Dynamical Behavior of a New Chaotic System with One Stable Equilibrium

This paper reports a simple three-dimensional autonomous system with a single stable node equilibrium. The system has a constant controller which adjusts the dynamic of the system. It is revealed that the system exhibits both chaotic and non-chaotic dynamics. Moreover, chaotic or periodic attractors coexist with a single stable equilibrium for some control parameter based on initial conditions. The system dynamics are studied by analyzing bifurcation diagrams, Lyapunov exponents, and basins of attractions. Beyond a fixed-point analysis, a new analysis known as connecting curves is provided. These curves are one-dimensional sets of the points that are more informative than fixed points. These curves are the skeleton of the system, which shows the direction of flow evolution.

Pengukuran Kualitas Perangkat Lunak Menggunakan Metode Function Analysis

Penelitian ini dilakukan untuk mengukur kualitas dari suatu aplikasi Point of Sales (POS) yang dapat mendukung proses transaksi pada bisnis. Aplikasi yang akan diteliti adalah aplikasi BukuKas yang merupakan aplikasi POS dengan pengguna yang cukup banyak di Indonesia. Pengukuran akan menentukan apakah BukuKas layak dipakai atau tidak. Metode dalam pengukuran ini akan menggunakan Function Point Analysis (FPA). FPA merupakan metode untuk mendapatkan ukuran biaya, durasi, dan jumlah sumber daya yang diperlukan oleh sebuah proyek perangkat lunak dan dapat dilakukan pada setiap tahap pengembangan perangkat lunak. Dari hasil penelitian, ditemukan bahwa aplikasi BukuKas merupakan aplikasi POS yang memiliki fitur yang cukup lengkap dan berkualitas, sehingga memungkinkan bahwa aplikasi ini dapat membantu pengguna dalam menjalankan usaha toko maupun UMKM. Hal ini telah dibuktikan dari Function Point yang dilakukan dan aplikasi ini mendapat skor tinggi sebesar 118,08, yang mana mplikasi ini mendapat presikat aplikasi yang mudah untuk digunakan dan cenderung kompleks, tentunya dari perhitungan ini dapat dikembangkan menjadi biaya perhitungan pembangunan aplikasi BukuKas.

Ultrasonic guided wave-based debond identification in a GFRP plate with L-stiffener

This paper presents a robust assessment of debond in a glass fibre-reinforced polymer composite structure with L-stiffener attachment. Towards this, the ultrasonic guided wave (GW) propagation based laboratory experiments have been carried out on a stiffened composite panel with piezoelectric transducers (PZT) for the excitation of GWs and a scanning laser Doppler vibrometer (SLDV) for sensing the GW propagation. To study the changes caused by the stiffener and debond a signal processing based multi-point analysis has been carried out. The proposed methodology consists of two steps. Step 1 using the full wavefield root mean square energy map-based approach to check the presence of debond. Step 2 using point-wise measurements to study debond localization and size estimation using a baseline free signal coefficient difference algorithm (SCDA). The proposed processing approaches are applied for an in-depth analysis of the experimental signals that provide information about the interaction of GWs with stiffener and debond. The mentioned approaches take advantage of the asymmetry caused by the damage. For the applied SCDA methodology there is no need for full-wavefield measurements, healthy case measurements, as only a few measurement points can be enough for the assessment of stiffener debond in such structures.

Phase profile of the wave function of canonical tensor model and emergence of large space–times

In this paper, to understand space–time dynamics in the canonical tensor model of quantum gravity for the positive cosmological constant case, we analytically and numerically study the phase profile of its exact wave function in a coordinate representation, instead of the momentum representation analyzed so far. A saddle point analysis shows that Lie group symmetric space–times are strongly favored due to abundance of continuously existing saddle points, giving an emergent fluid picture. The phase profile suggests that spatial sizes grow in “time,” where sizes are measured by the tensor-geometry correspondence previously introduced using tensor rank decomposition. Monte Carlo simulations are also performed for a few small N cases by applying a re-weighting procedure to an oscillatory integral which expresses the wave function. The results agree well with the saddle point analysis, but the phase profile is subject to disturbances in a large space–time region, suggesting existence of light modes there and motivating future computations of primordial fluctuations from the perspective of canonical tensor model.

When and Why Did Human Brains Decrease in Size? A New Change-Point Analysis and Insights From Brain Evolution in Ants

Human brain size nearly quadrupled in the six million years since Homo last shared a common ancestor with chimpanzees, but human brains are thought to have decreased in volume since the end of the last Ice Age. The timing and reason for this decrease is enigmatic. Here we use change-point analysis to estimate the timing of changes in the rate of hominin brain evolution. We find that hominin brains experienced positive rate changes at 2.1 and 1.5 million years ago, coincident with the early evolution of Homo and technological innovations evident in the archeological record. But we also find that human brain size reduction was surprisingly recent, occurring in the last 3,000 years. Our dating does not support hypotheses concerning brain size reduction as a by-product of body size reduction, a result of a shift to an agricultural diet, or a consequence of self-domestication. We suggest our analysis supports the hypothesis that the recent decrease in brain size may instead result from the externalization of knowledge and advantages of group-level decision-making due in part to the advent of social systems of distributed cognition and the storage and sharing of information. Humans live in social groups in which multiple brains contribute to the emergence of collective intelligence. Although difficult to study in the deep history of Homo, the impacts of group size, social organization, collective intelligence and other potential selective forces on brain evolution can be elucidated using ants as models. The remarkable ecological diversity of ants and their species richness encompasses forms convergent in aspects of human sociality, including large group size, agrarian life histories, division of labor, and collective cognition. Ants provide a wide range of social systems to generate and test hypotheses concerning brain size enlargement or reduction and aid in interpreting patterns of brain evolution identified in humans. Although humans and ants represent very different routes in social and cognitive evolution, the insights ants offer can broadly inform us of the selective forces that influence brain size.