Language processing reveals conceptual combination in human infants

Across three eye-tracking experiments, we taught 12-month-olds (N = 60) two novel quantity labels denoting sets of one and two (e.g., “mize” for 1; “padu” for 2). We then showed that they could not only generalize these labels to sets of previously unseen objects, but also combine them with familiar category labels acquired prior to the lab visit (e.g., “ball”, “duck”). Their eye movements revealed adult-like compositional procedures that go beyond serial processing of constituent meanings. These findings indicate that certain combinatorial processes involved in extracting complex linguistic meaning are already available by the end of the first year of life and are ready to support language comprehension.

The working memory costs of a central attentional bottleneck in multitasking

When two (or more) tasks, each requiring a rapid response, are performed at the same time then serial processing may occur at certain processing stages, such as the response selection. There is accumulating evidence that such serial processing involves additional control processes, such as inhibition, switching, and scheduling (termed the active scheduling account). The present study tested whether the existence of serial processing in multitasking leads to a requirement for processes that coordinate processing in this way (active scheduling account) and, furthermore, whether such control processes are linked to the executive functions (EF) of working memory (WM). To test this question, we merged the psychological refractory period (PRP) paradigm with a WM task, creating a complex WM span task. Participants were presented with a sequence of letters to remember, followed by a processing block in which they had to perform either a single task or a dual task, and finally were asked to recall the letters. Results showed that WM performance, i.e. the amount of letters recalled in the correct order, decreased when performing a dual task as compared to performing a single task during the retention interval. Two further experiments supported this finding using manipulations of the dual task difficulty. We conclude that the existence of serial processing in multitasking demands additional control processes (active scheduling) and that these processes are strongly linked to the executive functions of working memory.

Bit Streaming Processing Algorithms for Intelligent Hardware Converters

The need to transfer the primary data conversions close to the sensors, to the endpoints of monitoring systems, as well as in IoT terminal devices makes the development of new approaches to computing and the design of appropriate algorithms relevant. The article shows stream processing algorithms that provide functional transformations of signals presented in bit stream form (single pulse streams, PWM signal streams) and binary codes at the same time. In such algorithms, the computational process is based on discretization, pulse frequency sweep and pulse-width sweep of codes as well as organization of parallel-serial processing. The suggested principles of algorithm organization are based on the fact that the computation is considered not as an event associated with calculation but as a continuous process of a result formation. The transition to algorithmic representations proposed by the authors makes it possible to obtain universal behavioral descriptions, independently of the specific hardware on which their implementation is performed.

Optimasi Algoritma K-Means Clustering dengan Parallel Processing menggunakan Framework R

Parallel processing sering digunakan untuk melakukan optimasi execution time terhadap algoritma data mining. Pada penelitian ini, parallel processing digunakan untuk melakukan optimasi pada algoritma clustering K-Means. Implementasi algoritma K-means dilakukan dengan memanfaatkan package yang tersedia pada framework R. Algoritma K-Means dijalankan secara serial dan parallel. Untuk mendapatkan persentase optimasi, maka dilakukan perbandingan antara execution time pada parallel processing dan execution time pada serial processing. Penelitian ini menggunakan dataset Boston Housing yang umum digunakan pada data mining. Skenario pengujian dibedakan berdasarkan jumlah core dan jumlah centroid. Hasil pengujian menunjukkan bahwa parallel processing untuk tiap skenario memiliki execution time yang lebih kecil daripada serial processing. Optimasi yang dihasilkan cukup signifikan, yakni bernilai 20% hingga 52%. Optimasi tertinggi didapatkan pada jumlah core terbanyak dan jumlah centroid terbesar.

Impact of parallel processing of regional anesthesia with block rooms on resource utilization and clinical outcomes: a systematic review and meta-analysis

Block rooms allow parallel processing of surgical patients with the purported benefits of improving resource utilization and patient outcomes. There is disparity in the literature supporting these suppositions. We aimed to synthesize the evidence base for parallel processing by conducting a systematic review and meta-analysis. A systematic search was undertaken of Medline, Embase, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the National Health Service (NHS) National Institute for Health Research Centre for Reviews and Dissemination database, and Google Scholar for terms relating to regional anesthesia and block rooms. The primary outcome was anesthesia-controlled time (ACT; time from entry of the patient into the operating room (OR) until the start of surgical prep plus surgical closure to exit of patient from the OR). Secondary outcomes of interest included other resource-utilization parameters such as turnover time (TOT; time between the exit of one patient from the OR and the entry of another), time spent in the postanesthesia care unit (PACU), OR throughput, and clinical outcomes such as pain scores, nausea and vomiting, and patient satisfaction. Fifteen studies were included involving 8888 patients, of which 3364 received care using a parallel processing model. Parallel processing reduced ACT by a mean difference (95% CI) of 10.4 min (16.3 to 4.5; p<0.0001), TOT by 16.1 min (27.4 to 4.8; p<0.0001) and PACU stay by 26.6 min (47.1 to 6.1; p=0.01) when compared with serial processing. Moreover, parallel processing increased daily OR throughout by 1.7 cases per day (p<0.0001). Clinical outcomes all favored parallel processing models. All studies showed moderate-to-critical levels of bias. Parallel processing in regional anesthesia appears to reduce the ACT, TOT, PACU time and improved OR throughput when compared with serial processing. PROSPERO CRD42018085184.

A Proof “P≠NP” for P vs. NP Problem by Multiple-Tape Turing-Machine

P vs. NP problem is very important research direction in computation complexity theory. In this paper author, by an engineer&rsquo;s viewpoint, establishes universal multiple-tape Turing-machine and k-homogeneous multiple-tape Turing-machine, and by them we can obtain an unified mathematical model for algorithm-tree, from the unified model for algorithm-tree, we can conclude that computation complexity for serial processing NP problem if under parallel processing sometimes we can obtain P=NP&nbsp; in time-complexity, but that will imply another NP, non-deterministic space-complexity NP, i.e., under serial processing P&ne;NP&nbsp; in space-complexity, and the result is excluded the case of NP problem that there exists a faster algorithm to replace the brute-force algorithm, and hence we can proof that under parallel processing time-complexity is depended on space-complexity, and vice verse, within P vs. NP problem, this point is just the natural property of P vs. NP problem so that &ldquo;P&ne;NP &rdquo;.