The Strong Minimalist Thesis

This article reviews and attempts to evaluate the various proposals for a strong minimalist thesis that have been at the core of the minimalist program for linguistic theory since its inception almost three decades ago. These proposals have involved legibility conditions for the interface between language and the cognitive systems that access it, the simplest computational operation Merge (its form and function), and principles of computational efficiency (including inclusiveness, no-tampering, cyclic computation, and the deletion of copies). This evaluation attempts to demonstrate that reliance on interface conditions encounters serious long-standing problems for the analysis of language. It also suggests that the precise formulation of Merge may, in fact, subsume the effects of those principles of efficient computation currently under investigation and might possibly render unnecessary proposals for additional structure building operations (e.g., Pair-Merge and FormSequence).

Against Membership Inference Attack: Pruning is All You Need

The large model size, high computational operations, and vulnerability against membership inference attack (MIA) have impeded deep learning or deep neural networks (DNNs) popularity, especially on mobile devices. To address the challenge, we envision that the weight pruning technique will help DNNs against MIA while reducing model storage and computational operation. In this work, we propose a pruning algorithm, and we show that the proposed algorithm can find a subnetwork that can prevent privacy leakage from MIA and achieves competitive accuracy with the original DNNs. We also verify our theoretical insights with experiments. Our experimental results illustrate that the attack accuracy using model compression is up to 13.6% and 10% lower than that of the baseline and Min-Max game, accordingly.

Quantum Gates

As discussed in Chap. 10.1007/978-3-030-61601-4_2, information in classical computers is represented by bits. However, if the bits did not change, then the computer would remain the same forever and would not be very useful! Therefore, it is necessary to change the values of bits depending on what you want the computer to do. For example, if you want a computer to multiply the number 2 and the number 3 together to produce the number 6, then you need to put each of the numbers 2 and 3 into an 8-bit binary representation, and then have a computational operation to multiply the two 8-bit values together to produce 6. The operation of changing bits in a classical computer is performed by classical logic gates.

The hippocampus, memory, and spatial function

The hippocampal system provides a beautiful example of how different classes of neuronal network in the brain work together as a system to implement episodic memory, the memory for particular recent events. The hippocampus contains spatial view neurons in primates including humans, which provide a representation of locations in viewed space. These representations can be combined with object and temporal representations to provide an episodic memory about what happened where and when. A key part of the system is the CA3 system with its recurrent collateral connections that provide a single attractor network for these associations to be learned. The computational generation of time, encoded by time cells in the hippocampus, is described, and this leads to a theory of hippocampal replay and reverse replay. The computational operation of a key part of the architecture, the recall of memories to the neocortex, is described.

Fundamental Operations of Language

20 years ago, in lectures in Brasilia, I suggested that we might someday discover that the Faculty of Language (FL) is “beautifully designed, a near-perfect solution to the conditions imposed by the general architecture of the mind-brain in which it is inserted, another illustration of how natural laws work out in wondrous ways,” so that language is rather like a snowflake, and the near-perfect design can be expected to impose inefficiency of use. I added that “these are fables,” with the redeeming value that they “might even turn out to have some elements of validity. In the years since, solid reasons have been found to suggest that these hopes were understated, and that the “fable” – the Strong Minimalist Thesis – appears to have considerable validity. A number of striking and puzzling properties of FL – “universals of language” in the contemporary sense – have been shown to derive from the simplest computational operation, Merge, along with conditions of computational efficiency that are in effect part of natural law. And as anticipated, they do indeed impose communicative inefficiency.

RBFN based IPFC for Enhancement of Power System Security

Where the information is perverted by extreme noise level, causes complicated relationship between information and its yield. In that case, ANN is well known to solve this dilemma by giving fine result. Now, for specification and fine tuning of parameter, role of RBFN comes into picture. For optimizing the adoptability of the computational operation, Radial basis function (RBF) networks [10] is suggested which reduces execution time by providing more flexibility to identify the dynamic changes. For checking strength of 10-machine system, while designing, two signals: variation in V & variation in Vdc are correlated. Competency of PI controller with RBFN has been analyzed under varying system conditions. Influence of additional suppression controller: POD is designed to get promising results. Recommended intelligent controllers are having proficiency of scrutinizing unique features of IPFC. Feasibility of different controllers subject to a three phase fault are studied and investigated on time domain basis in MATLAB software to verify the effectiveness of each controller.

Spectral Methods in Spatial Statistics

When the spatial location area increases becoming extremely large, it is very difficult, if not possible, to evaluate the covariance matrix determined by the set of location distance even for gridded stationary Gaussian process. To alleviate the numerical challenges, we construct a nonparametric estimator called periodogram of spatial version to represent the sample property in frequency domain, because periodogram requires less computational operation by fast Fourier transform algorithm. Under some regularity conditions on the process, we investigate the asymptotic unbiasedness property of periodogram as estimator of the spectral density function and achieve the convergence rate.

Self-Tuning Varri Method in Preparing Fatigue Segment

An overlapping segmentation method on time series data is often used for preparing training dataset i.e. the population of instance, for classification data mining. Having large number of redundant instances would burden the training process with heavy computational operation. This would happen if practitioners fail to acknowledge an appropriate amount of overlap when performing the time series segmentation. Fortunately, the risk could be decreased if knowledge preferences can be determined to guide on overlapping criteria in the segmentation algorithm. Thus, this study aims to investigate how the Varri method is able to contribute for better understanding in preparing training dataset consists of irredundant fatigue segment from the loading history (fatigue signal). Generally, the method locates segment boundaries based on local maxima in the difference function which are above the assigned threshold. In the present study, the mean and standard deviation have been used to define the function due to the fact that predicting attributes are the key components in defining instance redundancy. The resulting dataset from the proposed method is trained by three classification algorithms under the supervision of the Genetic algorithms-based feature selection wrapper approach. The average performance index shows an additional advantage of the proposed method as compared to the conventional procedure in preparing training dataset.

Optimal Sequencing Site of Hydro-Power Stations

At the first stage of a hydro-power survey of a river, it is important to select the optimal hydro-power site. The most important condition to be satisfied is to determine the optimal site where the greatest and most economical amount of hydro-energy can be obtained. This paper proposes a new method in which the optimal arrangement of the hydro-power stations is determined by a computational operation using discrete data at points along the river such as the drainage area, altitude, and distance along the river channel as obtained from topographical maps instead of drawing on engineers’ experiences and the intuitions of experts. The results by this method are then compared with data on existing hydro-power stations and the results planned by expert engineers to show that this new computational method is superior.