A Cross-project Defect Prediction Model Using Feature Transfer and Ensemble Learning

Cross-project defect prediction (CPDP) trains the prediction models with existing data from other projects (the source projects) and uses the trained model to predict the target projects. To solve two major problems in CPDP, namely, variability in data distribution and class imbalance, in this paper we raise a CPDP model combining feature transfer and ensemble learning, with two stages of feature transfer and the classification. The feature transfer method is based on Pearson correlation coefficient, which reduces the dimension of feature space and the difference of feature distribution between items. The class imbalance is solved by SMOTE and Voting on both algorithm and data levels. The experimental results on 20 source-target projects show that our method can yield significant improvement on CPDP

Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks

We introduce Florence-2, a novel vision foundation model with a unified, prompt-based representation for a variety of computer vision and vision-language tasks. While existing large vision models excel in transfer learning, they struggle to perform a diversity of tasks with simple instructions, a capability that implies handling the complexity of various spatial hierarchy and semantic granularity. Florence-2 was designed to take text-prompt as task instructions and generate desirable results in text forms, whether it be captioning, object detection, grounding or segmentation. This multi-task learning setup demands large-scale, high-quality annotated data. To this end, we co-developed FLD-5B that consists of 5.4 billion comprehensive visual annotations on 126 million images, using an iterative strategy of automated image annotation and model refinement. We adopted a sequence-to-sequence structure to train Florence-2 to perform versatile and comprehensive vision tasks. Extensive evaluations on numerous tasks demonstrated Florence-2 to be a strong vision foundation model contender with unprecedented zero-shot and fine-tuning capabilities

Coupling Characteristics of Anterior Cruciate Ligament and Gait Analysis on Anterior Instability of Knee

Knee is the largest and most complicated joint in the human body. Since in humans the knee supports nearly the whole weight of the body, it is the joint most vulnerable to acute injury. Normal knee joint movements are accomplished via an intricate balance between passive ligamentous and active muscular components to maintain knee stability and prevent injury. The anterior cruciate ligament (ACL) is a critical passive component to normal knee function which acts to resist anterior rotatory motion of the tibia relative to the femur. The objective of this study is to investigate the coupling characteristic of the ACL, also try to search the kinematics and kinetic coupling characteristic make the quadriceps asymmetry after the ACL injured. Meanwhile this paper mainly presents some lower extremity data of the patients who had the anterior instability on the knee due to the ACL injury based on a infrared reflective marker system using stereophotogrammetry techniques. The compensatory mechanism and the biological coupling characteristic are analyzed in the paper. The results of this paper provide fundamental information on further study of kinematics and segmental coupling. The results of time-distance parameters indicate that the efficiency of walking is lower to some extent by decreased gait frequency and speed and prolonged gait circle that lead to unsteadiness of knee after injury. The kinematics data results demonstrate that the joint angle of extremity have adaptable changes produced by nervomuscular control system after injury. The kinemics data show that the other joints of affected extremity and joints of unaffected extremity both have adaptable changes, which is compensation profiting knee stability after injury. Keywords: biological coupling; kinematic coupling; compensatory mechanis

Population Redistribution among Multiple Electronic States of Molecular Nitrogen Ions in Strong Laser Fields

We carry out a combined theoretical and experimental investigation on the population distributions in the ground and excited states of tunnel ionized N2 molecules at various driver wavelengths in the near- and mid-infrared range. Our results reveal that efficient couplings (i.e., population exchanges) between the ground state and the excited states occur in strong laser fields. The couplings result in the population inversion between the ground and the excited states at the wavelengths near 800 nm, which is verified by our experiment by observing the amplification of a seed at ~391 nm. The result provides insight into the mechanism of free-space nitrogen ion lasers generated in remote air with strong femtosecond laser pulses.Comment: 18 pages, 4 figure

Current Status and Future Perspective of Waste Printed Circuit Boards Recycling

AbstractFor waste electrical and electronic equipment (WEEE), large quantities of waste printed circuit boards (PCBs) are released into environment. In light of their characteristics including complex structures, high metals content and potential hazards, waste PCBs are regarded as the most difficult parts of WEEE to be recycled. Therefore in recent ten years, the issue has attracted much attention from researchers and enterprises. This article reviews the latest processes of waste PCBs developed from laboratories to pilot engineering applications, and presents the most suitable available technology for waste PCBs, typically categorized as manually dismantling and automatic approaches in developing and developed countries, respectively. Towards achieving the better sustainability and recyclability for waste PCBs, nonmetal powder and precious metals should be developed for a deep recovery following mechanical treatment. Additionally, a significant shift is emerging from dismantling for recycling of printed wiring boards, to disassembling for remanufacturing of electronic components, which will indicate that a new paradigm of reclaiming waste PCBs is shaping

Evaluating active versus passive sources of human brucellosis in Jining City, China

Human brucellosis (HB) remains a serious public health concern owing to its resurgence across the globe and specifically in China. The timely detection of this disease is the key to its prevention and control. We sought to describe the differences in the demographics of high-risk populations with detected cases of HB contracted from active versus passive sources. We collected data from a large sample population from January to December 2018, in Jining City, China. We recruited patients that were at high-risk for brucellosis from three hospitals and Centers of Disease Control and Prevention (CDCs). These patients were classified into two groups: the active detection group was composed of individuals receiving brucellosis counseling at the CDCs; the passive detection group came from hospitals and high-risk HB groups. We tested a total of 2,247 subjects and 13.3% (299) presented as positive for HB. The positive rates for active and passive detection groups were 20.5% (256/1,249) and 4.3% (43/998), respectively (p < 0.001). The detection rate of confirmed HB cases varied among all groups but was higher in the active detection group than in the passive detection group when controlled for age, sex, ethnicity, education, career, and contact history with sheep or cattle (p < 0.05). Males, farmers, those with four types of contact history with sheep or cattle, and those presenting fever, hyperhidrosis and muscle pain were independent factors associated with confirmed HB cases in multivariate analysis of the active detection group. Active detection is the most common method used to detect brucellosis cases and should be applied to detect HB cases early and avoid misdiagnosis. We need to improve our understanding of brucellosis for high-risk populations. Passive HB detection can be supplemented with active detection when the cognitive changes resulting from brucellosis are low. It is important that healthcare providers understand and emphasis the timely diagnosis of HB