Efficient high order matching

We present a computational approach to high-order matching of data sets in IR(d). Those are matchings based on data affinity measures that score the matching of more than two pairs of points at a time. High-order affinities are represented by tensors and the matching is then given by a rank-one approximation of the affinity tensor and a corresponding discretization. Our approach is rigorously justified by extending Zass and Shashua's hypergraph matching to high-order spectral matching. This paves the way for a computationally efficient dual-marginalization spectral matching scheme. We also show that, based on the spectral properties of random matrices, affinity tensors can be randomly sparsified while retaining the matching accuracy. Our contributions are experimentally validated by applying them to synthetic as well as real data sets.     

Microwave remote sensing of physically buried objects in the Negev Desert: implications for environmental research

We report remote detections of physically buried specularly reflecting objects using microwave radar at two sites: Ashalim and Tseelim in the northern region of the Negev Desert, Israel. These detections provide confirmation that microwave subsurface remote sensing is a genuine phenomenon. At Ashalim, a scatterometer operating in the P-band (441 MHz, 68 cm) was mounted on a cherry picker truck at a height of 8 m and used to detect two triangular aluminum mesh reflectors (forming a 1-m square area reflector) buried down to a depth of 8 cm in dry sand. At Tseelim, the same scatterometer was mounted on an airplane flying at an altitude of 70 m and used to detect 1-m square aluminum reflectors (each one submerged at a different location along the airplane flight path) buried down to a depth of 20 cm. The experimental results compare favorably with a theoretical model that incorporates radar absorption effects arising in the sandy subsurface layer and radar interference effects arising from phase differences between reflections from the surface and buried reflector. The theoretical modeling also predicts the detection of a subsurface reflector down to a depth of about 4.4 m. This experiment and the associated modeling approach is the first of a series of planned experiments, which we outline for the detection and the theoretical evaluation of buried reflectors using remote microwave and VHF radar. We identify potential subject areas for environmental research.     

Communication—Processor Tradeoffs in a Limited Resources PRAM

We consider a simple restriction of the PRAM model (called PPRAM), where the input is arbitrarily partitioned between a fixed set of p processors and the shared memory is restricted to m cells. This model allows for investigation of the tradeoffs/ bottlenecks with respect to the communication bandwidth (modeled by the shared memory size m ) and the number of processors p . The model is quite simple and allows the design of optimal algorithms without losing the effect of communication bottlenecks. We have focused on the PPRAM complexity of problems that have $\tilde{O}$ (n) sequential solutions (where n is the input size), and where m ≤ p ≤ n . We show essentially tight time bounds (up to logarithmic factors) for several problems in this model such as summing, Boolean threshold, routing, integer sorting, list reversal and k -selection. We get typically two sorts of complexity behaviors for these problems: One type is $\tilde{O}$ (n/p + p/m) , which means that the time scales with the number of processors and with memory size (in appropriate ranges) but not with both. The other is $\tilde{O}$ (n/m) , which means that the running time does not scale with p and reflects a communication bottleneck (as long as m < p ). We are not aware of any problem whose complexity scales with both p and m (e.g. $O(n/\sqrt{m \cdot p})$ ). This might explain why in actual implementations one often fails to get p -scalability for p close to n .     

The effect of hydrogen on boron diffusion in SiO2

The diffusivity of boron in silicon dioxide may be increased by the introduction of hydrogen into the annealing atmosphere. In this paper we report on the diffusion characteristics of boron ion-implanted into thermally grown SiO₂. A sensitive technique was used in which the boron atoms redistributed into the substrate are characterized by electrical methods. The diffusivity of boron in thermal SiO₂ was measured over the temperature range of 950-1150°C with hydrogen partial pressure from 0 to 0.2 atm. It was found that the diffusion coefficient of boron in oxide at 1150° C increases as the square root of the hydrogen partial pressure. At fixed pressure the temperature dependence of the diffusion coefficient obeys a single-activation-energy exponential rule. At 0.1 atm partial pressure of H₂ the activation energy is 3.0 eV and the preexponential factor is 6 x 10⁵ [cm²/sec.].     

