Search

Traditional diagnosis technology on earlier detection of some deadly liver diseases has many disadvantages. These shortcomings are due mainly to inadequate accuracy, which usually leads to failing to give liver patients timely treatment. In order to solve this problem, this paper used Classification and Regression Tree (CART) as a weak classifier of the AdaBoost framework to propose a Classification and Regression Tree-Adaptive Boosting (CART-AdaBoost) model. Moreover, the authors trained and verified the model basing on the Indian Liver Patient Dataset (ILPD) of UCI. The results showed that the model's accuracy was 83.06%, and its precision was 84.31%. Besides, F1-score could reach 80.75%, and the recall metric was 77.48%. All the former three indicators were higher than those produced by single models or combination models (weak classifier + AdaBoost) listed in this paper. Besides, it is worth noting that the prediction accuracy and precision of the CART-AdaBoost model were improved by a maximum value of 18.60% and 23.84%, respectively. Therefore, the suggested model is of great benefit in enhancing the early detection effect of liver diseases.

With the appearance of the new engineering concept in 2017, the mode of talents development in colleges and universities has also changed. And the new engineering talents need to be more practical and innovative abilities. However, the professional certification of engineering education is an important guidance for the teaching of engineering majors in China, and it is the core idea of output-oriented, student-centered and continuous improvement to construct the quality control system of engineering education in colleges and universities in China. Combining with the core idea of engineering certification and the new requirements under the background of new engineering, in this paper, we put forward to a set of comprehensive software engineering course design for engineering certification in the new engineering environment, which is guided by engineering education, aims at improving students' engineering practical ability and innovation, provides a method of solution for the reform of software engineering course design under the new engineering background.

With the improvement of people’s living standards, people’s spiritual needs continue to increase, which makes personalized travel recommendation more and more popular. However, the complicated and overloaded information in the internet have caused troubles for people to choose travel scenic spots. Although collaborative filtering is widely used for recommendation algorithms, neither user-based nor item-based collaborative filtering take the users’ personalized characteristics into account. In order to recommend better travel scenic spots to users, we propose a personalized collaborative fusion algorithm combining user-based original collaborative filtering matrix with users’ personalized preference matrix to make the recommendation more accurate and attractive. We build our experiments on the data of Qunaer, the results show that our proposed algorithms can not only recommend similar users’ travel scenic spots, but also consider users’ own personalized characteristics.

This paper proposes an automatic flow to repair IR-drop violations by Engineering Change Order (ECO). Our ECO technique provides cell move and downsize solutions. We use machine learning to predict IR-drop so that we can prevent over-fixing. We use a commercial tool to predict timing so that this is a timing-aware ECO. With the above two predictions, we propose a novel multi-round bipartite matching to optimize the ECO resource utilization. Experimental results show that for a 5M gate real design, our proposed method repairs 2,504 (22%) violation cells out of the original 11,555 violation cells and repairs 36,272mV (37%) total excessive IR out of the original 98,674mV total excessive IR. We are able to perform ECO on seven thousand cells within 13 hours, so our ECO flow is practical and can be applied to large industrial designs.

The prevalence of predatory journals has become more severe recently as this is harmful to science and technology development. For scholars publish papers more effectively and avoid publishers for profits, this research used a machine learning method to identify the predatory journals. The features like text content and keywords of the collected journals' websites were extracted from mainstream predatory journal websites and normal journal websites. This research proposed a predatory journal classification system based on a new model. The results show that our model's recall rate exceeds 90%, ensuring that the journals submitted by the researchers are not predatory.

With the emergence of virtual reality (VR) like holographic telepresence, it is envisaged that the current networks may be overwhelmed due to the higher bandwidth demand to support high-resolution videos. On the other hand, Camera Blending Field (CBF) has been proposed to restore the occluded regions of cameras to enhance the user’s Quality of Experience (QoE) in VR. In this paper, we explore the source selection to maximize the user’s QoE under the network capacity and 3D reconstruction constraints. We first formulate a new optimization problem, named Source Selection for Real-time Telepresence with Occlusion (SSRTO), with the objective of QoE maximization. Then, we prove the NP-hardness and propose a new algorithm, Maximum Quality of Complete Model (MQCM), to maximize the user’s QoE by examining the proximity of cameras on the built Angle Directed Graph (ADG) and Neighbor Directed Graph (NDG) for reconstructing the complete 3D model. Simulation results show that MQCM can effectively improve the user’s QoE by more than 100% compared with the baseline schemes.

