... Energy is the fundamental premise of Physics. The term energy is used to describe the scalar quantity that is associate with an object or a system of objects [31]. It is scalar in the sense that it has magnitude without direction. ...

... Energy density is the potential energy per unit volume. The potential energy is the work required to charge the capacitor [31]. This is given by the square of charge multiplied by the capacitance and divided by two. ...

... E is the magnitude of the electrical field and í µí¼€ 0 is the electric constant (8.85 × 10 −12 í µí° ¶ 2 í µí±Ã­ µí±š 2 ) [31]. Energy density is an important metric for determining how much energy is available. ...

  • Kelechi Nwogu

The success of Wireless Sensor Networks is heavily constrained by its reliance on storage technology like batteries, which are a finite resource. Whilst the number of transistors in an IC doubles every 18 months, the energy density of batteries is relatively flat during the same time period. This is a key challenge in leveraging the Internet of Things on trains. The gravity of this problem is increased by an order of magnitude when the network is to be scaled up to hundreds or thousands of nodes. Comprehensive research and development efforts have been devoted to building ultra-low power sensors. These ultra-low power sensors are configured to have very low duty cycle and are practically asleep most of the time. Short duty cycle might extend the battery life, but the energy will inevitably run out. Energy harvesting has emerged as a viable solution to the energy loss issue by ensuring sensors never run out of energy. Though, there could be a significant upfront cost in employing energy harvesting; several studies have shown it takes 24 months or less to break even. Energy harvesters, unlike batteries, are not commonly a one size fits all; some customization is required based on the environment. Mechanical harvesting sources are ideal for the rail environment because this environment has an abundant amount of vibration energy. This thesis focuses on how Energy Harvesting and Storage can be used as the sole power source for the Wireless Sensor Networks that make up the Internet of Things in the railroad industry. It synthesizes the various works carried out in the energy harvesting techniques like solar and piezo, and storage technology like Lithium-ion batteries and Supercapacitors. After introducing the general concept of Internet of Things, Energy Harvesting, and Storage, this document provides an in-depth analysis of the data gathered during this research. The data was used to determine sensor node power consumption when arranged in a linear topology like the train, available ambient energy on the train, and optimal energy harvesting sources for the railroad. Adviser: Hamid Sharif

... These values correspond to 330 Ω internal resistance; same for both cells having similar substrate and similar graphite electrodes. The higher OCV value conirms that an MFC that is connected with an external resistance comparable to its internal resistance will produce maximum power [9,11]. ...

... The internal resistance is one of the major characteristics of a MFC, in accordance with the theorem of maximum power delivered by an electromotive force. An MFC connected with an external resistance equals to its internal resistance will give a maximum power output [10,11]. From Figure 27 the peaks occurred at 118 and 79 mW/m 2 for zinc/copper and graphite/graphite systems respectively. ...

... Rashedi et al. [14] proposed an optimization algorithm based on the gravity, which is one of the fundamental interactions in nature. Their approach, called Gravitational Search Algorithm, models each possible solution as a particle in the universe, which interacts with other ones according to the Newton's law of universal gravitation [48]. Let p i be a particle in a universe, and x i ∈ R n and v i ∈ R n its position and velocity, respectively. ...

We propose a nature-inspired approach to estimate the probability density function (pdf) used for data clustering based on the optimum-path forest algorithm (OPFC). OPFC interprets a dataset as a graph, whose nodes are the samples and each sample is connected to its k-nearest neighbors in a given feature space (a k-nn graph). The nodes of the graph are weighted by their pdf values and the pdf is computed based on the distances between the samples and their k-nearest neighbors. Once the k-nn graph is defined, OPFC finds one sample (root) at each maximum of the pdf and propagates one optimum-path tree (cluster) from each root to the remaining samples of its dome. Clustering effectiveness will depend on the pdf estimation, and the proposed approach efficiently computes the best value of k for a given application. We validate our approach in the context of intrusion detection in computer networks. First, we compare OPFC with data clustering based on k-means, and self-organization maps. Second, we evaluate several metaheuristic techniques to find the best value of k.

... The easiest explanation of motion is to use Newton's Law. Newton's first law explains the inertia of an object (Halliday et al., 2010). If an object initially has velocity v, then the speed will be constant when there is no force acting on the object. ...

