Discovering the Effectiveness of Pre-Training in a Large-scale Car-sharing Platform

Recent progress of deep learning has empowered various intelligent transportation applications, especially in car-sharing platforms. While the traditional operations of the car-sharing service highly relied on human engagements in fleet management, modern car-sharing platforms let users upload car images before and after their use to inspect the cars without a physical visit. To automate the aforementioned inspection task, prior approaches utilized deep neural networks. They commonly employed pre-training, a de-facto technique to establish an effective model under the limited number of labeled datasets. As candidate practitioners who deal with car images would presumably get suffered from the lack of a labeled dataset, we analyzed a sophisticated analogy into the effectiveness of pre-training is important. However, prior studies primarily shed a little spotlight on the effectiveness of pre-training. Motivated by the aforementioned lack of analysis, our study proposes a series of analyses to unveil the effectiveness of various pre-training methods in image recognition tasks at the car-sharing platform. We set two real-world image recognition tasks in the car-sharing platform in a live service, established them under the many-shot and few-shot problem settings, and scrutinized which pre-training method accomplishes the most effective performance in which setting. Furthermore, we analyzed how does the pre-training and fine-tuning convey different knowledge to the neural networks for a precise understanding

A Suspended Nanogap Formed by Field-Induced Atomically Sharp Tips

A sub-nanometer scale suspended gap (nanogap) defined by electric field-induced atomically sharp metallic tips is presented. A strong local electric field (\u3e109 V=m) across micro/nanomachined tips facing each other causes the metal ion migration in the form of dendrite-like growth at the cathode. The nanogap is fully isolated from the substrate eliminating growth mechanisms that involve substrate interactions. The proposed mechanism of ion transportation is verified using real-time imaging of the metal ion transportation using an in situ biasing in transmission electron microscope (TEM). The configuration of the micro/nanomachined suspended tips allows nanostructure growth of a wide variety of materials including metals, metal-oxides, and polymers. VC 2012 American Institute of Physics

EFFECT OF SEAT TUBE ANGLE ON THE WORK EFFICIENCY OF LOWER LIMB MUSCLES DURING CYCLING

The effect of seat tube angle (STA) on work efficiency at lower limb muscle was evaluated during a pedal rotation using inverse dynamic model. Since the target is not professional cyclist, the various seat tube angles of 78, 68, 58 and 48 degrees was investigated. Cycling simulation was performed at 250W and 60rpm. The works of individual muscle of lower limb and the total work was estimated. The result shows that the total work of single leg at seat tube angles of 78, 68, 58 and 48 degrees were 168.1(J), 167.9(J), 168.9(J) and 170.8(J) respectively. In conclusion, the exertion of lower limb for delivering same amount of work to the crank is the smallest at around 72 degree of seat tube angle which mean work efficiency of lower limb is the greates

No-rebound trend of sea ice reduction in the Arctic Ocean: Role of "inertia effect" of the ocean

第4回極域科学シンポジウム横断セッション：[IA] 「急変する北極気候システム及びその全球的な影響の総合的解明」―GRENE北極気候変動研究事業研究成果報告2013―11月12日（火） 国立極地研究所 ２階大会議

Six-dimensional considerations of Einstein's connection for the first two classes. I. The recurrence relations in 6

Lower dimensional cases of Einstein's connection were already investigated by many authors for n=2,3,4,5. This paper is the first part of the following series of two papers, in which we obtain a surveyable tensorial representation of 6-dimensional Einstein's connection in terms of the unified field tensor, with main emphasis on the derivation of powerful and useful recurrence relations which hold in 6-dimensional Einstein's unified field theory (i.e., 6-g-UFT)

Association between polymorphisms of arachidonate 12-lipoxygenase (ALOX12) and schizophrenia in a Korean population

Arachidonic acid (AA), an essential polyunsaturated fatty acid, is one of the major components of neural membranes, which show an altered phospholipid composition in schizophrenia. Arachidonate 12-lipoxygenase (ALOX12), an important enzyme, metabolizes AA to 12-HPETE, which affects catecholamine synthesis. However, research has yet to show the genetic association between ALOX12 and schizophrenia. Therefore, we investigated single nucleotide polymorphisms (SNP) of the ALOX12 gene in schizophrenia, recruiting patients with schizophrenia (n = 289) and normal controls (n = 306) from a Korean population. We selected three SNPs (rs1126667, rs434473, and rs1042357) of the ALOX12 gene and genotyped them by direct sequencing. We reviewed the schizophrenic patients' medical records and assessed them clinically using the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Negative Symptoms (SANS), and the Operational Criteria Checklist (OPCRIT). Then we statistically analyzed the genetic associations between the SNPs and schizophrenia, finding a genetic association between both rs1126667 and rs1042357 and schizophrenia, in the recessive model (p = 0.015 and 0.015, respectively). We also found an association between rs434473 and negative symptoms, defined through a factor analysis of the OPCRIT data (p = 0.040). Consequently, we suggest that SNPs of the ALOX12 gene might be associated with schizophrenia and negative symptoms in this Korean population. These weak positives require additional study