Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Network based on GLCM, and CIE L*a*b* Color Space to Classify Tomatoes Maturity

Tomato (Lycopersicum commune) is one of the fruits that can be consumed directly or processed into food or drinks. In the harvesting season, tomatoes will be picked and sorted into different class depending on its size, shape, and color. The quality and the taste of tomatoes fruit depends on the maturity level of this fruit. There is some product that used a different level of tomato maturity. Therefore it is necessary to classify the ripeness of this fruit. The use of information technology such as computer vision can help the farmer to classify tomato based on maturity level. To be able to determine the ripeness of tomatoes from an image, a computer needs to identify the right parameters to determine the maturity of this fruit. The texture and color on the surface of tomatoes is a feature that easily recognized in determining the maturity of tomatoes. Therefore this research proposed the combination of GLCM texture extraction and CIE L*a*b* color space and also Backpropagation neural network (BPNN) to classify tomatoes maturity. GLCM feature extraction consisted of Contrast, Correlation, Energi, Homogeneity, and Entropy. GLCM was implemented in each RGB color layer, then the average of CIE L*a*b* was calculated. From 75 train set and 25 test set, BPNN model can classified tomatoes maturity with accuracy 100% and average accuracy 95.46%.
Reliability Assessment for AC/DC Hybrid Distribution Network With High Penetration of Renewable Energy

Recently, the AC/DC hybrid distribution network has become a general trend in energy research. To accommodate the addition of renewable energy, this paper proposes a reliability assessment approach for AC/DC hybrid distribution network considering the new features introduced by the DC distribution technique. First, the probability models of renewable generations and loads are established. Second, the control modes of the voltage source converter (VSC) yielding to different fault scenarios are modeled based on its operating characteristics. Thereafter, an optimal load shedding model that considers the control modes of the VSC is developed, and it can be solved using a second-order cone algorithm. Finally, a reliability assessment method for the AC/DC hybrid distribution network is proposed that is based on the nonsequential Monte Carlo method. Case studies based on a modified AC/DC distribution network are applied to verify the effectiveness of the proposed method. The operational characteristics and reliability performance of the AC/DC distribution network with high integration of renewable energy are demonstrated by comparing it to a corresponding AC distribution network.
Evaluation of Vehicles’ Platooning on Expressways Based on V2X

Vehicles’ platooning and V2X(vehicle to everything) communication technologies provide new ideas for solving expressways congestion, improving traffic safety, reducing energy consumption and environmental pollution, which has recently drawn an increasing attention from governments, vehicle manufacturers, and researchers. Vehicles’ platooning refers to a linear platoon of vehicles that travel along the same path with a small space headway. When V2X technology is applied into vehicles’ platooning, drivers will drive on the same path with a more reasonable following behaviors, including driving speed and following distance, which will improve traffic efficiency and safety in theory. This study firstly models the driver’s following behavior based on V2X with intelligent driver model (IDM), which calibrated by data which meets the characteristics of data in the connected environment. Considering the different traffic loads, traffic management strategy and the fact that the full market penetration of connected vehicle (CV) might not be accomplished recently, the research will change the traffic volume, the penetration rate of CV and management strategies to evaluate vehicles’ platooning in connected environment. The assessment will be evaluated in terms of safety and traffic efficiency.
Annotated Classic From B Cells to the World, NF-kB Takes the Stage

We are pleased to present a series of Annotated Classics celebrating 40 years of exciting biology in the pages of Cell. This installment revisits “Inducibility of k Immunoglobulin Enhancer-Binding Protein NF-kB by a Posttranslational Mechanism” by Ranjan Sen and David Baltimore. Here, Sankar Ghosh comments on the work that established the key defining properties of the transcription factor NF-kB—identified months earlier in another classic Cell paper—and made it into such an important and central regulatory molecule in biology.
FAST ALGORITHM TO LEAKAGE POWER REDUCTION BY INPUT VECTOR CONTROL 1Dionatan