Linear air track is often used in physics learning for linear motion experiments because it can reduce friction between objects with trajectories. However, the use of air tracks for motion experiments in schools often does not care about aspects of air drag, so the purpose of this study is to calculate the air friction contained in the air track and as an offer of enrichment experiments at senior high school. The research method used is an experimental method that uses a set of air track experimental devices consisting of trajectors, carts, blower, and time counters with light sensors. Cart objects with a mass of 120.02 gram is given the initial velocity variation 12.272 cm/s, 16.286 cm/s and 24.599 cm/s. Then the time recorded when the cart crosses the distance of 10 cm to 110 cm at intervals of 10 cm. This experiment is conducted in the Integrated Science Laboratory, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang. The second Newton law has been derived to obtain a special exponential function, so the relation between distance and time is obtained. The non-linear relation between distance and time shows the effect of air drag. Then, fitting the graph of the distance and time relation so that the air drag constants obtained are (10.6 ± 0.1) gram/s, (10.6 ± 0.2) gram/s, and (11.1 ± 0.2) gram/s. The results of the air drag constants obtained can be additional data as a factor affecting experiments using linear air track and can be enrichment experiments at senior high school laboratory.

... Nilai g berkurang dengan naiknya ketingian objek. (Halliday, Resnick, & Walker, 2008). ...

... The idea is that rules gravity is concerned with the fact that an object with mass attracts one another. One of the most accepted theories is the Newton's law of universal gravitation, which says that " every massive particle in the universe attracts other massive one with a force that is directly proportional to the product of their masses and inversely proportional to the square of the distance between them " [19] (8) ...

Although nontechnical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy and to characterize possible illegal consumers has not attracted much attention in this context. In this paper, we focus on this problem by reviewing three evolutionary-based techniques for feature selection, and we also introduce one of them in this context. The results demonstrated that selecting the most representative features can improve a lot of the classification accuracy of possible frauds in datasets composed by industrial and commercial profiles.

... Rashedi et al. [14] proposed an optimization algorithm based on the gravity, which is one of the fundamental interactions in nature. Their approach, called Gravitational Search Algorithm, models each possible solution as a particle in the universe, which interacts with other ones according to the Newton's law of universal gravitation [48]. Let p i be a particle in a universe, and x i ∈ R n and v i ∈ R n its position and velocity, respectively. ...

Although hyperspectral images acquired by on-board satellites provide information from a wide range of wavelengths in the spectrum, the obtained information is usually highly correlated. This article proposes a novel framework to reduce the computation cost for large amount of data based on the efficiency of the Optimum-Path Forest classifier and the power of meta-heuristic algorithms to solve combinatorial opti-mizations. Simulations on two public datasets have shown that the proposed framework can indeed improve the effectiveness of the Optimum-Path Forest and considerably reduce data storage costs.

  • Dady Sulaiman
  • Wibowo Romadhoni
  • Arlina Arlina

Electrical energy is one of the primer facilities used in every activity. Almost all the existing facilities use electricity. This is inversely proportional to the depleting energy source. The solution to this problem is to replace fossil fuels with renewable energy sources. Renewable energy is a source of energy that can be recycled and does not damage the environment. One type of renewable energy is to use the electrolysis method. Electrolysis Method is one of the renewable energy sources. This method uses electrolyte solution which can be found in sour and runny fruit such as lemon (Citrus Limon L.) and Wuluh Star fruit (Averrhoa bilimbi). The study was conducted in a laboratory by mixing the results of the juice of the two fruits with different compositions. The mixes are placed in the arcs (a mixture container to test the electrical properties) and then tested using a multimeter every 2 hours for 24 hours. The results are described in graphical form. The average power of each mixture is, C1 = 2.2mW, C2 = 4.7mW, and C3 = 8.5 mW and based on the graph, each mixture has decreased voltage and current. Even so among the three mixtures, the third mixture has a better electrical power value than the other two mixes. This shows that the higher the acidity of a solution the higher the electricity produced.

