Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Document Summarization Using Deep Learning Mechanism with Competent Analysis

Keywords play an important role in every aspect of search methodologies. Due to the rapid increase of information on the internet, keywords aid in for the effective search. Research on keyword mining is gaining more and more attention among researchers and learners. Document summarization generates a brief summary by extracting keywords from documents or from multiple documents by the deep learning algorithm. The main concept is to reduce the content or minimize the key important information present in any documents. The procedure is finagled by the Restricted Boltzmann Machine (RBM) algorithm for better efficiency and for removing redundant and unrelated sentences. The restricted Boltzmann machine is an undirected graphical model for binary random variables. It mainly consists of three layers input, hidden and the output layer. The input data is equally distributed to the hidden layer for further operation. The experimentation is carried out and the summary is generated for every document set given. From the summary, the document similarity is calculated from the selected inputs. It mains focus on the keyword iteration of each document given. This paper helps to calculate the accuracy of similarity among the documents.
Evaluation and Redesign of Semester Learning Plan to Improve the Effectiveness Business Process (Case Study: Telkom University)

— Telkom University is a private educational institution that implements an academic portal called iGracias to serve the needs of students, lecturers, employees, and parents/guardians of students, especially in providing campus information quickly and widely and up-to-date. One of the most important processes in iGracias is the Semester Learning Plan process, from managing the PLO Master to managing the Detailed RPS approval. Based on 2020 data obtained from the PuTI (Information Technology Center) Telkom University, there were 1931 access logs on iGracias related to the Semester Preparation Plan process in the Information Systems study program at Telkom University. Seeing this, it is necessary to analyze and improve the Semester Learning Plan process so that it can increase the effectiveness of time and activities in the process. This redesign process uses the Business Process Model and Notation (BPMN) and the Bizagi Application as a simulation tool for both existing business processes and targeted business processes. From the simulation, the time required for existing business processes is 109948,2678 hours with a total of 12 activities. While the targeting business process resulted in only 42791,07528 hours to complete 11 activities.
Early Identification of Rice Plant Diseases using Machine Learning Algorithms

As a precaution and to achieve better quality of crops early detection of rice plant is mandatory . to do this, first disease on the rice plant leaves is identified which helps the farmers to identify type of disease. Different types of diseases may infect rice plants which decrease the yield. Most common diseases are which infect the rice is Rice Blast , leaf smut, bacterial leaf blight and brown spot. Here we have applied machine learning algorithms to detect most common diseases. Different machine learning algorithms are used to train the dataset. First, The data is preprocessed after this step we use different machine learning algorithms which includes Decision Tree algorithm-J48,K-Nearest Neighbor ,Naive Bayes. Among these algorithms J48 Decision Tree Algorithm achieved 96% of accuracy. To increase the accuracy CNN Classifier is applied on the dataset. Using this Approach the accuracy level is increased up to 97.58%.
How Much Should You Trust Your Power Calculation Results? Power Analysis as an Estimation Problem

With the surge of randomized experiments and the introduction of pre-analysis plans, today’s political scientists routinely use power analysis when designing their empirical research. An often neglected fact about power analysis in practice, however, is that it requires knowledge about the true values of key parameters, such as the eﬀect size. Since researchers rarely possess deﬁnitive knowledge of these parameter values, they often rely on auxiliary information to make their best guesses. For example, survey researchers commonly use pilot studies to explore alternative treatments and question formats, obtaining eﬀect size estimates to be used in power calculations along the way. Field experimentalists often use evidence from similar studies in the past to calculate the minimum required sample size for their proposed experiment. Common across these practices is the hidden assumption that uncertainties about those often empirically obtained parameter values can safely be neglected for the purpose of power calculation. In this paper, we show that such assumptions are often consequential and sometimes dangerous. We propose a conceptual distinction between two types of power analysis: empirical and non-empirical. We then argue that the former should be viewed as an estimation problem, such that their properties as estimators (e.g., bias, sampling variance) can be formally quantiﬁed and investigated. Speciﬁcally, we analyze two commonly used variants of empirical power analysis – power estimation and minimum required sample size (MRSS) estimation – asking how reliable these analyses can be under scenarios resembling typical empirical applications in political science. The results of our analytical and simulation-based investigation reveal that these estimators are likely to perform rather poorly in most empirically relevant situations. We oﬀer practical guidelines for empirical researchers on when to (and not to) trust power analysis results.
Optimal H ∞ Control Design of MMC-based HVDC Links