5G supports more new services, including enhanced Mobile Broadband (eMBB), Ultra-reliable and Low Latency Communications (URLLC) and massive Machine Type Communications (mMTC). The Quality of Service (QoS) requirements of these 5G service types are different. In this paper, we capture the packets from the Narrow Band-Internet of Things (NB-IoT) transmission, Unmanned Aerial Vehicle (UAV) control, 4K video and Facebook access for emulating mMTC, URLLC, eMBB and Internet traffic in 5G. With the captured packets, we investigate using the machine learning technology to classify the packets based on the payload information. Specifically, the Convolutional Neural Network (CNN) model is performed to classify the application packets into suitable groups. In addition, this paper studies the effects of various parameters such as the kernel number, kernel size, pooling window size, the dropout rate and the payload length to find the optimal values for high accuracy and low latency.

The deconvolution technique can improve the spatial resolution of Millimeter and Sub-millimeter Sounding/Imager (MMSI) of FY-4 satellite. In this paper, the technique is applied to the simulated brightness temperature image of a typhoon scene, which indicates that the deconvolution technique is feasible to enhance the spatial resolution of MMSI. In the analysis of the antenna temperature of the earth obtained by MMSI, We consider the effect of beam scanning and acquire an accurate estimate of the brightness temperature distribution. The results show that the outline of the typhoon in the enhanced image is closer to the initial image than the non-enhanced image. The correlation coefficient is improved and the spatial resolution is enhanced from 96km to 57km, which indicates the effectiveness.

Initial fleet assignment usually begins one month before a flight takes off, at which time the demand is real uncertain. In order to achieve a balance between seats and demand, our paper puts forward demand driven dispatch method, the main idea of which is to do initial assignment during flight scheduling and flight swapping with demand forecasting can be more accurate. This paper presents BP neural network-Particle Swarm Optimization algorithm to forecast demand based on DCP-3 accepted demand in Revenue Management System.

In this paper, we propose a novel control method using voice recognition for electric equipment. By doing so, users can just make voice to control the targeted machine and use without any hand-held device. Especially, the implemented system is based on a FPGA (Field-Programmable Gate Array) embedded system, that provides a capability to enhance the performance of signal processing by employing specific hardware-accelerated co-processors. As such, a more intelligent and performance effective control style will be realized for future smart control of electric equipment.

Test case recording and playback technology, normally implemented as a test case recorder, has been widely applied in the industry. One of the key research topics is how to determine if a web page has entered a ready state before the recorder can perform the next test command? If a web element is incorrectly selected during playback, the related test command will fail to process. This research puts forward four kinds of automatic waiting mechanism for playing test commands. The experiment result shows that the waiting time can be determined dynamically and automatically, so that testers do not have to manually add waiting commands thereby reducing the time and error of artificial discrimination. The proposed mechanisms were implemented as parts of the SideeX open source web testing software and have been further adopted by the new Selenium IDE and Katalon Recorder. Currently, over 60,000 web testers around the world run the mechanisms.

This paper presents a new method for generating object mesh models composed of hexahedra. The proposed method is based on a self-organizing deformable model (SDM) which is a deformable surface model guided by competitive learning and an energy minimization approach. Extending the SDM, the proposed method generates a hexahedral mesh model of a target object by fitting a cuboid composed of rectangular voxels to the object. Moreover, the shape of each hexahedron in the model is corrected by dividing the hexahedron into sub-hexahedra and moving the nodes of the hexahedron. From our experimental results, the proposed method obtains the hexahedral mesh model which consists of many regular hexahedra while recovering the shape of the object.

This paper analyses the failure mechanism and striking process of heavy ions irradiated vertical double diffusion power metal-oxide-semiconductor field effect transistor(VDMOS), concludes three irradiation hardening technologies, shielding technology, recombination technology and enhancement technology, summarizes the development of single-event irradiation hardening technologies for power VDMOS in domestic and international.These technologies could provide reference for the researchers who are engaging in the single-event irradiation hardening technology of semiconductor device.