  • Sergio Colafrancesco Sergio Colafrancesco

The recent X-ray, optical and radio observations of galaxy clusters indicate that the atmospheres of these cosmic structures consist of a complex structure of thermal (hot and warm) and non-thermal (with different origin and spectra) distribution of electrons (and protons) which is, therefore, far from its modelling as a single, thermal leptonic gas. This evidence requires to go beyond the simple, standard lore of the SZ effect. This task is challenging for both the theoretical aspects of their modelling and for the experimental goals to be achieved, but it will return a large amount of physical information by using the SZ effect as a unique tool for astro-particle and cosmology.

The force of labour is the result of complex factors and their interactions. A complete understanding of the mechanisms that serve to control uterine contractility and human labour is hindered by the fact that human labour has redundant mechanisms to enhance survivability. However, these complexities do not obviate the need for objective investigation. Such studies have provided a growing understanding of the forces of labour and lead to changes in clinical management. We hope there will be more in the future.

Intrusion detection systems that make use of artificial intelligence techniques in order to improve effectiveness have been actively pursued in the last decade. However, their complexity to learn new attacks has become very expensive, making them inviable for a real time retraining. In order to overcome such limitations, we have introduced a new pattern recognition technique called optimum-path forest (OPF) to this task. Our proposal is composed of three main contributions: to apply OPF for intrusion detection, to identify redundancy in some public datasets and also to perform feature selection over them. The experiments have been carried out on three datasets aiming to compare OPF against Support Vector Machines, Self Organizing Maps and a Bayesian classifier. We have showed that OPF has been the fastest classifier and the always one with the top results. Thus, it can be a suitable tool to detect intrusions on computer networks, as well as to allow the algorithm to learn new attacks faster than other techniques.

Besides optimizing classifier predictive performance and addressing the curse of the dimensionality problem, feature selection techniques support a classification model as simple as possible. In this paper, we present a wrapper feature selection approach based on Bat Algorithm (BA) and Optimum-Path Forest (OPF), in which we model the problem of feature selection as an binary-based optimization technique, guided by BA using the OPF accuracy over a validating set as the fitness function to be maximized. Moreover, we present a methodology to better estimate the quality of the reduced feature set. Experiments conducted over six public datasets demonstrated that the proposed approach provides statistically significant more compact sets and, in some cases, it can indeed improve the classification effectiveness.

Social influence has been widely studied in areas of viral marketing, information diffusion and health care. Currently, most influence models only deal with a single influence without the interference of other influences. Also, the influence spreading in previous models must be triggered by individuals who have been activated by the influence. In this paper, we argue that it is the attraction from a specific influence makes an individual choose to spread it among multiple influences. Inspired by charged system theory in physics, a new influence model is proposed, considering individual features and social structure features. It also gives a natural description about how individuals make decisions among multiple influences. Then a novel algorithm based on this model is provided to predict human behavior. Extensive experiments on three real-world datasets demonstrate that our model and algorithm statistically outperform the state-of-the-art methods in terms of prediction accuracy.

  • Gregory Mack
  • Terry Walker

The effect of the amount of helium-4 produced from Big Bang nucleosynthesis on the power spectrum of the cosmic microwave background radiation (CMBR) is explored for two reasons: to see if the mass fraction of helium-4 produced during the events following the Big Bang has an effect on the power spectrum of the CMBR, and if a constraint can be placed on this amount. This is done through the help of a computer program called CMBFAST, which computes power spectra of models of the CMBR with varying parameters. The effect was indeed apparent in graphs produced from values taken from CMBFAST. Drawing randomly on numbers from a Gaussian distribution of the parameters that were taken to vary in the program, bands of power spectra for a specific value of the mass fraction of helium-4 were produced, and a constraint could be placed on the amount of helium-4 present in the early universe. An upper limit of eighty percent helium-4 by mass was confidently found to exist through computer modeling, while a lower limit was inconclusive.

  • Marian W Radny Marian W Radny
  • Aime B Duval

A computer-aid, online tutorial/assessment scheme based on an eGrade (Wiley & Sons) software package designed and implemented in the introductory physics courses at the University of Newcastle (Australia) is described and evaluated. It is shown that the designed approach enhances student's satisfaction and performance, and represents a valuable experience in developing a consistent tutorial/assessment online supporting scheme for large-class introductory physics courses.