—Modular multilevel converter (MMC) has emerged as the preferred choice for Voltage Source Converter (VSC)-based High Voltage Direct Current (HVDC) systems due to its low losses, low harmonic distortion, modularity, and redundancy. These advantages come at the expense of a complex control system with the strong coupling among its control variables, which complicates the design procedure of both its individual control loops and the DC link controllers. In fact, the performance improvement of a control loop could lead to degraded performance of other feedback loops. Hence, to deal with such a complex dynamic system, this article suggests adopting multivariable H ∞ optimal control techniques in order to ensure stability and optimized performance of a VSC-HVDC link. First, a full-order, centralized multi-input-multi-output (MIMO) controller is derived based on H ∞ optimisation and used as a benchmark for the system performance level. Then, a ﬁxed-structure, decentralized MIMO controller is synthesized to make a compromise between the optimal performance and feasibility of practical implementation. Finally, simulations are conducted to evaluate and compare the performance degradation due to the migration from a high-order, centralized controller towards a low-order, decentralized controller.
EVALUATION OF A PASSIVE KNEE EXOSKELETON FOR VERTICAL JUMPING THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR

In recent studies exoskeletons have been proven to augment human mobility and facilitate daily tasks such as walking, running, and hopping. Most exoskeletons are designed to reduce the effort (i.e., metabolic rate) expended by their user while performing aerobic tasks. However, exoskeletons that assist fast, explosive movement, specifically vertical jumping, have yet to be thoroughly examined. Furthermore, a fundamental lack of understanding still prevails regarding the interactions between humans and exoskeletons. Our main hypothesis was that a passive exoskeleton has the ability to increase vertical jumping height without providing additional external energy. The designed passive knee exoskeleton consists of springs which act in parallel to the quadriceps femoris muscle. These springs store energy in the negative-work phase, during knee flexion, and inject the energy in the consequent positive-work phase, during knee extension. The stored energy can then be utilized to increase the jumping height. The exoskeleton was tested on ten healthy participants, in two separate experimental sessions, in which they aimed to jump as high as possible. In the first session, participants jumped under five conditions- two without the exoskeleton and three with the exoskeleton and three different spring stiffness levels. The participants jumped without receiving instructions on how to use the exoskeleton. Results showed an increment in jump height as spring stiffness increased, and no difference in height between the jumps with and without the exoskeleton. In the second session, participants jumped under two conditions- without the exoskeleton and with the exoskeleton with the highest spring stiffness level. The participants were trained to better utilize the exoskeleton by exploring different jumping techniques in order to improve their adaption to the exoskeleton. The second session, including instructions and training with the exoskeleton, resulted in a 6.4%±0.9% (mean ± SE) increase in jumping height compared to jumping without the exoskeleton. To the best of our knowledge, this is the first time a passive exoskeleton is shown to be successful in augmenting vertical jumping. The knowledge accumulated during this study regarding the human-exoskeleton Subsequently, these results will be used in our laboratory for the development of a model for the human-exoskeleton interaction using an optimal control process, that aims to enable developing different types of exoskeletons in a faster and more economical way. Sections of this work were presented in the 2019 International and American Society of Biomechanics conference in Calgary, Canada. This work was also presented in 2020 The International Symposium on Wearable Robotics conference in Vigo, Spain (Virtually). Additionally, we are also in preparations for a publication in Science Robotics.
Numerical Solution of the Modiﬁed Kawahara Equation Using Sinc Collocation Method

: This paper investigates numerical solution of the modiﬁed Kawahara equation by using ﬁnite difference method and sinc collocation method. The semi-discrete scheme is obtained by approximating time derivative with (cid:18) -weighted scheme. Then, a fully discrete scheme is established by a collocation method using sinc basis. The stability of proposed method is analyzed by expressing the fully discrete scheme in matrix form. Finally, some numerical experiments illustrate the efﬁciency and superiority of present method, and two invariants are evaluated to determine the conservativeness of the method.
Radar and LiDAR Fusion for Scaled Vehicle Sensing

