Active Multi-Field Learning for Spam Filtering

Ubiquitous spam messages cause a serious waste of time and resources. This paper addresses the practical spam filtering problem, and proposes a universal approach to fight with various spam messages. The proposed active multi-field learning approach is based on: 1) It is cost-sensitive to obtain a label for a real-world spam filter, which suggests an active learning idea; and 2) Different messages often have a similar multi-field text structure, which suggests a multi-field learning idea. The multi-field learning framework combines multiple results predicted from field classifiers by a novel compound weight, and each field classifier calculates the arithmetical average of multiple conditional probabilities predicted from feature strings according to a data structure of string-frequency index. Comparing the current variance of field classifying results with the historical variance, the active learner evaluates the classifying confidence and regards the more uncertain message as the more informative sample for which to request a label. The experimental results show that the proposed approach can achieve the state-of-the-art performance at greatly reduced label requirements both in email spam filtering and short text spam filtering. Our active multi-field learning performance, the standard (1-ROCA) % measurement, even exceeds the full feedback performance of some advanced individual classifying algorithm

High NH3 deposition in the environs of a commercial fattening pig farm in central south China

Intensive livestock production has been increasing, and has resulted in the emission of more than seven teragram per year of ammonia (NH3) in China in recent years. However, little is known about the fate of the emitted NH3, especially the dry deposition of NH3 in the environs of intensive animal farms. In this study, the spatial and temporal variations of NH3 deposition in the environs of an intensive fattening pig farm were investigated in the central south of China. NH3 concentrations were measured at sites situated 50, 100, 200, 300, and 500 m in the downwind direction from the farm each month from July 2018 to June 2019. The NH3 deposition was calculated based on a bidirectional NH3 exchange model. The monthly NH3 emissions from the pig farm were estimated based on the breeding stock. The annual average NH3 concentrations ranged from 1200 to 14 μg m−3 at the downwind sites within 500 m of the pig farm, exhibiting exponential decay as distance increased. Strong seasonality in NH3 deposition was observed, with the highest season being in the summer and lowest in the winter, and air temperature was found to be an important factor affecting this seasonal variation. The estimated monthly total dry deposition within 500 m of the pig farm ranged from 92 to 1400 kg NH3–N mo−1, which accounted for 4.1%–14% of the total monthly NH3 emissions from the pig farm. The estimated total NH3 emissions and NH3 deposition from the pig farm were 63 000 kg NH3–N yr−1 and 5400 kg NH3–N yr−1, respectively, with the annual average ratio of NH3 deposition to NH3 emission being 8.6%. This study found NH3 deposition around intensive pig farms is high, and determined it as a significant fate of the NH3 emitted from pig farms

Simple-Random-Sampling-Based Multiclass Text Classification Algorithm

Multiclass text classification (MTC) is a challenging issue and the corresponding MTC algorithms can be used in many applications. The space-time overhead of the algorithms must be concerned about the era of big data. Through the investigation of the token frequency distribution in a Chinese web document collection, this paper reexamines the power law and proposes a simple-random-sampling-based MTC (SRSMTC) algorithm. Supported by a token level memory to store labeled documents, the SRSMTC algorithm uses a text retrieval approach to solve text classification problems. The experimental results on the TanCorp data set show that SRSMTC algorithm can achieve the state-of-the-art performance at greatly reduced space-time requirements

Effects of core self-evaluations on the job burnout of nurses: the mediator of organizational commitment.

OBJECTIVE: To explore the impact of Core self-evaluations on job burnout of nurses, and especially to test and verify the mediator role of organizational commitment between the two variables. METHOD: Random cluster sampling was used to pick up participants sample, which consisted of 445 nurses of a hospital in Shanghai. Core self-evaluations questionnaire, job burnout scale and organizational commitment scale were administrated to the study participants. RESULTS: There are significant relationships between Core self-evaluations and dimensions of job burnout and organizational commitment. There is a significant mediation effect of organizational commitment between Core self-evaluations and job burnout. CONCLUSIONS: To enhance nurses' Core self-evaluations can reduce the incidence of job burnout

Evaluation of the Degradation on a COTS Linear CCD Induced by Total Ionizing Dose Radiation Damage

The evaluation of the degradation on a COTS linear Charge Coupled Device (CCD) induced by total ionizing dose (TID) radiation damage was presented. The radiation experiments were carried out at a 60Co γ-ray source. The parameters of DALSA’s linear CCD were measured at the CCD test systems as the EMVA1288 standard before and after the radiation. The dark current, dark signal nonuniformity (DSNU), photo response nonuniformity (PRNU), saturation output, full-well capacity (FWC), quantum efficiency (QE), and responsivity versus the TID were analyzed. The behavior of the tested CCD had shown a remarkable degradation after radiation. The degradation mechanisms of the CCD induced by TID damage were also discussed

Characterization of total ionizing dose damage in COTS pinned photodiode CMOS image sensors

The characterization of total ionizing dose (TID) damage in COTS pinned photodiode (PPD) CMOS image sensors (CISs) is investigated. The radiation experiments are carried out at a 60Co γ-ray source. The CISs are produced by 0.18-μm CMOS technology and the pixel architecture is 8T global shutter pixel with correlated double sampling (CDS) based on a 4T PPD front end. The parameters of CISs such as temporal domain, spatial domain, and spectral domain are measured at the CIS test system as the EMVA 1288 standard before and after irradiation. The dark current, random noise, dark signal non-uniformity (DSNU), photo response non-uniformity (PRNU), overall system gain, saturation output, dynamic range (DR), signal to noise ratio (SNR), quantum efficiency (QE), and responsivity versus the TID are reported. The behaviors of the tested CISs show remarkable degradations after radiation. The degradation mechanisms of CISs induced by TID damage are also analyzed