution histogram of local point cloud. Principal component histogram and gradient direction histogram effectively coding the local shape of gestures, depth distribution histogram compensates the loss of the shaping descriptor information. Through preliminary training of random forest classifier to filter the characteristics, and characteristics with less influence on classification results are removed, thus the computational costs are reduced. The filtered characteristics are used for training of random forest classifier again to classify gestures. Experiment is carried on two large-scale gesture data sets, for more difficult ASL dataset, the proposed method has improved the recognition rate of 3.6% then the best previous algorithm.

From information revolution to ubiquitous revolution, IT(information technology) has prospered influencingthelife of human and general industries. The transition from production management system in the early days to SCM today in logistics is mostly attributed to IT. In terms of WMS, from the initial production management system to the current system,massive amounts of IT have been applied to its use. Hence, this thesis presents a new type of logistics tracking and inventory management system that is able to track back the location of each commodity applying IoT(Internet of Things), known to be a current trend of IT, to utilize location-based information. The presented system also has capability to supervise the condition of commodity and real-time cargo shifting, applying environmental information gathered in inventory.

The construction of the Japanese translation platform will be of great importance in translation industry and the related industries. It is the important foundation to promote the development of Japanese translation. With PHP technology, this paper will build a Japanese translation information system, which use database technology to design a background system architecture, and use DW platform for front design. It includes network information technologies such as E-R Model, MYSQL, PHP and web publish. Design and implementation of Japanese translation system is the only way to realize informationization of the contemporary Japanese translation.

In order to solve the problem of pedestrian detection performance, the described operator was improved. In this paper, semantic local binary pattern (SLBP) and histogram of oriented gradient (HOG) are combined as new feature operator. This feature method would enrich the information and enhance the detection performance. And then histogram intersection kernel support vector machine (HIKSVM) classifier is trained by the augment feature. Because the time cost is too large by the conventional SVM. HIKSVM could make up this drawback, and significantly reduce the training time. The experiments on the INRIA pedestrian dataset show that the method obtained significant improvement in accuracy comparing to HOG descriptors.

Currently, IoT (Internet of Things) technology actively and intelligently connects several physical objects in our daily lives to each other through the internet using data communications and mutual recognition for interested individuals. This connectivity is employed for various events such as accidents, disasters, and environment, etc. There is a necessity to prepare alternatives to these uses for not only health screening, nursing, and housekeeping service for assisting the recovery of social relationships and ability in daily living, but also for the creation of content for providing necessary information to individuals. This paper reports on a study of smart care service model that focuses on prevention and diagnosis, and is equipped with portability and miniaturization. This smart care service provides a caring service for the elderly and people in need of care by monitoring their health status. It combines various contents including the status recognition module, experiencing module, and sensory module. This is accomplished by using commercial smartphone applications under the IoT environment, transitioning from a medical facility centered service to a user-centered smart care service.

Anterior cruciate ligament (ACL) 3D reconstruction is a challenging problem for both orthopedic and sports surgeons. In this paper, to investigate the method of quickly establishing 3D digital model of ACL using 2D magnetic resonance images (MRI) and 2D computed tomography (CT) images, we propose an new scene-based segmentation 3D reconstruction method for anterior cruciate ligament. First, CCD camera is anglicized for 3D reconstruction method. Second, scene segmentation method is proposed to get image patch set. Third, the distance is calculated between the image patch and viewpoint of CCD camera. Finally, the proposed method is done for scene reconstruction. The performance of the proposed model is demonstrated on various 2D MRI and CT images. A relatively reliable ACL 3D reconstruction results indicate the validity of our method. The proposed method can provide a complete set of computer aided ACL operation system and realizing the individualized anatomical reconstruction of ACL.

Information hiding techniques have recently turned out to be critical in many applications. Text message, a digital sound recording, movie, as well as images tend to be progressively equipped using distinct nevertheless imperceptible grades, which might include a hidden copyright notice as well as assistance to prevent unauthorized replicating immediately. Many analysts will work in data disappearing techniques employing unique suggestions and regions to cover their secret files. In this paper we present a theoretical performance analysis for some basic method of text based -Steganography techniques, audio files, portable executable files, and digital images, then we compare between them according to their performance using some evaluation parameters to accomplish the goal of reduces the chances of error and enhances security measures.

We subdivide social network user’s state to four kinds, Unknown state, Known state, Informed state,refractorystate.Different users may have different judgment for th same information, they transmit the information to their friends in social network lie on the information value and compare with the information threshold, we think unknown users in social network have different thresholds of an information value and sub divide these users to i class, and assume accumulated information valueof users follow uniform distribution. Apply mean field theory to build the diffusion model,from the number of refractory nodes, we can know the diffusion effect of an information in asocial network.

The growth of technology leads the industry to move beyond and crosses the boundaries of its own disciplines. The changes from pure mechanical system, to electronics systems and the integration with control software brings new challenges to the engineers working in the industry and to the source shaped the engineers. As a result, institutes of higher education need to make the necessary changes to meet this continuing market demands. This work address the issue and describes a new systematic and an effective approach for teaching hardware based courses for large non-homogenous (Computer Science and Electronics students) class setting using existing e-learning system in the university to promote powerful, long-lasting learning outcomes. It is a blend of several approaches with an insightful goal to provoke deeper understanding in various topics in microprocessors and microcontrollers details, intended to teach the computer science students to learn low-level hardware interfacing, interrupt handling, and other microprocessors issues, as well as embedded systems through learning microcontrollers. Our methodology revolute around three steps: using visual simulators, incrementally weighted exercises, from easiest to hardest, and finally working on real hardware controllers. The proposed approaches developed for the course “Embedded Controller Technology”, but any other hardware based course can apply them. The approach comprises a 3-hour a week lecture and 2-hour a week laboratory, both taught in the 3rd semester. Imposing the approach leads to the overall improvement of the course quality: student satisfaction and interest, increased number of completed hardware projects and significant improvement in grade distribution and it has been observed that students feel better prepared to face the challenges to be found in their future professional activities.