Based on the NaSch model, this paper establishes a cellular automaton traffic flow model considering driver characteristics is established in this paper. The vehicle driving characteristics under the disturbance of the driver are simulated. Numerical analysis shows that at low density, the maximum speed can be reached without the driver interference factor. With the increase of density, the critical density of the system is larger and the influence of driver behavior on traffic flow is increased. When the driver's interference factor is below the p=0.8 ratio, the impact of the system's flow is tiny and the purpose of safe driving is achieved by observing the trend of traffic. However, when the driver interference factor ratio is large, in the high density area, the system traffic will be more affected, the traffic than the above situation is smaller.

This paper introduces a kind of simulation testing system scheme for train-borne controller and applies it to the simulation testing system of the controller. Besides, it elaborates the system structure, interface type and key module of the hardware realization. The simulation testing system for train-borne controller is completely built, and plays a vital role in the train-borne controller simulation testing and factory complete equipment testing process.

The next few years promises drastic improvements to global navigation satellite systems. USA is modernizing GPS, Russia is GLONASS, Europe is moving ahead with its own Galileo System, and China is expanding its BeiDou system from a regional navigation system to a full constellation global navigation satellite system known as BeiDou-2/Compass. Chinese BeiDou satellite navigation system constellation currently consists of twenty-six BeiDou satellites and can provide services of navigation and positioning in the Asia-Pacific Region. In this paper, we calculate the high frequency data of GPS and BeiDou by using the broadcast ephemeris, and the results are applied to the real-time positioning of the float platform in the experiment of Air-Gun in reservoir. We use the data to analyze the quality by multipath effect, signal noise ratio, positioning accuracy and so on. The results show that the accuracy of the BeiDou is slightly lower than that of GPS. The accuracy of GPS in horizontal direction is about 5 mm and that of vertical direction is about 12 mm, and the accuracy of BeiDou in horizontal direction is about 5.5 mm and that of vertical direction is about 16 mm.

The next few years promises drastic improvements to global navigation satellite systems. The USA is modernizing GPS, Russia is GLONASS, Europe is moving ahead with its own Galileo System, and China is expanding its BeiDou-1 system from a regional navigation system to a full constellation global navigation satellite system known as BeiDou-2/Compass. Chinese BeiDou satellite navigation system constellation currently consists of twenty-three BeiDou satellites and can provide services of navigation and positioning in the Asia-Pacific Region. This paper focuses on calculating the results of differential positioning with different ephemeris, combining dynamic GPS and BeiDou data of air-gun in reservoir. In this experiment, the high-frequency GPS and BeiDou data is real-time calculated by broadcast ephemeris, and the result is used for real-time positioning of the air-gun floating platform. Then we calculate the GPS data of the experiment by precise ephemeris, and the accuracy of broadcast ephemeris of GPS is verified by comparison. Finally, calculate the high frequency data of GPS and BeiDou with precise ephemeris in order to verify the accuracy of BeiDou positioning. The experimental results show that the accuracy of GPS and BeiDou navigation system are basically the same and the data of GPS and BeiDou navigation system calculated by broadcast ephemeris can record the displacement of the floating platform accurately.

In this paper, the maximum voltage gain and output power design method based on the optimal distance point is also put forward. Meanwhile, the research on the efficiency evaluation in Class-E converter based on GaN devices has shown that GaN transistor can obviously brings higher transmission efficiency, smaller size and lower cost in Class-E converter due to the lower R ds(on) and the gate charge (Q g ).

People's behavior is constrained by external social norms, meanwhile they will internalize the norms they approved, thus making their own internalized morality. If someone violates this internalized norm, he will not only be punished by others, but also generate guilt or shame by himself, so he will adjust his behavior in order to avoid such feelings. Though loan experiments, this paper investigates the relationship between people's repayment behavior and their internalized morality of keeping their appointment. Also we explore the influence of other factors on people's repayment behavior, including rule preference, risk preference and social value orientation. The result shows that, in consideration of other factors, the stronger people's internalized morality, the better their repayment behavior.