This study aimed to determine the effect of 0.2 mT magnetic field exposure on metals (Al, Pb, Cd and Cu) containing media, to proteolytic index of Bacillus sp., protease activity and cell morphology of Bacillus sp. This study consisted of three stages. The first stage was a proteolytic test on solid media containing milk. The second stage was the production of protease enzymes in liquid media. The third stage was Scanning Electron Microscopy (SEM) analysis on a culture treatment known as protease enzyme activity. The results showed that the largest proteolytic index on CuCl2 metal ion content of magnetic 0.2 mT magnetic field for 10 minutes increased the value of the largest proteolytic index was 4.33. While in the ion solution containing CdCl2, Bacillus sp. culture did not grow. In the production of enzymes in the liquid medium, the highest enzyme activity (0.140 U/ ml) was produced on a medium containing AlCl3 and exposed to magnetic fields. The SEM analysis also proved that the supplementation of AlCl3 increased cell length by 2.38 and 2.78 times longer than control without magnetic field and for magnet field, respectivelly.

  • Mansour Sheikhan Mansour Sheikhan

Suprasegmental (prosody) features of discourse provide a vehicle by which speakers reflect their mental purposes to listeners. Generating suitable prosody information is critical to expressing messages and improving the intelligibility and naturalness of synthetic speech. Generic prosody generators should provide information about pitch frequency (F 0) contours, energy levels, word durations, and inter-word pause durations for speech synthesizers. The present study used a recurrent neural network (RNN) for prosody generation. The inputs of this RNN were word-level and syllable-level linguistic features. To provide data efficiently for the RNN-based prosody generator in the training, validation, and test phases, automatic segmentation and labeling of phonemes were performed. The number of inputs to the RNN was reduced by employing a binary gravitational search algorithm (BGSA) for feature selection (FS). The proposed prosody generator provided 12 output prosodic parameters for the current syllable for representing pitch contour, log-energy contour, inter-syllable pause duration, duration of syllable, duration of the vowel in the syllable, and vowel onset time. Experimental results demonstrated the success of the RNN-based prosody generator in synthesizing the six prosodic elements with acceptable root mean square error (RMSE). By using a BGSA-based FS unit, a lighter neural model was achieved with a 53 % reduction in the number of weight connections, producing RMSEs with acceptable degradation over the no-FS unit prosody generator. The performance of the BGSA-based FS method was compared with a binary particle swarm optimization (BPSO) algorithm, and the BGSA showed slightly better results. A modified mean opinion score scale was used to evaluate the intelligibility and naturalness of synthesized speech using the proposed method.

In classification problems, it is common to find datasets with a large amount of features, some of theses features may be considered as noisy. In this context, one of the most used strategies to deal with this problem is to perform a feature selection process in order to build a subset of features that can better represents the dataset. As feature selection can be modeled as an optimization problem, several studies have to attempted to use nature-inspired optimization techniques due to their large generalization capabilities. In this chapter, we use the Cuckoo Search (CS) algorithm in the context of feature selection tasks. For this purpose, we present a binary version of the Cuckoo Search, namely BCS, as well as we evaluate it with different transfer functions that map continuous solutions to binary ones. Additionally, the Optimum-Path Forest classifier accuracy is used as the fitness function. We conducted simulations comparing BCS with binary versions of the Bat Algorithm, Firefly Algorithm and Particle Swarm Optimization. BCS has obtained reasonable results when we consider the compared techniques for feature selection purposes.

The sintering behavior of commercially available MgAl2O4 spinel was investigated under DC electric field in a range of 0 and 1000 V/cm. Flash-sintering results in densification close to theoretical density at 1410°C under the DC field of 1000 V/cm, in comparison to the higher sintering temperature of 1650°C in case of conventional sintering. It was observed that the fields less than 750 V/cm had no significant effect on the densification behavior. An abrupt increase in power dissipation was observed corresponding to the occurrence of the flash event. A significant enhancement in grain size was observed in case of flash-sintered dense spinel samples. The gradual increase in the specimen conductivity observed in the electric field-assisted sintering (FAST) regime led to Joule heating within the specimen. The increased specimen temperature triggered further increment of current and Joule heating, resulting in the immediate densification.