The diffusion of ion-implanted arsenic in thermally grown SiO2

The diffusivity of ion-implanted As in SiO₂ is investigated as a function of the implanted dose, oxide type and ambient in the 1000–1200° C temperature range. The As diffusivity in oxide is extracted, using electrical methods, from the profiles of As diffused into the substrate. Secondary-ion-mass-spectroscopy depth profiles of some of the samples are in agreement with the results of the electrical methods. Two types of oxide are investigated: Dry oxide grown in O₂ and wet oxide grown in steam. The diffusivity is characterized as a function of the temperature for dry oxide annealed in N₂, and for wet oxide annealed both in N₂ and in N₂/H₂ (10%). The measured As diffusivity vs temperature is fitted to a single activation energy exponential model. For the wet-grown oxide, the extracted activation energy for the N₂/H₂ (10%) annealed sample is 4.4 ± 0.5 eV and for the N₂ annealed oxide it is found to be 5.5 ± 0.5 eV. For oxide grown in dry oxygen the As diffusivity is characterized also as a function of the implant dose. It is found to be independent of the implanted dose, for ion energy of 40 keV and dose in the 10¹²–10¹⁵ cm^-2 range, and its activation energy equals 4.7 ± 0.5 eV. The extracted parameters were installed in the SUPREM-III process simulation program and correctly predict ion-implanted As diffusion behavior in SiO₂.     

Nanoinformatics in Drug Delivery

The use of nanomedicine for targeted drug delivery, though well established, is still a growing and developing field of research with potential benefits to many biomedical problems. There is a plethora of nano-carriers with myriads of designs of shapes, sizes and composition that involves complex, trial and error based preparation protocols. The digital age brought an information revolution with automated data analysis, machine learning and data mining applied to almost every field of research including drug delivery. Indeed, nanomedicine has benefitted from the use of data science and information science to optimize, standardize, and understand the synthesis, characterization, and biological effects of nanomaterials. This short review will describe several concepts and a few examples of nanoinformatics, including Nano-Quantitative Structure-Activity Relationship (Nano-QSAR), the use of computational methods for predicting different properties of nanomedicine in drug delivery and propose an outlook for the future.     

Combining static and dynamic array detection for binary synthesis with multiple memory ports

In High-Level Synthesis, Binary Synthesis is a method for synthesizing compiled applications for which the source code is not available. One of the advantages of FPGAs over processors is the availability of multiple internal and external memory banks. Binary synthesis tools use multiple memory banks if they are able to recover data-structures from the binary. In this work we improve the recovery of data-structures by introducing dynamic memory analysis and combining it with improved static memory analysis. We show that many applications can only be synthesized using dynamic memory analysis. We present two FPGA based architectures for implementing the bound-checking and recovery for the synthesized code. Our experiments show that the proposed technique accelerates the execution of applications which use multiple memory banks concurrently. We demonstrate that many binary applications indeed benefit from this technique.     

Barrier layers for Cu ULSI metallization

Barrier layers are integral parts of many metal interconnect systems. In this paper we review the current status of barrier layers for copper metallization for ultra-large-scale-integration (ULSI) technology for integrated circuits (ICs) manufacturing. The role of barrier layers is reviewed and the criteria that determine the process window, i.e. the optimum barrier thickness and the deposition processes, for their manufacturing are discussed. Various deposition methods are presented: physical vapor deposition (PVD), chemical vapor deposition (CVD), electrochemical deposition (ECD), electroless deposition (ELD), and atomic layer CVD (ALCVD) for barrier layers implementation. The barrier integration methods and the interaction between the barrier and the copper metallization are presented and discussed. Finally, the common inspection and metrology for barrier layer are critically reviewed.     

A signal processing approach to symmetry detection.

We present an algorithm that detects rotational and reflectional symmetries of two-dimensional objects. Both symmetry types are effectively detected and analyzed using the angular correlation (AC), which measures the correlation between images in the angular direction. The AC is accurately computed using the pseudopolar Fourier transform, which rapidly computes the Fourier transform of an image on a near-polar grid. We prove that the AC of symmetric images is a periodic signal whose frequency is related to the order of the symmetry. This frequency is recovered via spectrum estimation, which is a proven technique in signal processing with a variety of efficient solutions. We also provide a novel approach for finding the center of symmetry and demonstrate the applicability of our scheme to the analysis of real images.