Power consumption is a crucial parameter in CMOS circuit design. Leakage power is no longer a negligible component in low power circuits design due to the aggressive scaling of CMOS devices. Input vector control is an effective method to reduce leakage power when a circuit is in standby mode. It tries to find a vector that minimizes leakage power to be statically applied to the primary inputs of a circuit. The power consumption in CMOS circuits is evaluated in this work and a fast algorithm to reduce leakage power by input vector control is proposed. Experimental results on combinational circuits of ISCAS’85 benchmarks show this algorithm can accelerate calculation up to 25 times when compared to random vector technique and provides better results.
Calcium isotope evidence for environmental variability before and across the Cretaceous-Paleogene mass extinction

Carbon dioxide release during Deccan Traps volcanism and the Chicxulub impact likely contributed to the Cretaceous-Paleogene (K-Pg) mass extinction; however, the intensity and duration of CO2 input differed between the two events. Large and rapid addition of CO2 to seawater causes transient decreases in pH, [CO32–], and carbonate mineral saturation states. Compensating mechanisms, such as dissolution of seafloor sediment, reduced biomineralization, and silicate weathering, mitigate these effects by increasing the same parameters. The calcium isotope ratios (δ44/40Ca) of seawater and marine carbonates are hypothesized to respond to these perturbations through weathering/carbonate deposition flux imbalances and/or changes in fractionation between carbonate minerals and seawater. We used a high-precision thermal ionization mass spectrometry method to measure δ44/40Ca values of aragonitic bivalve and gastropod mollusk shells from the K-Pg interval of the López de Bertodano Formation on Seymour Island, Antarctica. Well-preserved shells spanning the late Maastrichtian (ca. 67 Ma) to early Danian (ca. 65.5 Ma) have δ44/40Ca values ranging from −1.89‰ to −1.57‰ (seawater [sw]). Shifts in δ44/40Ca inversely correlate with sedimentological indicators of saturation state. A negative excursion begins before and continues across the K-Pg boundary. According to a simple mass-balance model, neither input/output flux imbalances nor change in the globally integrated bulk carbonate fractionation factor can produce variations in seawater δ44/40Ca sufficient to explain the measured trends. The data are consistent with a dynamic molluscan Ca isotope fractionation factor sensitive to the carbonate geochemistry of seawater. The K-Pg extinction appears to have occurred during a period of carbonate saturation state variability caused by Deccan volcanism.
1 Exactly Verifying a Single Tree in Linear Time Although computing

We study the robustness verification problem for tree based models, including decision trees, random forests (RFs) and gradient boosted decision trees (GBDTs). Formal robustness verification of decision tree ensembles involves finding the exact minimal adversarial perturbation or a guaranteed lower bound of it. Existing approaches find the minimal adversarial perturbation by a mixed integer linear programming (MILP) problem, which takes exponential time so is impractical for large ensembles. Although this verification problem is NP-complete in general, we give a more precise complexity characterization. We show that there is a simple linear time algorithm for verifying a single tree, and for tree ensembles the verification problem can be cast as a max-clique problem on a multi-partite graph with bounded boxicity. For low dimensional problems when boxicity can be viewed as constant, this reformulation leads to a polynomial time algorithm. For general problems, by exploiting the boxicity of the graph, we develop an efficient multi-level verification algorithm that can give tight lower bounds on robustness of decision tree ensembles, while allowing iterative improvement and any-time termination. On RF/GBDT models trained on 10 datasets, our algorithm is hundreds of times faster than the previous approach that requires solving MILPs, and is able to give tight robustness verification bounds on large GBDTs with hundreds of deep trees.
3-Phase Line-Interactive Dynamic Voltage Restorer with Hybrid Sag Detection Algorithm

