Sentence examples for can generally be grouped from inspiring English sources

The existing methods can generally be grouped into two categories, the adsorption of gases and the adsorption of polar liquids or molecules from solution.

The approaches for the design of approximate DSP systems can generally be grouped in three categories: (i) transistor level, (ii) gate level, and (iii) algorithmic level.

The 50+ projects we have helped fund have been diverse in topic, scale, and purpose, but they can generally be grouped into three categories: (1) those that promote local innovation and design, (2) those that focus on bridging opportunity gaps, (3) those who showcase something about Miami from a unique perspective.

These approaches can generally be grouped into two larger categories: logical and continuous models.

Youth activities vary widely in terms of specific activities and in time devoted to them but can generally be grouped by the type and total duration spent per type.

The second largest country in South America, behind Brazil, and the eighth largest in the world, Argentina offers a huge variety of landscapes, though property buying opportunities can generally be grouped into two types: city and country.

There are many different varieties and methods of attacks, they can generally all be grouped into several categories: by the general target of the attack, i.e., application, network, or mixed; by whether the attack is active or passive; by how the attack works, i.e., via password cracking or by exploiting code and cryptographic algorithms.

In addition, ordinary VQs can generally be divided into two groups: entropy-constrained VQ (ECVQ) [15] and resolution-constrained VQ (RCVQ) [16], and the above-mentioned methods are mainly proposed for the RCVQ and can hardly be applied on the ECVQ [17].

For graph classification, brain network analysis approaches can generally be put into three groups: (1) extracting some local measures (e.g., clustering coefficient) to train a standard vector-based classifier; (2) directly adopting graph kernels for classification; and (3) finding discriminative subgraph patterns.

Methods for this task can generally be categorized into three groups: hierarchical, local or hybrid methods [ 16].

There are many sources of uncertainty in an IEHM programme which can generally be divided into two groups, quantitative uncertainty and qualitative uncertainty [ 33].