Encouraging farmers to adopt environmentally friendly technology through the rational use of social learning and agricultural extension is an effective way overcome bottleneck caused by slow diffusion technology. Based on expanding existing objects research farmers' adoption behavior, this paper examines influence behavior from a dynamic perspective. In doing so, it enriches theoretical empirical behavior. Specifically, takes fertigation as example, constructs analysis framework that...

This study used an odor sensing system with a 16-channel electrochemical sensor array to measure beef odors, aiming distinguish odors under different storage days and processing temperatures for quality monitoring. Six ranged from purchase (D0) eight (D8), three temperature conditions: no heat (RT), boiling (100 °C), frying (180 °C). Gas chromatography-mass spectrometry (GC-MS) analysis showed that odorants in the varied conditions. Compounds like acetoin 1-hexanol changed significantly...

Local defects of rotating machinery give rise to periodic impulses in vibration. To acquire this fault information, many diagnostic methods have been reported the past decades. Among them, envelope spectrum analysis is usually used as final tool; however, its success highly de pends on correct informative frequency band selection. The key problem how find centre and related bandwidth associated fault. In paper, a novel method proposed for selection optimal parameters. This improves...

We introduce a general iterative method for finding the solution of variational inequality problem over fixed point set nonexpansive semigroup in Hilbert space. prove that sequence converges strongly to common element above two sets under some parameters controlling conditions. Our results improve and generalize many known corresponding results.

Facial nerve paralysis adversely affects both mental and physical health of patients. Several degree evaluation methods for facial have been put forward based on the static asymmetry computer vision technologies. However, traditional still suffer from two drawbacks: (1) movement information is ignored which could be important analysis; (2) shallow machine learning models used by them may not well extract effective features different grades. In this paper, we present Triple-stream Long Short...

To assist subject matter experts in investigating electronic failures of drilling tools, an innovative risk assessment approach for oil well operations is developed that relies on synthetic time-series data to emulate environmental factors encountered downhole, explicitly focusing temperature, shock, and vibration. The involves utilizing load cycle counting extract meaningful features from each channel measured by the tool. results experiments with related dwell periods (dwell time damage)...

Background noise reduction has been studied for many years. However, unwanted human speech suppression is not well discussed due to sparsity of the signal. Traditional blind source separation (BSS) methods such as independent component analysis (ICA) assume prior knowledge number sources and require that must equal sensors. Above limitations prevent practical use enhancement using traditional BSS mobile phone communication. In this paper, a combination method speaker recognition system (SRS)...

The purpose of this paper is to prove strong convergence theorems for finding a common element the set fixed points weak relatively nonexpansive mapping and solutions variational inequality an inverse-strongly-monotone by new hybrid method in Banach space. We shall give example which but not space . Our results improve extend corresponding announced Ying Liu[Ying Liu, Strong theorem space, Appl. Math. Mech. -Engl. Ed. 30(7)(2009), 925-932] some others.

In many real scenarios, data are often divided into a handful of artificial super categories in terms expert knowledge rather than the representations images. Concretely, superclass may contain massive and various raw categories, such as refuse sorting. Due to lack common semantic features, existing classification techniques intractable recognize without class labels, thus they suffer severe performance damage or require huge annotation costs. To narrow this gap, paper proposes learning...

Logging tools widely used in the oil and gas industry are exposed to demanding environmental conditions that can lead faster degradation unexpected failures. These events reduce productivity, delay deliverables, or even bring entire drilling operations an end. However, such accidents be avoided using a prognostics health management approach. This paper presents data-driven fault detection method for transmitter logging-while-drilling tool adopting support vector machine classifier. The...

In the area of well construction, tool reliability and field environment are two contributing factors that influence drilling job efficiency success. Either using high specification tools in low-risk environmental or applying low harsh environments is inadvisable. Thus, how to select a suitable fitting an approaching great significance for planning. However, today, selection decision not optimized because it often based on partial data availability understanding. This paper presents...

Traditional intelligent diagnosis methods and current popular deep learning based basically adopt the approach of batch learning, which may waste time computing resources since they need to discard previous learned model retrain a new on newly added data prior data. Moreover, manual feature extraction is often necessary step for diagnosis, such process relies much knowledge. To solve above mentioned problems, this paper proposes fault method class incremental without extraction. Based...

In this paper, we prove strong convergence theorem by the hybrid method for an α-nonexpansive mapping in a Banach space.Our results complement and enrich research contents of mapping.Simultaneously, our main result generalizes Takahashi, Takeuchi, Kubota's result[W.

Abstract The purpose of this paper is to propose a modified hybrid projection algorithm and prove strong convergence theorems for family quasi-"Equation missing"<!-- image only, no MathML or LaTex -->-asymptotically nonexpansive mappings. method the proof different from original one. Our results improve extend corresponding announced by Zhou et al. (2010), Kimura Takahashi (2009), some others.

To increase the efficiency and accuracy of multiclass acoustic signal recognition, an incremental learning algorithm based on probabilistic support vector data description (SVDD) machine (SVM) is proposed in this paper. A general classification structure with probability distribution constructed by applying SVDD SVM to separately train models. Avoiding repeated training, class-incremental (CIL) combination trained models overall model construction kernel density comparison. For its specific...

This paper presents a predictive maintenance-planning solution in the oil and gas industry. The focuses on mechanical components of bottomhole assemblies, which are equipment that goes underground well-construction activities. Two were successfully modelled, namely crossovers collars. They tubular structures have to be repaired ("cut") after performing drilling job remove worn material. A linear behaviour was observed for degradation crossovers. subsequent model predicted remaining jobs...

Today's oil and gas industry frequently uses logging-while-drilling (LWD) tools to operate in extreme environmental conditions. These conditions include elevated temperature, vibration, pressure, which can result accelerated tool degradation rates possible failures. Detecting such failures before conducting a new drilling job is of great significance guarantee the efficiency success job. Previously fault detection task required field engineers check relevant signal channels manually,...