Information filtering is an area of research that develops tools for discriminating between relevant and irrelevant information. Users first give descriptions about what they need, i.e., user profiles represented by a set of keywords, to start the services. A profile index is built on these profiles. Then, the Web page will be recommended to the users whose profiles belong to the filtered resul...

Let G be a directed graph with n vertices, subject to dynamic updates, and such that each edge weight can assume at most S diierent arbitrary real values throughout the sequence of updates. We present a new algorithm for maintaining all pairs shortest n) amortized time per update and in O(1) worst-case time per distance query. This improves over previous bounds. We also show how to obtain query...

Background/aim: this editorial is aimed at providing a reference for the medical nutritional therapy (MNT) in patients with type 2 diabetes, as recommended by new Italian guidelines treatment of diabetes and its 2023-Update. Methods results: present paper re¬vised recently published (outpatients) update, either primary care or specialist referral. The guideline has been developed following meth...

The main objective is to design DA based adaptive filter in order to decreasing the logic complexity. Throughput is increasedby using parallel Look Up Table (LUT) update and concurrent implementation of filtering and weight-update operations.DA uses bitserial operations andlook-up tables (LUTs) to implement high throughput filters. Two smart LUT updating methods are developed, and least meansqu...

This literature review presents the most recent developments in the management of multiple myeloma, which is characterized by the presence of abnormal plasma cells (myeloma cells) that accumulate into the bone marrow. Aspects related to pathophysiology, clinical manifestations, laboratory, study and treatment are described. These pieces of information  are necessary to accomplish a better ...

Recursive identification methods using time-domain data have been developed in [l, 21 utilizing a gradient-based identification technique for estimating the Markov parameters of a system. This identification technique utilizes the ARMARKOV representation of a time-invariant finite-dimensional system which relates the current output of a system to past outputs as well as current and past inputs....

i,y with features x and label y. The computation of this sensitivity value is governed by the actual online update where we compute the derivative of the change in the prediction as a function of the importance weight w for a hypothetical example with cost 0 or cost 1 and the same features. This is possible for essentially all online update rules on importance weighted examples and it correspon...