This paper presents one syntactic foam with excellent mechanical properties and prominent hydrostatic pressure performance for 11000 meters deep-sea. The properties of the syntactic foam are studied on the basis of relevant standards. The compressive strength, compressive modulus and shear strength of syntactic foams are about 100MPa, 1300MPa and 40MPa separately in atmosphere environment. The water absorption of the material is less than 1percent in the 110MPa hydrostatic pressure for 8h, and the appearance maintains intact in the 140MPa hydrostatic pressure when the density of the syntactic foam is between 0.670 to 0.688g/cm3.

This paper proposes a miniaturized bandpass filter using dual-mode double-folded laminated waveguide cavity resonators on a multilayer low temperature co-fired ceramic (LTCC) substrate. The double-folded cavity is constructed by inserting a metal plate with an L-shape slot at the vertical center of the cavity. By changing the extra metal plate size along the folded side, the frequency ratio of resonant modes TE201 and TE301 can be flexibly adjusted as a dual mode cavity. Two dual-mode cavities are then stacked vertically and fed with two microstrip lines to form a 4th order Chebyshev Alter, where the coupling and feeding slots are designed according to the field distribution to achieve the desired coupling coefficients and external quality factors for different resonant modes. Designed at center frequency 73.5 GHz with 5.8% fractional bandwidth, the proposed filter has compact size and good frequency responses.

A compact low temperature co-fired ceramic (LTCC) filter using vertically interdigitated resonators is realized in this paper. Multilayer vertically interdigitated capacitors (VICs) and a metal strip inductor are connected in parallel to implement the proposed vertically interdigitated resonator (VIR). The proposed bandpass filter is designed at center frequency 2.45 GHz with 8% fractional bandwith. This filter has not only a compact physical size 1.75 × 0.983 × 0.963 mm3 but also a compact electrical size 0.039 × 0.022 × 0.021 λ g 3. The measured insertion loss of the realized filter is about 2.1 dB and in-band return loss is greater than 14 dB.

This paper uses MaSE to build the application model of city traffic monitoring system based on MAS, establishes the model of static and dynamic Agent model which were combined with the characteristics of the monitoring system by using UML. This model maps the entity state change into the model for analysis and simulation using autoregressive Markov probability model, has improved the efficiency of status event analysis and recognition.

Meteorological environment is an important influencing factor in performance of the optical equipment. Traditional single meteorological environment modeling has limitations. According to the laser rangefinder in complex meteorological environment, systematically analyzes four typical meteorological environments. Construct multi-agent based on meteorological environment model by extract important factors. Experiment results approved the effectiveness and reliability of the model.

With the rapid development of multi-core and multi-threading technologies, the performance gap between CPU and storage system is widening year by year, causing the storage system to be the bottleneck of the whole system performance. To alleviate this situation, flash memory has been used as the caching device of HDDs. On the other hand, cloud computing is becoming more and more popular and mature in industry field. As the key building block of it, virtualization technology allows several virtual machines (VMs) running on one single physical machine simultaneously, most of which usually run the same or similar operating systems and applications. In this scenario, flash cache will be occupied by many duplicate data blocks. However, existing flash cache architectures and replacement policies don't take this observation into consideration, which greatly limits the efficient use of the flash cache. In this paper, we propose a new duplication-aware flash cache architecture (DASH). In this architecture, flash cache is organized to cache only one copy of the duplicate data blocks, which can notably expand the effective cache capacity, making more I/O requests hit in the cache. Moreover, this architecture can reduce the amount of data written to flash cache, and thus the life span of flash device can be significantly prolonged. Experiments based on realistic applications show that, in some situations, our cache architecture can improve the cache hit ratio by 5 times, reduce the average I/O latency by 63% and eliminate flash cache writes by 81%.

Smart mobile handheld devices (MHDs) are being adopted at a fast speed. Compared to wireless non-handheld devices (NHDs), MHDs tend to be more mobile and can be used more opportunistically. In this paper, we study two important network usage characteristics of MHDs, namely session lengths and IP address usage, in a university campus WiFi network. Specifically, we analyze two five-week long DHCP traces collected from the network, characterize session lengths of MHDs, and develop two hyper-exponential models to capture the distribution of session lengths.We further characterize the IP address usage of MHDs, and develop two analytical models to predict the number of concurrent IP addresses that are being used by MHDs at one point of time. Goodness of fit tests indicate that our analytical models of session lengths provide good fit, and evaluation results demonstrate that the predictions from our models for IP address usage are accurate. Our results provide important insights on managing MHDs as they are being adopted rapidly in WiFi networks.

