Abstract The primary objectives of the present exposition are to: (i) provide a generalized unified mathematical framework and setting leading to unique design computational algorithms for structural dynamic problems encompassing broad scope linear multi‐step (LMS) methods within limitation Dahlquist barrier theorem (Reference [3], G. Dahlquist, BIT 1963; 3 : 27), also new designs numerically dissipative with optimal algorithmic attributes that cannot be obtained employing existing...

Group recommendation has become highly demanded when users communicate in the forms of group activities online sharing communities. These include student study, family TV program watching, friends travel decision, etc. Existing techniques mainly focus on small user groups. However, communities have enabled among thousands users. Accordingly, over large groups urgent. In this paper, we propose a new framework to accomplish goal by exploring interests and connections between We first divide...

Some noteworthy and historical perspectives an overview of macroscale microscale heat transport behavior in materials structures are presented. The topic waves is also discussed. significance constitutive models for both conduction described conjunction with generalizations drawn concerning the physical relevance role relaxation retardation times emanating from Jeffreys type flux model, consequences to Cattaneo model subsequently Fourier model. Both macroscopic formulations applications...

With the development of mobile communication techniques, spatial crowdsourcing has become popular recently. A typical topic is task assignment, which assigns crowd workers to users' requests in real time and maximizes total revenue. However, it common that available over a platform are too far away serve requests, so some user may be rejected or responded at high money cost after long waiting. Fortunately, neighbors usually have resources for same services. Collaboratively conducting...

Nowadays, research on session-based recommender systems (SRSs) is one of the hot spots in recommendation domain. Existing methods make recommendations based user’s current intention (also called short-term preference) during a session, often overlooking specific preferences associated with these intentions. In reality, users usually exhibit diverse for different intentions, and even same intention, individual can vary significantly between users. As interact items throughout their intentions...

Abstract A standardized formal theory of development/evolution, characterization and design a wide variety computational algorithms emanating from generalized time weighted residual philosophy for dynamic analysis is first presented with subsequent emphasis on detailed formulations particular class relevant to the so‐called integration approaches which belong much broader classification discretized operators. Of fundamental importance in present exposition evolution theoretical encompassing...

Abstract A novel procedure, concepts, and new ideas to tailor design time operators under the notion of algorithms by is formulated in this exposition with emphasis on applications broad area computational mechanics, but focus solid structural mechanics/dynamics as an illustration. The concepts capitalize upon: (i) recently developed unified theory underlying ( Int. J. Numer. Meth. Engng 2004; 59 :597–668), (ii) newly established spaces algorithmic measures for evaluating quality 2005; 64...

Purpose To present a novel registration approach called LATIS (Local Affine Transformation guided by Internal Structures) for coregistering post prostatectomy pseudo ‐whole mount (PWM) pathological sections with in vivo MRI (magnetic resonance imaging) images. Materials and Methods Thirty‐five patients biopsy‐proven prostate cancer were imaged at 3T an endorectal coil. Excised specimens underwent quarter step‐section pathologic processing, digitization, annotation, assembly into PWM....

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> We propose a shot-based interest point selection approach for effective and efficient near-duplicate search over large collection of video shots. The basic idea is to eliminate the local descriptors with lower frequencies among selected frames from shot ensure that representation compact discriminative. Specifically, we an adaptive frame strategy called furthest voronoi (FPV) produce set...

The creation of sharing communities has resulted in the astonishing increasing digital videos, and their wide applications domains such as entertainment, online news broadcasting etc. improvement these relies on effective solutions for social user access to video data. This fact driven recent research interest recommendation shared communities. Although certain effort been put into communities, contextual information users not well exploited recommendation. In this paper, we propose an...

Abstract A new unified theory underlying the theoretical design of linear computational algorithms in context time dependent first‐order systems is presented. Providing for first perspectives and fresh ideas, unlike various formulations existing literature, present involves following considerations: (i) it leads to avenues designing foster notion by recovering (ii) describes a evolution operators via mathematical framework, (iii) places into explains/contrasts future developments including...

Using a new design procedure termed as Algorithms by Design, which we have successfully introduced in our previous efforts for second-order systems, alternatively, advance this exposition, the and development of computational framework that permits order-preserving time accurate, unconditionally stable, zero-order overshooting behavior, features with controllable numerical dissipation dispersion via family algorithms effectively solving transient first-order systems. The key feature is...

As one of the most popular services over online platforms, social recommendation has attracted increasing research efforts recently. Among all tasks, an important is item high speed media streams. Existing stream techniques are not effective for handling users with diverse interests. Meanwhile, approaches recommending items to a particular user efficient when applied huge number In this paper, we propose novel framework Specifically, first Bi-Layer Hidden Markov Model (BiHMM) that adaptively...

Federated learning (FL) has received much attention in privacy-preserving and responsible recommender systems. Recent studies have shown promising results while federating widely-used recommendation methods such as collaborative filtering. A major barrier when bringing FL into production is that the model complexity or volume of gradients to be transmitted over communication channel grows linearly number items a particular system increases. To address this challenge, we propose...