Mismatch in the Classification of Linear Subspaces: Sufficient Conditions for Reliable Classification

This paper considers the classification of linear subspaces with mismatched classifiers. In particular, we assume a model where one observes signals in the presence of isotropic Gaussian noise and the distribution of the signals conditioned on a given class is Gaussian with a zero mean and a low-rank covariance matrix. We also assume that the classifier knows only a mismatched version of the parameters of input distribution in lieu of the true parameters. By constructing an asymptotic low-noise expansion of an upper bound to the error probability of such a mismatched classifier, we provide sufficient conditions for reliable classification in the low-noise regime that are able to sharply predict the absence of a classification error floor. Such conditions are a function of the geometry of the true signal distribution, the geometry of the mismatched signal distributions as well as the interplay between such geometries, namely, the principal angles and the overlap between the true and the mismatched signal subspaces. Numerical results demonstrate that our conditions for reliable classification can sharply predict the behavior of a mismatched classifier both with synthetic data and in a motion segmentation and a hand-written digit classification applications.Comment: 17 pages, 7 figures, submitted to IEEE Transactions on Signal Processin

Compressive Classification

This paper derives fundamental limits associated with compressive classification of Gaussian mixture source models. In particular, we offer an asymptotic characterization of the behavior of the (upper bound to the) misclassification probability associated with the optimal Maximum-A-Posteriori (MAP) classifier that depends on quantities that are dual to the concepts of diversity gain and coding gain in multi-antenna communications. The diversity, which is shown to determine the rate at which the probability of misclassification decays in the low noise regime, is shown to depend on the geometry of the source, the geometry of the measurement system and their interplay. The measurement gain, which represents the counterpart of the coding gain, is also shown to depend on geometrical quantities. It is argued that the diversity order and the measurement gain also offer an optimization criterion to perform dictionary learning for compressive classification applications.Comment: 5 pages, 3 figures, submitted to the 2013 IEEE International Symposium on Information Theory (ISIT 2013

Laboratory-scale Investigation of Two-phase Relative Permeability

We present experimental investigations of two-phase (oil and water) relative permeability of laboratory scale rock cores through a joint use of direct X-ray measurement and flow-through investigations. The study is motivated by the observation that appropriate modeling of oil and water displacement in porous media or fractured rocks requires to be firmly grounded on accurate and representative core flood experiments and their appropriate interpretation. Experimental data embed key information relating relative permeability to observables. In this context, direct measurement of in-situ fluid saturation through X-Ray techniques has the unprecedented ability to characterize key processes occurring during the displacement of immiscible fluids through natural permeable materials. Water saturation profiles determined by X-ray scanner can then be linked to relative permeability curves stemming from two-phase flow experiments. We illustrate the benefit of employing direct X-Ray measurements of fluid saturation through a set of laboratory experiments targeted to the estimate of two-phase relative permeabilities of homogeneous samples (sand pack and Berea sandston core). Data are obtained for a range of diverse fractional flow rates and provide information at saturations ranging from irreducible water content to residual oil saturation. Our X-Ray saturation data are consistent with an interpretation of measured relative permeabilities as associated with water-wet rock conditions. The comparison of different preamble samples result high displacement efficiency and recovery factor corresponds to the high permeable and well-connected pores

Smooth golden fleece and prickly golden fleece as potential new vegetables for the ready-to-eat production chain

Smooth golden fleece (Urospermum dalechampii (L.) F.W. Schmidt) and prickly golden fleece (Urospermum picroides (L.) Scop. ex F.W. Schmid) are two wild edible plants used in traditional cuisine and folk medicine. In this research, the domestication of both species was tested for the first time using a floating system and two plant densities (412 and 824 plants m−2) to evaluate yield and quality. Some quality traits were also compared in cultivated plants and wild ones gathered in grasslands. The results show that both species are suitable for cultivation, although prickly golden fleece showed highest total phenols (132 mg 100 g−1 fresh weight—f.w.) and total antioxidant activity (0.19 mg 100 g−1 f.w.). At low sowing density, smooth golden fleece showed a nitrate content of about 7200 mg kg−1 f.w., 38% higher than plants of the same species grown at high density and plants of prickly golden fleece. These results suggest that high density can be used to optimize yield in two harvests. By permitting modulation of nutrients and a product without soil residues, the floating system used in this study proved suitable for growing U. dalechhampii and U. picroides as new vegetables for the ready-to-eat production chain