User-generated images are now prevalent across social media platforms, such as Facebook, Twitter, and various blogospheres. These images can be categorized and ranked based on their relevant topics. In this paper, we present and compare candidate schemes for mining salient images related to a specific topic or object among a large number of images from a blogosphere. Identifying salient images consists of several steps: calculating the similarity between images, k-means clustering images, and ranking images. In each step, we propose a set of alternatives and as a result, present an optimal combination scheme by conducting an empirical comparison of the performance of each scheme. Furthermore, to address scalability, we also present a distributed version of the schemes and experimental results based on MapReduce on top of a Hadoop environment.

In the past sensors and surveillance systems were installed in the home environment to capture user activities. However, blind spots exist in areas out of reach of sensors. Obstacles and furniture are some barriers that cause fall down of elderly in the home environment. A motion sensor is mounted on Arduino platform to design a visual navigation system in service robot. Colors and depth of images are used to predict the walking route of elderly and to navigate the service robot. The service robot is functioned to use strategy inferred from fuzzy output to make the elderly detour from any possible collision with barriers. A graceful deception model and fuzzy inference system are proposed in this paper. In case an incident is predicted to happen in the current walking route, the proposed system will calculate the dangerous degree to avoid colliding with obstacles. Experiment results are given to verify the effectiveness of the presented work.

For the ability to explore the memory's fullest potential, memory de-duplication has been widely experimented with in current main stream virtualization platforms. A lot of work has been done to improve the efficiency of memory de-duplication, while too little attention was paid to the introduced security issues which have been proved by prior work. To deal with this security risk and efficiently manage the memory we start our work in this paper. We first conduct extensive experiments on different OS platforms to study the realistic situation of page sharing. By analyzing the results we find: 1) Page sharing is contributed mostly by self-sharing (nearly 90%), and the self-sharing rate varies significantly between Linux and Windows OS platforms. Compared with self-sharing the inter-VM sharing rate is extremely low, under 1% in most cases. 2) Page size has a larger influence on Linux platform than Windows platform, so sub-page de-duplication proposed in prior work may achieve better performance on Linux platform. On the basis of above findings we propose a group-based secure page sharing model (or GSKSM), in which we consider both VM processes and normal processes. We have successfully implemented it in Linux kernel 3.6.6, and the experiment results show it works well with negligible overhead. Finally based on GSKSM we further present an efficient memory management approach (or SEMMA), which combines GSKSM and balloon technique to efficiently manage the memory, and the preliminary experiment result is satisfactory.

The Independent Component Analysis (ICA) method has applied in the field of blind source separation. On the basis of analyzing ICA, the study ameliorates the FastICA. The conventional FastICA has only a second order convergence rate and combination of static model and batch optimization algorithm. An improved ICA algorithm is therefore proposed to reduce the iteration steps and dynamic the algorithm. The experimental results show that the improved algorithm achieved satisfactory results.

This paper, by exploiting characteristic function (CHF) and Beaulieu series, evaluates bit error rate (BER) of Orthogonal Frequency Division Multiplexing (OFDM) with Binary Phase Shift Keying (BPSK) modulation impaired by residual frequency and timing offsets over frequency selective Rayleigh fading channels. While it overcomes the limitation that the previous studies using the similar CHF approach can not calculate exact BER when OFDM has a large number of sub carriers. Simulation results illustrate the accuracy of the proposed analysis.

In this paper, we propose a simple loss less algorithm which can compress all types of images with the same high Compression Rate. The algorithm consists of two phases. First, it removes the correlation between pixels with Snake Scan to get residual of data. And then encode the residual of data with an Adaptive Arithmetic Coding. This Adaptive Arithmetic Coding only uses adjacent data to build the probability model. 24 color images provided by Kodak Company were used to test compression rate of this proposed algorithm. The results show the efficiency of this proposed algorithm is better than original Adaptive Arithmetic Coding method.