This paper describes the development of a 3phase line-interactive DVR with a hybrid sag detecti on algorithm. The developed detection algorithm has a hybrid structure composed of an instantaneous detector and the RMSvariation detectors. The source voltage passes thro ug the sliding-window DFT and RMS calculator, and the instantaneous sag detection part. If instantaneous sag is detected, the RMS variation detector-1 is selected t o calculate the RMS variation. The RMS variation detector-2 is se lect d when the instantaneous sag occurs under the operati on of the RMS variation detector-1. The feasibility of propose d algorithm was verified through computer simulations and exper im ntal works with reference to a prototype of line-interac tive DVR with 3kVA rating. The line-interactive DVR with propsed algorithm can compensate the input voltage sag and interruption within 2ms delay. The developed DVR can effectively compensate the voltage sag or interruption for the sensitive load, such as computer, communication equipment, an d automation equipment.
Arxiv 20150413021900: Shearer's PP & hard-sphere in 1D

We revisit the smallest non-physical singularity of the hard-sphere model in one dimension, also known as Tonks gas. We give an explicit expression of the free energy and reduced correlations at negative real fugacity and elaborate the nature of the singularity: the free energy is right-continuous, but its derivative diverges. We derive these results in several novel ways: First, by scaling up the discrete solution. Second, by an inductive argument on the partition function à la Dobrushin. Third, by a perfect cluster expansion counting the Penrose trees in the Mayer expansion perfectly. Fourth, by an explicit construction of Shearer’s point process, the unique R-dependent point process with an R-hard-core. The last connection yields explicit and optimal lower bounds on the avoidance function of R-dependent point processes on the real line.
Design and Evaluation of a Method for Enhancing Robustness of MCMC-Based Autonomous Decentralized Mechanism for VM Assignment Problem

Autonomous Decentralized Mechanism (ADM) is actively discussed to realize a scalable control scheme for large-scale is wide-area systems. The previous work has proposed the Markov Chain Monte Carlo (MCMC)-based ADM for indirectly controlling the entire system, but has not fully discussed the impact of environmental fluctuation on its robustness. In this paper, we propose a method to enhance the robustness of the MCMC-based ADM against severe environmental fluctuations. In the proposed method, each node adjusts the control parameter of the MCMC-based ADM to absorb environmental fluctuations. In addition, we apply the proposed method to virtual machine (VM) assignment problem in data centers. Through simulation experiment, we clarify the effectiveness of the proposed method for severe environmental fluctuation. Keywords -Autonomous Decentralized Mechanism, Large-Scale and Wide-Area System, Markov Chain Monte Carlo, Robustness, Environmental Fluctuation, Virtual Machine Placement Problem
Diagnosing Failures in the Mobile Network Operation using Ensemble of Classifiers

—Mobile networks combine different communication technologies sharing the same infrastructure. Although each technology accomplishes different networking requirements, it also hinders the network operation. Standard network monitoring tools often fail to detect service faults due to the multitude of monitored parameters of hardware from different vendors. To overcome this issue, we propose the Advanced Infrastructure for fault Diagnosis in Mobile Networks (AID-MN). AID-MN relies on applying ensemble of classiﬁers, a machine-learning technique, on fault postmortem data to automatically recognize the causes of service faults. We evaluate the performance of AID-MN in a case study of an operational access mobile network aiming at diagnosing intermittent 2G service failures. The results show that AID-MN assists the detection of the fault cause and supports to offer a feasible solution to the fault in a fast and effective way. Any service that have information about your status can be used with our solution.
Communication Challenges and Solutions between Heterogeneous Industrial IoT Systems

Industrial automation systems require communication technologies with high availability, high security and low latency. Accordingly, the current article addresses industrial-specific communication challenges, presenting some of the relevant solutions. In order to prove the usability of the presented technologies with sound results, this paper utilises a primarily Industrial IoT(IIoT) solution, the Arrowhead Framework, to experiment with communication capabilities between different IIoT clouds. The research is limited to three technologies from the LTE UE categories: Cat 3, Cat Ml and NB-IoT.The novelty of this paper is that it provides a set of experimental studies on applying different mobile networking technologies to support IIoT applications. The studies are based on our current, real-life measurements.
Bid-Ask Spread, Strike Prices,

