Deliver or hold: Approximation Algorithms for the Periodic Inventory Routing Problem

The inventory routing problem involves trading off inventory holding costs at client locations with vehicle routing costs to deliver frequently from a single central depot to meet deterministic client demands over a finite planing horizon. In this paper, we consider periodic solutions that visit clients in one of several specified frequencies, and focus on the case when the frequencies of visiting nodes are nested. We give the first constant-factor approximation algorithms for designing optimum nested periodic schedules for the problem with no limit on vehicle capacities by simple reductions to prize-collecting network design problems. For instance, we present a 2.55-approximation algorithm for the minimum-cost nested periodic schedule where the vehicle routes are modeled as minimum Steiner trees. We also show a general reduction from the capacitated problem where all vehicles have the same capacity to the uncapacitated version with a slight loss in performance. This reduction gives a 4.55-approximation for the capacitated problem. In addition, we prove several structural results relating the values of optimal policies of various types

Using a delta-doped CCD to determine the energy of a low-energy particle

The back surface of a thinned charged-coupled device (CCD) is treated to eliminate the backside potential well that appears in a conventional thinned CCD during backside illumination. The backside of the CCD includes a delta layer of high-concentration dopant confined to less than one monolayer of the crystal semiconductor. The thinned, delta-doped CCD is used to determine the energy of a very low-energy particle that penetrates less than 1.0 nm into the CCD, such as a proton having energy less than 10 keV

Evaluating the interaction of 308-nm xenon chloride excimer laser with human dentin and enamel hard tissues

Background: The pulsed output of the 308 nm XeCl laser and its photoablation action rather than photothermal action offers the ability to remove dental hard tissues with minimal generation of heat in the tissue. Materials and Methods: A total of 20 human molar teeth (ten teeth used as enamel samples and ten teeth used as dentin samples after removing the enamel tissue from their crowns) were irradiated by the laser. The crown of each sample was regarded as a cube which its lateral sides were exposed in 2Hz frequency without water cooling. Also, 18 holes for all enamel samples and 18 holes for all dentin samples were obtained. Three different amounts of energy were selected as a variable factor with 6 different numbers of pulses in each energy. The images of these holes were prepared by optic and computer combining, and the amounts of the ablation depth and effective ablation area were calculated using the MATLAB software. Results: The amounts of ablation depth were increased with increasing the number of pulses for both enamel and dentin tissues. The amounts of ablation depth were also increased with increasing the amounts of energy for both enamel and dentin tissues. The greater amounts of ablation depth and effective ablation area were observed in the dentin tissue rather than the enamel tissue. The borders of created holes were reported sharp and clear. Conclusion: The application of the XeCl laser for hard tissue removal and cavity preparation can be possible after some certain modifications

Delta-doped hybrid advanced detector for low energy particle detection

A delta-doped hybrid advanced detector (HAD) is provided which combines at least four types of technologies to create a detector for energetic particles ranging in energy from hundreds of electron volts (eV) to beyond several million eV. The detector is sensitive to photons from visible light to X-rays. The detector is highly energy-sensitive from approximately 10 keV down to hundreds of eV. The detector operates with milliwatt power dissipation, and allows non-sequential readout of the array, enabling various advanced readout schemes

Delta-doped hybrid advanced detector for low energy particle detection

A delta-doped hybrid advanced detector (HAD) is provided which combines at least four types of technologies to create a detector for energetic particles ranging in energy from hundreds of electron volts (eV) to beyond several million eV. The detector is sensitive to photons from visible light to X-rays. The detector is highly energy-sensitive from approximately 10 keV down to hundreds of eV. The detector operates with milliwatt power dissipation, and allows non-sequential readout of the array, enabling various advanced readout schemes

Calibration Model Maintenance in Melamine Resin Production: Integrating Drift Detection, Smart Sample Selection and Model Adaptation

The physico-chemical properties of Melamine Formaldehyde (MF) based thermosets are largely influenced by the degree of polymerization (DP) in the underlying resin. On-line supervision of the turbidity point by means of vibrational spectroscopy has recently emerged as a promising technique to monitor the DP of MF resins. However, spectroscopic determination of the DP relies on chemometric models, which are usually sensitive to drifts caused by instrumental and/or sample associated changes occurring over time. In order to detect the time point when drifts start causing prediction bias, we here explore a universal drift detector based on a faded version of the Page-Hinkley (PH) statistic, which we test in three data streams from an industrial MF resin production process. We employ committee disagreement (CD), computed as the variance of model predictions from an ensemble of partial least squares (PLS) models, as a measure for sample-wise prediction uncertainty and use the PH statistic to detect hanges in this quantity. We further explore supervised and unsupervised strategies for (semi-)automatic model adaptation upon detection of a drift. For the former, manual reference measurements are requested whenever statistical thresholds on Hotelling’s $T^2$ and/or Q-Residuals are violated. Models are subsequently re-calibrated using weighted partial least squares in order to increase the influence of newer samples, which increases the flexibility when adapting to new (drifted) states. Unsupervised model adaptation is carried out exploiting the dual antecedent-consequent structure of a recently developed fuzzy systems variant of PLS termed FLEXFIS-PLS. In particular, antecedent parts are updated while maintaining the internal structure of the local linear predictors (i.e. the consequents). We found improved drift detection capability of the CD compared to Hotelling’s $T^2$ and Q-Residuals when used in combination with the proposed PH test. Furthermore, we found that active selection of samples by active learning (AL) used for subsequent model adaptation is advantageous compared to passive (random) selection in case that a drift leads to persistent prediction bias allowing more rapid adaptation at lower reference measurement rates. Fully unsupervised adaptation using FLEXFIS-PLS could improve predictive accuracy significantly for light drifts but was not able to fully compensate for prediction bias in case of significant lack of fit w.r.t. the latent variable space

Calibration and flight performance of the long-slit imaging dual order spectrograph

We present a preliminary calibration and flight performance of the Long-Slit Imaging Dual Order Spectrograph (LIDOS), a rocket-borne instrument with a large dynamic range in the 900 - 1700A bandpass. The instrument observes UV-bright objects with a CCD channel and fainter nebulosity with an MCP detector. The image quality and the detector quantum efficiencies were determined using the calibration and test equipment at the Johns Hopkins University, and further monitored using an on-board electron-impact calibration lamp. We review results from each of the three flights of the instrument.Comment: 12 pages. to appear in Proc. SPIE 701

Method to Improve Indium Bump Bonding via Indium Oxide Removal Using a Multi-Step Plasma Process

A process for removing indium oxide from indium bumps in a flip-chip structure to reduce contact resistance, by a multi-step plasma treatment. A first plasma treatment of the indium bumps with an argon, methane and hydrogen plasma reduces indium oxide, and a second plasma treatment with an argon and hydrogen plasma removes residual organics. The multi-step plasma process for removing indium oxide from the indium bumps is more effective in reducing the oxide, and yet does not require the use of halogens, does not change the bump morphology, does not attack the bond pad material or under-bump metallization layers, and creates no new mechanisms for open circuits

Two-Step Plasma Process for Cleaning Indium Bonding Bumps

A two-step plasma process has been developed as a means of removing surface oxide layers from indium bumps used in flip-chip hybridization (bump bonding) of integrated circuits. The two-step plasma process makes it possible to remove surface indium oxide, without incurring the adverse effects of the acid etching process