  • Niyazi Özgür Bezgin Niyazi Özgür Bezgin

This study applies a new concept, a new analytical method and presents a new analytical equation developed by the author to estimate the vertical impact forces of train wheels imposed on railway tracks along defective track lengths where there is a vertical irregularity in the track profile. The new method bases on the principle of conservation of energy, rules of kinematics and a new concept of impact reduction factor. This paper begins by an overview of some of the existing empirical and advanced analytical methods that estimate the vertical impact forces applied on the railway track by the wheels of a moving train. The paper then reintroduces the proposed new method and the new equation and provides an in-depth example of its application. The paper concludes by comparing the results estimated by the proposed method with the estimates of some of the existing semi-empirical equations.

Morphologic studies suggest dramatic, asymmetric uterine growth during pregnancy that is caused by muscle cell hypertrophy. This growth is most marked at the fundus. Our objective was to evaluate sonographically the in vivo changes in myometrial thickness during active labor, second-stage labor, and after delivery. Abdominal ultrasound scans were performed on 52 term pregnant women to investigate the dynamic changes in myometrial thickness during the active and second stages of labor and immediately after delivery. Twenty-six women (mean +/- SEM gestational age, 39.09 +/- 0.3 weeks) were in active labor (cervical dilatation >4 cm with regular uterine contractions). An additional 26 nonlaboring women (gestational age, 39.8 +/- 0.2 weeks) provided control measurements. The myometrium was defined sonographically as the echo homogeneous layer between the serosa and the decidua. Myometrial thickness was measured at the low segment and mid anterior, fundal, and posterior uterine walls by the same observer. Myometrial thickness was also measured during uterine contractions and after artificial rupture of the amniotic membranes. All laboring women had uncomplicated labor patterns when studied and were delivered spontaneously. The myometrium was significantly thinner during active labor compared with nonlabor at each site studied: midanterior (mean [+/-SEM] myometrial thickness, 5.8 +/- 0.27 vs 8.83 +/- 0.51 mm; t test, P <.001), fundus (mean myometrial thickness, 6.78 +/- 0.32 vs 8.49 +/- 0.35 mm; P =.0015), and posterior (mean myometrial thickness, 6.22 +/- 0.34 vs 8.12 +/- 0.30 mm; P <.001). However, myometrial thickness did not differ among sites within the two groups. The thickness of the low segment was not affected by labor status (nonlabor, 4.68 +/- 0.48 vs labor, 4.66 +/- 0.37 mm; P =.97). Similarly, the myometrial thickness of the anterior uterine wall was unaffected by contractions (no contractions, 5.56 +/- 0.2 vs contractions, 5.68 +/- 0.22 mm; t test, P =.654). There was no change in myometrial thickness measured immediately before and after rupture of the amniotic membranes, despite a significant decrease of the amniotic fluid index. There was significant thickening of the anterior and fundal myometrium during the second stage of labor after the fetal head descended to +3 station by digital examination (anterior, 12.99 +/- 0.60 vs 5.8 +/- 0.27 mm; t test, P <.001; fundus, 10.61 +/- 1.63 vs 6.78 +/- 0.32 mm; t test, P =.04). Valsalva maneuver (pushing) during contractions did not affect myometrial thickness at the fundus (between contractions, 10.61 +/- 1.63 vs pushing, 10.76 +/- 1.95 mm; t test, P =.99). Immediately after delivery, the myometrial thickness at the placental insertion site was the thinnest. After completion of the third stage of labor, the uterine fundus remained significantly thinner than the anterior and posterior walls (fundus, 27.37 +/- 3.5 mm vs anterior, 40.94 +/- 3.5 vs posterior, 42.34 +/- 2.44; one-way analysis of variance, P =.02). There is significant and widespread thinning of the myometrium during active labor. Descent of the fetal head during the second stage of labor is associated with a significant relative thickening of the anterior and fundal myometrium. After delivery, the relationship reverses. These findings suggest the directionality of the expulsive force vectors (fundal dominance) is not determined by asymmetric myometrial growth but, rather, may be a function of increased "myometrial mass" that results from increased surface area at the fundus.

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