In empirically deriving risk-neutral densities (RND) from option prices, one of the key assumptions that the strike prices should be continuous over the entire spectrum of non-negative real numbers, is not met due to market trading mechanism. This study looks at how this failure affects the empirical RND. It also tests the possible impact that bid-ask spread has on the empirical RND. With Heston (1993) option pricing model of stochastic volatility as a mapping tool between option prices and risk-neutral price distributions, and realistic assumptions of option specifications, simulation results show that RND are less stable and realiable when there are a limited number of different strike prices, even less so when bid-ask spread is incorporated into option prices.
Physical activity and fitness measures in New Zealand : a study of validation and correlation with cardiovascular risk factors

i ACKNOWLEDGEMENTS . ii TABLE OF CONTENTS . iii LIST OF TABLES.xvi LIST OF FIGURES. xvii LIST OF ABBREVIATIONS . xvii CHAPTER 1: INTRODUCTION AND BACKGROUND 1.1 PHYSICAL ACTIVITY.1 1.1.1 Physical Activity and Health . 1 1.1.2 What is Physical Activity? 1 Physical Activity Dimensions.2 Physical Activity Contexts . 2 1.1.3 Measurement of Physical Activity.3 Physical Activity Questionnaires.3 Objective Measures of Physical Activity . 4 1.2 CARDIORESPIRATORY FITNESS . 5 1.2. 1 Cardiorespiratory Fitness and Health . 5 1.2. 2 Assessment of Cardiorespiratory Fitness.5 1.2. 3 Correlates of Cardiorespiratory Fitness . 6 1.3 PHYSICAL ACTIVITY LEVELS IN NEW ZEALAND . 7 1.3. 1 Creation of New Zealand Physical Activity Questionnaires . 7 1.3. 2 Validation of New Zealand Physical Activity Questionnaires . 8 1.3. 3 Creation of a New Zealand Compendium of Physical Activities.8 1.3. 4 Cardioprotective Roles of Cardiorespiratory Fitness and Physical Activity . 9 1.4 CHAPTER OUTLINE OF THESIS AND AUTHOR’S ROLE . 11 1.4. 1 Author’s Involvement.5
Microglia: the physiology and its role in the aging brain

Microglia are resident immune cells of the CNS and have a distinct phenotype in the healthy brain, induced by ‘off’ signals expressed by neurons and astrocytes. In reaction to disturbance in the CNS, microglia change their morphology and phenotype towards a beneficial or detrimental state, thereby regulating the disease pathology. Microglial activation is very diverse and dynamic, regulated by ‘on’ signals, also released by neurons and astrocytes. Normal aging of the brain is accompanied with increased microglial activation and enlarged microglial subtypes, increasing the risk of neurogenerative diseases. A better comprehension of microglial behavior will be necessary in understanding the pathogenesis of ischemia and neurogenerative diseases, in order to develop effective therapies.
Perceptions Of Accountants And Prospective Accountants About Islamic Accounting Based On The Characteristics And Objectives Of Islamic Accounting

This study aimed to determine the perceptions of accountants and prospective accountants about Islamic accounting in terms of the characteristics and objectives of Islamic accounting. The research method used was a survey method with data collection techniques using questionnaires given to respondents where the respondents consisted of corporate accountants who worked on Islamic banks, accounting educators and accounting students from several Islamic universities in Medan.The techniques used to test hypotheses were one sample t-test, and independent sample t-test. Based on statistical tests performed, the findings of this study were: 1) Islamic accounting characteristics were not the same as conventional accounting characteristics according to the perceptions of corporate accountants, accounting educators and accounting students, 2) the purpose of Islamic accounting was not the same as conventional accounting according to the perceptions of corporate accountants, accounting educators and accounting students, and 3) there was no significant difference in perception among corporate accountants, accounting educators and accounting students about the characteristics of Islamic accounting and the purpose of Islamic accounting.
Super-Resolution Meets Quantum Optics