FeIII porphyrin complexes as bioinspired catalysts exhibit remarkable catalytic activity for sulfides oxidation near the natural conditions, i.e. at room temperature, in the protonic solvent and with psychological oxidant H2O2 aqueous in the absence of other chemical assistance. Various sulfur substrates existing in petroleum were examined including refractory dibenzothiophene. Reaction conditions affecting the conversion of sulfides and the stability of catalyst were investigated. The results showed that polar and protonic solvent can facilitate this oxidation and the catalyst's life-span was closely related with temperature variations. FeIII porphyrin, substituted on the phenyl groups with a chlorine atom, displayed higher efficiency than no substituted. The conversions calculated from the GC data are 100, 99.81, 99.78 and 77.05 wt % for di-n-butyl sulfide, thioanisole, diphenyl sulfide and dibenzothiophene respectively after a typical procedure.

Tags are very popular in online social communities (like You tube, Flickr) and provide valuable and crucial information for these communities. But at the same time, there exist a lot of noisy tags, which leads many researches to tag suggestion, tag recommendation for the items, such as to the websites, photos, books, movies, and so on. Most of them used the textural features of tags to extract related tags to items, like tag frequency. In our paper, we address the problem of tag recommendation for users in Flickr. This issue is as important as tag recommendation for items, because representative tags of users are strongly related to usersi¯ favorite topics. We propose several novel features of tags which we call them social features as well as textual features. Experimental results show that our proposed scheme achieves viable performance on tag recommendation for users.

The railway signaling system is a safety related system composed of several sub-systems which have to exchange information with each other. As the communication system may be subjected to intentional or unintentional external attacks, the application of specific safety techniques is necessary. In this paper, a safety protocol is designed. Compared with the general TCP/IP protocol, a safety layer, on which several safety measures are applied to defense against the possible threats or attacks, is inserted between the top application layer and the lower transmission layer. The result illustrates that the designed protocol conforms to the international standard EN50129, and can switch the system to a fail-safe state when an unexpected failure or error occurs.

With the popularity of learning on the internet, the construction of perfect web-based learning environment has become one of the hot points on researching remote education. Cloud computing is another brand-new concept of network following the network computing. It will become a primary way for people to obtain service and information in the future. In this paper, web-based learning environment and the concept of cloud computing are discussed. The lastest development of cloud computing is summarized. Cloud computing and its application to web-based learning environment are made some researches preliminarily and its basic framework has been given.

Smart grid is envisioned to incorporate local distributed power generation for better efficiency and flexibility. Distributed generation, when not used carefully, however, may compromise the stability of the grid. Recently, researchers have proposed innovative architectures (e.g., microgrid, LoCal grid) that virtualize a local generator as a constant load, source, or zero load to the grid, thus offering great promise to connect distributed generation into the grid without sacrificing its reliability. In fact, intuitively, using these architectures, distributed generation may enhance the stability of the power grid. In this paper, we develop a simulation model to quantify how much distributed generation can mitigate cascading failures. Applying this model to IEEE power grid test cases, we find that local power generation, even when only using a small number of local generators, can reduce the likelihood of cascading failures dramatically.

Various clustering methods based on the behavior of real ants have been proposed. In this paper, we develop a new algorithm in which the behavior of the artificial ants is governed by fuzzy set. Firstly, we define the average distance between objects, and the average distance is the domain of the object similarity. Secondly, the similarity between objects is mapped a domain of fuzzy sets by membership function. Finally, by the given confidence level, fuzzy sets will be separated into universal set. The universal set will decide that ants pick up or put down the object. In the experiment, spatial data source comes from the actual survey data in mine. LF algorithm and the fuzzy ant based spatial clustering algorithm separately to cluster these data. Through analysis and comparison the experimental results to prove that the fuzzy ant based spatial clustering algorithm enhances the clustering effect.

On the basis of home and abroad relative works, the Laplace equation, and the basic definition of the electron transit time, we derived mathematically the formulae of potential distribution function and the formulae of the electron transit time function inside an ideal spherical vacuum microelectronics diode. Using our formulae, a rough value of the electron transit time for an ideal spherical vacuum microelectronics diode has been calculated. By introducing a concept of an equivalent diode, a rough value of the electron transit time inside a spherical vacuum microelectronics triode has also been calculated. From those values, the application potential of those vacuum microelectronics diode or triode can be estimated at MW and THz regime.