N,N-ジメチルホルムアミド(DMF)含有産業排水の嫌気性処理

Tohoku University李玉友課

An Investigation of Daylighting Performance in Sidelit Spaces

The positive influence of daylight on people’s work and well-being has been confirmed in many studies. However, excessive daylight causes discomfort glare, which decreases work productivity, impairs occupants’ vision, and may even cause headaches. Substantial studies explored glare by correlating physical lighting measurements and subjective evaluations. With the development of High Dynamic Range (HDR) image techniques, dynamic changes of daylighting distributions can be effectively captured. Consequently, more studies paired HDR image techniques with subject evaluations to explore glare. However, studies merely relying on field measurements are not only time-consuming and labor-intensive but may also disturb occupants. To address these problems, this dissertation proposed the method of integrating three research tools, HDR image techniques, simulations, and questionnaire surveys, to investigate daylight glare. Using sidelit spaces across five buildings as the example, this dissertation aimed to demonstrate the accuracy of simulation results and the correlations between subject occupant evaluations and physical lighting data derived from both field measurements and simulation results. This dissertation is comprised of three sections. The first section focused on field measurements. Over 200 HDR images across five buildings were taken and analyzed using select visual discomfort metrics. The results showed that daylight glare probability (DGP) outperformed the other visual discomfort metrics in terms of identifying intolerable and imperceptible glare. The second section utilized these HDR images to calibrate four of the five buildings’ Radiance models. The relative RMSE of simulated vertical eye illuminance under both the Perez all-weather sky model and the hybrid photo-radiometer sky model were 23.7% and 21.2%, respectively. The frequencies of accurate glare prediction under both sky models were 93.9% and 95.5%, respectively. The results indicated that Radiance models with precise geometries and material properties can accurately represent the real lighting environments. Finally, the third section paired questionnaire surveys with both the HDR image technique and simulations to investigate daylight qualities within an open-plan office. The study found that taller windows, proximity to windows, and facing towards windows caused severe glare. By removing workstation partitions and arranging seating orientations perpendicular to the windows, the renovated layout design increased occupant satisfaction with their daylighting environments and tolerance for daylight glare. The last section demonstrated the effectiveness of integrating the three tools in lighting studies and the importance of interior layout and furniture designs in terms of daylight glare reduction

Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks

It is desirable to train convolutional networks (CNNs) to run more efficiently during inference. In many cases however, the computational budget that the system has for inference cannot be known beforehand during training, or the inference budget is dependent on the changing real-time resource availability. Thus, it is inadequate to train just inference-efficient CNNs, whose inference costs are not adjustable and cannot adapt to varied inference budgets. We propose a novel approach for cost-adjustable inference in CNNs - Stochastic Downsampling Point (SDPoint). During training, SDPoint applies feature map downsampling to a random point in the layer hierarchy, with a random downsampling ratio. The different stochastic downsampling configurations known as SDPoint instances (of the same model) have computational costs different from each other, while being trained to minimize the same prediction loss. Sharing network parameters across different instances provides significant regularization boost. During inference, one may handpick a SDPoint instance that best fits the inference budget. The effectiveness of SDPoint, as both a cost-adjustable inference approach and a regularizer, is validated through extensive experiments on image classification

Cochlear homeostasis and its role in genetic deafness

AbstractEach component of the human ear performs a specific function in hearing. The actual process of sound transduction takes place in the auditory portion of the inner ear, the fluid-filled cochlea. In the cochlea, the sensitivity and efficiency of sensory apparatus to convert mechanical energy into neural activity, largely depends on the fluidic and ionic environment. In the lateral wall of cochlea, the secretory epithelium stria vascularis plays an important role in the maintenance of fluidic and ionic homeostasis. A variety of gene mutations disturbs the cochlear homeostasis and subsequently leads to hearing impairment. The review covers several aspects of cochlear homeostasis, from cochlear fluid and the functional role of stria vascularis, cochlear K+recycling and its molecular substrates to genetic deafness with abnormal cochlear homeostasis

A Novel Wide-Area Backup Protection Based on Fault Component Current Distribution and Improved Evidence Theory

In order to solve the problems of the existing wide-area backup protection (WABP) algorithms, the paper proposes a novel WABP algorithm based on the distribution characteristics of fault component current and improved Dempster/Shafer (D-S) evidence theory. When a fault occurs, slave substations transmit to master station the amplitudes of fault component currents of transmission lines which are the closest to fault element. Then master substation identifies suspicious faulty lines according to the distribution characteristics of fault component current. After that, the master substation will identify the actual faulty line with improved D-S evidence theory based on the action states of traditional protections and direction components of these suspicious faulty lines. The simulation examples based on IEEE 10-generator-39-bus system show that the proposed WABP algorithm has an excellent performance. The algorithm has low requirement of sampling synchronization, small wide-area communication flow, and high fault tolerance

A novel inductor for stabilizing the dc link of adjustable speed drive

The DC-link filter which includes a magnetic inductor and a storage capacitor is one of the key parts of adjustable speed drives in the market. It significantly affects the stability, reliability, and power density of the motor-drive system. This paper proposes a novel, variable active inductor to improve the performance of DC links in terms of stability, reliability, size, and cost. In contrast to conventional DC-link magnetic inductors, the variable active inductor is made of power electronic circuits, including active switches, passive filters, and smart controllers, which no longer rely on magnetic material. The demonstration shows that the inductor can emulate the electrical characteristics of the magnetic inductor for filtering harmonics and stabilizing the DC link, meanwhile representing a smaller size, lighter weight, and lower cost compared with a conventional one. Furthermore, this paper proposes a variable inductance control method which is able to adaptively tune the inductance value with the operating conditions of the drive system. The DC link can be stabilized, and high performance can be maintained in both balanced and unbalanced grid voltage conditions. A case study of the proposed variable inductor in a motor drive with a three-phase diode-bridge rectifier as the front end is discussed. Experimental results are given to verify the functionality and effectiveness of the proposed variable inductor

Application of integrated formation evaluation and three-dimensional modeling in shale gas prospect identification

Identifying the shale gas prospect is crucial for gas extraction from suchreservoirs. Junggar Basin (in Northwest China) is widely considered tohave high potential as a shale gas resource, and the Jurassic, the mostsignificant gas source strata, is considered as prospective for shale gasexploration and development. This study evaluated the Lower JurassicBadaowan Formation shale gas potential combined with geochemical,geological, and well logging data, and built a three-dimensional (3D)model to exhibit favorable shale gas prospects. In addition, methane sorption capacity was tested for verifying the prospects. The Badaowan shalehad an average total organic carbon (TOC) content of 1.30 wt. % andvitrinite reflectance (Ro) ranging from 0.47% to 0.81% with dominatedtype III organic matter (OM). X-ray diffraction (XRD) analyses showedthat mineral composition of Badaowan shale was fairly homogeneous anddominated by clay and brittle minerals. 67 wells were used to identifyprospective shale intervals and to delineate the area of prospects. Consequently, three Badaowan shale gas prospects in the Junggar Basin wereidentified: the northwestern margin prospect, eastern Central Depressionprospect and Wulungu Depression prospect. The middle interval of thenorthwestern margin prospect was considered to be the most favorableexploration target benefitted by wide distribution and high lateral continuity. Generally, methane sorption capacity of the Badaowan shale wascomparable to that of the typical gas shales with similar TOC content,showing a feasible gas potential