Super-resolution is a general term for methods surpassing the diffraction limit in optical microscopy, imaging details finer than half of the visible wavelength. Each of these methods employs a different source of extra information such as non-linearity or a time dependent scene. We present here two methods, which for the first time apply the quantum nature of light as a source of extra information in order to break the diffraction limit.
Regional Policy and Firm Performance-Evidence for Eastern Europe

The European Union allocates a large share of its budget to Structural Funds Program in order to reduce regional disparities and to foster the economic, social and territorial cohesion across its member countries. Given its importance, many studies have aimed to evaluate the effectiveness of the EU’s regional policy. These studies, which were predominantly focused on the growth of regions in the EU, have shown that impact EU Structural Funds depends on the regional absorptive capacity, the objective of the funds and on the intensity of Structural Funds. So far, there is little evidence on the direct and indirect effects of EU Structural Funds on the performance of firms. This paper provides to the literature through the combination of firmlevel information with detailed information on the regional distribution of EU Structural in Central Eastern European new member states. By applying a Heckman-GMM estimation, we are able to assess the impact of the EUs regional policy on the survival probability of firms and on firm performance indicators such as productivity, value added and employment. A high share of EU Structural Funds leads to an increase in employment and to a lower productivity of firms located in the corresponding region. Furthermore, our findings confirm that it is essential to take a precise look at the expenditure categories. Funds allocated in the category of productive environment lead to a higher probability of small and low productive firms to stay in the market and, hence, promote a persistency of existing economic structures.
CCTP-2019-2 , ITCP-IPP 2019 / 2 , MAD-TH-1902 Understanding KKLT from a 10 d perspective

Some of the most well-celebrated constructions of metastable de Sitter vacua from string theory, such as the KKLT proposal, involve the interplay of gaugino condensation on a D7-brane stack and an uplift by a positive tension object. These constructions have recently been challenged using arguments that rely on the trace-reversed and integrated 10d Einstein equation. We give a critical assessment of such concerns. We first relate an integrated 10d Einstein equation to the extremization condition for a 10d-derived 4d effective potential. Then we argue how to obtain the latter from a 10d action which incorporates gaugino condensation in a (recently proposed) manifestly finite, perfectsquare form. This effective potential is consistent with 4d supergravity and does not present obstacles for an uplifted minimum. Moreover, within standard approximations, we understand the uplift explicitly in one of the popular versions of the integrated 10d equation. Our conclusion is that de Sitter constructions of the KKLT type cannot be dismissed simply based on the integrated 10d equations considered so far.
One night of partial sleep deprivation affects biomarkers of cardiac damage, but not cardiovascular and lipid profiles, in young athletes

Sleep loss is among the most common yet frequently overlooked problems. This disruptive influence is associated with an adverse lipid profile (LP) and consequently results in an increased risk of cardiovascular disease. Furthermore, it has been well established that athletes are increasingly confronted with sleep problems. The aim of this study was to explore the effect of one night of partial sleep deprivation (PSD) on the cardiovascular profile and LP in young, trained athletes. Ten male Taekwondo athletes were randomized for three sleep conditions in a counterbalanced order: (i) following a baseline sleep night (BN), (ii) following PSD at the beginning of the night (PSDBN), and (iii) following PSD at the end of the night (PSDEN). Basal cardiovascular physiological measures were recorded, and blood samples were taken in the fasted state following each sleep session (i.e., in the morning at 07:00 h). The results showed that myoglobin and creatine phosphokinase increased significantly after PSDEN but not after PSDBN. By contrast, no alteration was observed in the LP and physiological parameters following the two types of PSD. In conclusion, these results show that PSDEN increases cardiac damage biomarkers significantly, even though they do not reach clinical significance. Thus, one night of PSD does not affect the physiological responses and biomarkers of LP in Taekwondo athletes.
Design and evaluation of computerized cognitive games to improve cognitive performance in multiple sclerosis: A correlation and validation study

This paper aims to provide data related to the correlations between web-based cognitive game training tasks and cognitive performance in patients with multiple sclerosis. A brief description of the game training platform, technology required, and design principles are described. Correlations were computed to explore the relationships between performance of cognitive games and the cognitive test battery.