Securing Text Messages Using Graph Theory and Steganography

تامين البيانات يعتبر كعنصر مهم في انظمة لاتصالات وتناقل البيانات. ويكمن دوره الرئيسي في الحفاظ على المعلومات الحساسة بأمان وبشكل متكامل من المرسل إلى المتلقي ، وهناك نوعان من مبادئ الامنية هما التشفير وإخفاء المعلومات ، الأول يعمل على تغيير مظهر المعلومات ويغير من هيئتها في حين أن الثاني يخفيها من الدخلاء. النظام المصمم يقترح طريقة جديدة للتشفير باستخدام خصائص نظرية البيانات ؛ يعطي مفتاحًا تم إنشاؤه بتحويل كلمة السر الى مخطط (graph) من نوع متكامل  complete  ثم نستخرج مصفوفة التجاور adjacency matrix  للمخطط ونستخدمها كمفتاح نهائي لتشفير النص  وذلك باستخدام عملية الضرب (ضرب المصفوفات) للحصول على النص المشفر بعدها يتم استخدام طريقة البت الاقل اهمية Least Significant Bit LSB   لإخفاء الرسالة المشفرة في صورة ملونة في المكون الاخضر G من مكوناتها. وكذلك تم توظيف معادلة تحليل PSNR والتي اثبتت كفاءة النظام في اخفاء الرسالة باقل تشويش ممكن بحوالي (97-85)  dB لصورة الغلاف قبل وبعد عملية الاخفاء و MSE تتراوح بين  (4.537e-05 -5.27546e-04) و  SSIM=1.0.       Data security is an important component of data communication and transmission systems. Its main role is to keep sensitive information safe and integrated from the sender to the receiver. The proposed system aims to secure text messages through two security principles encryption and steganography. The system produced a novel method for encryption using graph theory properties; it formed a graph from a password to generate an encryption key as a weight matrix of that graph and invested the Least Significant Bit (LSB) method for hiding the encrypted message in a colored image within a green component. Practical experiments of (perceptibility, capacity, and robustness) were calculated using similarity measures like PSNR, MSE, and SSIM. These measures had proved the efficiency of the system for image quality and hiding messages with PSNR ratio more than 85 dB, MSE ranged (4.537e-05  to 5.27546e-04) and SSIM=1.0 for using a cover file with size ranged from 256×300 to 1200×760 pixels and message ranged from 16 to 300 characters.

Accurate, Very Low Computational Complexity Spike Sorting Using Unsupervised Matched Subspace Learning

This paper presents an adaptable dictionary-based feature extraction approach for spike sorting offering high accuracy and low computational complexity for implantable applications. It extracts and learns identifiable features from evolving subspaces through matched unsupervised subspace filtering. To provide compatibility with the strict constraints in implantable devices such as the chip area and power budget, the dictionary contains arrays of {-1, 0 and 1} and the algorithm need only process addition and subtraction operations. Three types of such dictionary were considered. To quantify and compare the performance of the resulting three feature extractors with existing systems, a neural signal simulator based on several different libraries was developed. For noise levels $\sigma_N$ between 0.05 and 0.3 and groups of 3 to 6 clusters, all three feature extractors provide robust high performance with average classification errors of less than 8% over five iterations, each consisting of 100 generated data segments. To our knowledge, the proposed adaptive feature extractors are the first able to classify reliably 6 clusters for implantable applications. An ASIC implementation of the best performing dictionary-based feature extractor was synthesized in a 65-nm CMOS process. It occupies an area of 0.09 mm2 and dissipates up to about 10.48 μW from a 1 V supply voltage, when operating with 8-bit resolution at 30 kHz operating frequency

Extraseasonal production in a soilless system and characterisation of landraces of carosello and barattiere (Cucumis melo l.)

Barattiere and Carosello are typical melon (Cucumis melo L.) landraces of Puglia’s (South-ern Italy) biodiversity. Their unripe fruits are locally consumed as an alternative to cucumbers (C. sativus L.) and are appreciated for their qualitative profile. Nevertheless, they are underutilized crops. For the high variability and confusing denominations, a morphological characterization is essential to discriminate and valorise landraces; additionally, it is fundamental to implement the agronomic technique to allow the cultivation outside the natural growth period (summer) by soilless cultivation. Two genotypes of Barattiere (‘Allungato’ and ‘Tondo’), two of Carosello (‘Scopatizzo’ and ‘Tomentoso’ (CAT)) and two of cucumber (‘Baby Star’ and ‘Modan’ hybrids) were vertically grown in the winter–spring period in a rockwool soilless system in a glasshouse with supplemental light. Lan-draces were characterized by morpho-physiological descriptors of melon; fruit biometrics and colour were analysed for all genotypes; productive parameters, leaf fluorescence, and chlorophyll content were measured. Genotypes varied in seeds, stem, leaf, fruit traits and they were andromonoecious; Carosello flowered earlier and produced more than Barattiere; CAT fruits were hairy and elongate, while other genotypes tended to rounder and glabrous fruits. Although landraces grew slower than cucumbers, both produced marketable fruits and the production of Carosello was comparable to cucumbers. In conclusion, Barattiere and Carosello have a productive potential and one vertically trained stem in a soilless system is appropriate for their extra-seasonal production