We extend a previous work on a multithreaded typed assembly language (MIL) targeted at shared memory multiprocessors, and describe the design of a type-preserving compiler from the π-calculus into MIL. The language enforces a policy on lock usage through a typing system that also ensures race-freedom for typable programs, while allowing for typing various important concurrency patterns. Our tra...

In this paper, the effectiveness of a corrective learning algorithm MIL (Mirror Image Learning) [1] [2] is comparatively studied with that of ALSM (Average Learning Subspace Method) [3]. Both MIL and ALSM were proposed to improve the learning effectiveness of class conditional distributions. While the ALSM modifies the basis vectors of a subspace by subtracting the autocorrelation matrix for co...

We extend a previous work on a multithreaded typed assembly language (MIL) targeted at shared memory multiprocessors, and describe the design of a type-preserving compiler from the π-calculus into MIL. The language enforces a policy on lock usage through a typing system that also ensures race-freedom for typable programs, while allowing for typing various important concurrency patterns. Our tra...

In the supervised learning setting termed Multiple-Instance Learning (MIL), the examples are bags of instances, and the bag label is a function of the labels of its instances. Typically, this function is the Boolean OR. The learner observes a sample of bags and the bag labels, but not the instance labels that determine the bag labels. The learner is then required to emit a classification rule f...

BACKGROUND Miltefosine (MIL), the only oral drug for visceral leishmaniasis (VL), is currently the first-line therapy in the VL elimination program of the Indian subcontinent. Given the paucity of anti-VL drugs and the looming threat of resistance, there is an obvious need for close monitoring of clinical efficacy of MIL. METHODS In a cohort study of 120 VL patients treated with MIL in Nepal,...

A hydrophilic, hydrostable porous metal organic framework (MOF) material-MIL-101 (Cr) was successfully doped into the dense selective polyamide (PA) layer on the polysulfone (PS) ultrafiltration (UF) support to prepare a new thin film nanocomposite (TFN) membrane for water desalination. The TFN-MIL-101 (Cr) membranes were characterized by SEM, AFM, XPS, wettability measurement and reverse osmos...

A cationic porous framework with mobile anions (MIL-101(Cr)-Cl) was easily and successfully synthesized by utilizing the stronger affinity of F- to Al3+ than Cr3+ in the charge-balanced framework of MIL-101(Cr). The structure, morphology and porosity of MIL-101(Cr)-Cl were characterized. The obtained new materials retain the high surface area, good thermostability, and structure topology of MIL...

Multiple Instance Learning (MIL) has been widely used in various applications including image classification. However, existing MIL methods do not explicitly address the multi-target problem where the distributions of positive instances are likely to be multi-modal. This strongly limits the performance of multiple instance learning in many real world applications. To address this problem, this ...

Splenocytes from nonobese diabetic mice overexpressing murine IL (mIL)-4 upon recombinant retrovirus infection lose their capacity to transfer diabetes to nonobese diabetic-scid recipients. Diabetes appeared in 0-20% of mice injected with mIL-4-transduced cells vs 80-100% of controls injected with beta-galactosidase-transduced cells. Protected mice showed a majority of islets (60%) presenting w...

In multiple-Instance Learning (MIL), training class labels are attached to sets of bags composed of unlabeled instances, and the goal is to deal with classification of bags. Most previous MIL algorithms, which tackle classification problems, consider each instance as a represented feature. Although the algorithms work well in some prediction problems, considering diverse features to represent a...