It is expected that the flexible display will provide various physical forms of the interface through its bendable, rollable or foldable characteristics without any damage and these forms are considered as the core factors to deliver user experiences in the interface. In this study, we determined the ways of utilization of the form factors in the design phase of the user experience by analyzing the effectiveness of the flexible display’s form factors to each and every user experience type through a survey. The analyzed user experiences are Functionality, Understandability, Pleasure, Convenience, Familiarity, Stimulation, Adaptability, Collectivity, Reality, and Aesthetic; the results showed that each user experience type has a different level of effectiveness of the form factors. This indicated that particular user experiences and certain form factors are related and implies that the designer can use certain form factors to express particular user experiences.

In Heterogeneous Network (HetNet), the small base station such as femtocells are deployed in indoor and multiple business complexes in order to extend the coverage and capacity. The deployment of co-channel (i.e. shared channel) for femtocells along with macrocell induces the severe interference issues. This is because of effects on SINR and thereby capacity become deteriorated. Therefore, this paper investigates the interference mitigation techniques and come out with a proposal to improve the Signal to Interference Noise Ratio (SINR) performance as well as total capacity in Heterogeneous Network (HetNet).The simulation results show that the achieved capacity is maximized than the existing technique.

Quantum-dot-cellular-automata is a potential technology for low power and high density memory designs. In this paper a comprehensive review of parallel and serial QCA memory-cell designs are presented. It is shown that a loop-based serial memory-cell design is better in terms of latency, clocking and timing, hardware requirement.

Since cases being analyzed and detected by the police using surveillance videos, insufficient resolution and degradation always lead to the suspect’s face being unrecognized. For such cases, from the perspective of learning-based face super-resolution method, this paper proposed a novel face restored solution based on face super-resolution and image mosaic. Firstly, by applying global similarity selection over the entire database, the scope of the used samples can be narrowed and boost the speed. Then the local representation between neighbors can make the method more robust against noise under severe conditions. Finally the reconstructed face could be inserted into original background by the improved Poisson Editing algorithm. This scheme achieve the effect of face restoring on a single frame in surveillance videos. Experiments under common database and real surveillance video scenarios demonstrate our method has better performance, especially for noise input images.

The resource scheduling imbalance is a multi-objective optimization problem in cloud computing environment, this paper introduced the particle swarm optimization algorithm in cloud computing, a simulated annealing ideas is proposed in view of the prematurity of the algorithm, on the premise of performance determination, the position of the particle is determined by the probability choice, which helps the particle to escape. In order to enhance the global searching ability of the particle, the algorithm is combined with the chaotic mechanism to improve the accuracy of the algorithm. The inertia weight is adjusted dynamically according to the current state of the particle, accordingly, at the same time to obtain the optimal solution to ensure the convergence. Analysis of the experimental results show that the improved algorithm has a significant improvement in the ability of optimization and convergence speed, compared with other algorithms, the benchmark functions comparison is better, the different resource task proportion spent the shortest time and load balancing is the highest.

This paper presents the development of an automatic piano which plays by itself from MIDI(Musical Instrument Digital Interface) file. We can find the MIDI format file in music data files or play data files. Piano tone is extracted from the MIDI fileand the sync time is judged and decided from the extracted piano tone so that the sync time can be sent to master CPU. These data are sent to slave CPU and then to the sound board and solenoid driving circuits. We research and develop sound trace software and sound trace board. This is one of the key technologies for a digital piano keyboard. It transmits the extracted data to the key motion control device which makes the piano playing automatically. Due to the large sound data, NAND flash memory is used to handle the data. Because the read/write speed is very important, main memory is required to be designed as a very fast structure. We designed it to fit the length of the PCB pattern address line. Because we expect large electrical current, SMPS(Switching Mode Power Supply) should be designed in low volume and weight with high power efficiency. We add a regulator to the circuit to supply the constant voltage for the circuit to prevent possible damages. Regulators are 5V and 24V.5V regulator is for MCU and 24V regulator is for solenoid. We designed the optimum key-scan circuit for controlling the 88 keyboards and designed the serial control for the reduced number of wires. The self-playing piano has high growth potential in superior educational effectiveness and a variety of usability. This technology is also likely to be applied to a medical device as music therapy.

A real-time control device for railway vehicle simulation is designed in this study according to the experimental requirements of a railway vehicle electric traction and electric braking system. The device uses the high-speed processing characteristic of DSP and runs on the basis of both DSP and the corresponding experimental platform. The simulation experiment for a different power grade traction system is achieved through control of the device. Full static and dynamic simulation of the operating condition of the train electric traction and braking system is attained in the case of no commissioning.

The purpose of this study is to explore the possibility of reflective writing as a creative teaching-learning method to promote introspective thinking of pre-service teachers. Reflective writing is a new method to understand one’s points of view on the world. Reflective writing refers to reflecting process on writers’ previous writing experiences, which reveals cognitive and emotional process. Reflective writing provides researchers with the data which is impossible to be recognized from result text, and it also offers the opportunity to develop systematic thinking ability. In these regards, reflective writing has the possibility of the creative and ingenious research method. The results of this study show that reflective writing provides pre-service teachers with the opportunity to scrutinize their attitudes and belief on education. It can also provide meaningful data for educators to understand their students’ perception on education and help to organize the effective teaching project to customize their students’ needs and interests.