Partial nitritation is required to provide nitrite for the anammox reaction in an autotrophic nitrogen removal process, which has been considered crucial achieving energy-positive mainstream sewage treatment. In this study, three lab-scale reactors were operated treat wastewaters with low ammonium concentrations at high hydraulic loading rates (nitrogen of 0.36 kg N/d/m3). Long-term experiments repeatedly demonstrated that a rate favored startup partial nitritation, as indicated by buildup...

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, rules are planned, and the RRA processes split into five steps Introduction only lists 4 so AUVs can rapidly respond various environment obstacles. The largest polar angle (LPAA) designed change detected obstacle's irregular outline a convex polygon, which simplifies...

One of the major steps for opinion mining is to extract product features. The vast majority existing approaches focus on explicit feature identification, few attempts have been made identify implicit features in reviews, however; people tend express their opinions with simple structures and brachylogies, which lead more reviews. By analyzing characteristics reviews Chinese Internet, this paper proposes a novel context-based extracting method. We according words similarity between features'...

The presence of different malicious regions on a single breast reveal some necessary information for cancer early detection. In current computer-aided diagnosis models, lesions contained in mammogram are not detected and segmented individually. Therefore, the multidetection segmentation can help radiologists an accurate diagnosis. This study aims to develop model based regional learning technique RoI-based Convolutional neural network (CNN), which is known as Masked Regional Neural Network...

The most efficient and ordinarily used early detection method of breast cancer is screening mammography deep learning widely employed in the medical imaging domain. But In circumstances, large data size for training a significant difficulty second thing very less work on six levels BI-RADS classification. this research, purpose classification, we proposed methodology with ResNet-based customized neural network (RN-BCNN) as compared to traditional ConvNet model, using augmentation pyramid...

The limited communication consensus control problem is studied for leader-following multi-UUVs (multiple unmanned underwater vehicles) in a swarm system that contains multiple secondorder UUVs with the time-varying delay. multi-UUV will be divided into many sub-groups each includes one leader and follower UUVs, leaders-group composed of all leaders sub-groups. In leaders-group, called commander, follow commander. Under mechanism, multi-independent switching topologies are proposed hybrid...

Context-aware recommender system (CARS) can provide more accurate rating predictions and relevant recommendations by taking into account the contextual in-formation. Yet state-of-the-art context-aware matrix factorization approaches only consider influence of con-textual information on item bias. Tensor based Multiverse Recommendation deals with in-formation incorporating user-item-context interaction recommendation model. However, all these cannot fully capture rating. In this paper, we...

Adverse Drug Reaction (ADR) is one of the major challenges to evaluation drug safety in medical field. The Bayesian Confidence Propagation Neural Network (BCPNN) algorithm main used by World Health Organization monitor ADRs. Currently, ADR reports are collected through spontaneous reporting system. However, with continuous increase and possible use scenarios, efficiency stand-alone detection will encounter considerable challenges. Meanwhile, BCPNN requires a certain number disk I/O, which...

Topic model has been used to extract implicit features yet little concerns have given general opinion words, e.g., "Okey" (good). In this paper we present a modified topic joint topic-opinion (JTO) for extracting of words including special and ones. Our is based on an extension standard LDA by adding level. This considers both topics context words. Experiments show that JTO provides higher accuracy in extraction.

Trust-aware recommender system (TARS) can provide more relevant recommendation and accurate rating predictions than the traditional by taking trust network into consideration. However, most of trust-aware collaborative filtering approaches do not consider influence contextual information on prediction. To opposite, context-aware matrix factorization as we know take In this paper, propose two Trust-based Context-aware Matrix Factorization (TCMF) to fully capture ratings. We integrate both...

Trust-aware recommender system (TARS) can provide more relevant recommendation and accurate rating predictions than the traditional by taking trust factors into consideration, yet currently only static is modeled in these systems. In this paper, we propose to integrate social network analysis based dynamic model with context-aware matrix factorization a new trust-based factorization(DTCMF) fully capture of trust. Evaluations on real dataset three semi-synthetic datasets demonstrate that our...

Purpose The fast and easy generation of personalized mannequin is the premise for accurate 3D measurement customers in an electronic made to measure (e_MTM) system. purpose this paper attempt propose a new virtual human modeling technique meet requirement. Design/methodology/approach customized constructed by assemblage body parts. parts including bust, waist hip segments are achieved modification standard section templates, while silhouette obtained from front side photos used confine...

A novel obstacle avoidance strategy is proposed for autonomous underwater vehicle (AUV) in unknown environment according to detected outline of avoidance. The obstacle's algorithm (OOA) adapt irregular obstacles which used detouring their by forward looking sonar (FLS). largest polar angle (LPA) produce avoidances' changing into convex polygon, simplifies the process. Finally, simulations are carried out demonstrate performance strategy, where obtained path optimal or sub-optimal AUV moving...

Socioeconomic factors are extrinsic that drive spatial variability. They play an important role in land resource systems and sometimes more than of the natural setting. The study aims to build a comprehensive framework for assessing unconsolidated cultivated (UCL) south-central southwestern portions Hubei Province, China, which have not experienced project management consolidation, identify roles especially socioeconomic factors. Moreover, attempts attributes indicators describe...

The ability to detect anomalies in application log files has attracted the attention of researchers over past decade as it become a challenging issue. Intuitively, noticeable variation performance can be result some natural causes (e.g., CPU workload variations and memory leaks) or from internal errors that may cause failure crash. In here, an account prediction detection together with their been reported. A framework for was particularly targeted onto whereby quantity historical data...