Scaled test-beds (STBs) are popular tools to develop and physically test algorithms for advanced driving systems, but often lack automotive-grade radars in their sensor suites. To overcome resolution issues when using a radar at small scale, a high-level sensor fusion approach between the radar and automotive-grade LiDAR was proposed. The sensor fusion approach was expected to leverage the higher spatial resolution of the LiDAR effectively. First, multi object radar tracking software (RTS) was developed to track a maneuvering full-scale vehicle using an extended Kalman filter (EKF) and the joint probabilistic data association (JPDA). Second, a 1/5 scaled vehicle performed the same vehicle maneuvers but scaled to approximately 1/5 the distance and speed. When taking the scaling factor into consideration, the RTS’ positional error at small scale was, on average, over 5 times higher than in the full-scale trials. Third, LiDAR object sensor tracks were generated for the small-scale trials using a Velodyne PUCK LiDAR, a simplified point cloud clustering algorithm, and a second EKF implementation. Lastly, the radar sensor tracks and LiDAR sensor tracks served as inputs to a high-level track-to-track fuser for the small-scale trials. The fusion software used a third EKF implementation to track fused objects between both sensors and demonstrated a 30% increase in positional accuracy for a majority of the small-scale trials when compared to using just the radar or just the LiDAR to track the vehicle. The proposed track fuser could be used to increase the accuracy of RTS algorithms when operating in small scale and allow STBs to better incorporate automotive radars into their sensor suites. Radar and LiDAR Fusion for Scaled Vehicle Sensing
Controls of intermodel uncertainty in land carbon sink projections

Over the last decades, land ecosystems removed from the atmosphere approximately one third of anthropogenic carbon emissions, highlighting the importance of the evolution of the land carbon sink for projected climate change. Nevertheless, the latest cumulative land carbon sink projections from eleven Earth system models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) show large differences, even for a policy-relevant scenario with 10 mean global warming by the end of the century below 2°C relative to preindustrial conditions. We hypothesize that this intermodel uncertainty originates from model differences in the sensitivities of net biome production (NBP) to (i) atmospheric CO 2 concentration, (ii) air temperature and (iii) soil moisture, as well as model differences in average conditions of (iv) air temperature and (v) soil moisture. Using multiple linear regression and a resampling technique, we quantify the individual contributions of these five terms for explaining the cumulative NBP anomaly of each model relative to the multi- 15 model mean. Results indicate a primary role of the response of NBP to interannual temperature and soil moisture variability, followed by the sensitivity to CO 2 , and lastly by the average climate conditions, which also show sizeable contributions. We find that the sensitivities of NBP to temperature and soil moisture, particularly in the tropics, dominantly explain the deviations from the ensemble mean of the two models with the lowest carbon sink (ACCESS-ESM1-5 and UKESM1-0-LL) and of the two models with the highest sink (CESM2 and NorESM2-LM). Overall, this study advances our understanding of why land carbon sink projections from Earth system models differ globally and across regions, which can guide efforts to reduce the T and SM are generally smaller. The overall intermodel standard deviation of global land projected NBP based on the regression estimates is 3.86 gC m -2 y -1 (equivalent to 44.9 PgC during the period 2015–2100), relative to which the intermodel standard deviations of the contributions from the controls are 53.2% for sCO 2 , 58.5% for sT, 39.9% for sSM, 24.5% for T and 27.6% for SM. These results highlight the importance of sSM and SM as controls of projected cumulative NBP, in addition to sT and T. Furthermore, the high intermodel standard deviation values for many of the controls suggest that while constraining any individual control would help reduce the spread of the projected land carbon sink, a large
THE OPTIMAL RELATIONSHIP BETWEEN ACTUATOR STIFFNESS AND ACTUATION TIMING FOR A PASSIVE ANKLE EXOSKELETON: AN OPENSIM SIMULATION

Introduction The passive ankle exoskeleton developed by Collins et al. (2015) reduced the metabolic cost of walking with an actuation-timing of ~16% of stance [1]; however, other actuation timings have not been extensively investigated. Therefore, the purpose of this study was to determine the optimal relationship between actuator-stiffness and actuation-timing for a passive ankle exoskeleton by using musculoskeletal modeling.
Bibliometric Analysis of Studies on Salafism in Indonesia

This study analyzes and develops Salafism in Indonesia with a bibliometric approach. In this article, we describe the trend of Salafism publications in Indonesia; (1) Geographical Distribution; (2) Number of Documents Per Author; (3) Number of Documents Per University; (4) Total documents based on the subject area; (5) Documents based on country (6) Indonesian Salafism citation. The authors used the Scopus Search Engine as a tool in data collection in the form of publications related to the theme of Salafism in Indonesia. The data collection using visualization software VOS viewer and Nvivo. The results of this study indicate that, from 2005 to 2021, 68 documents wrote about Salafism in Indonesia in the Scopus database. Indonesia is the country with the most significant contributor to the writing of Salafism in Indonesia as many as 23 documents. Moreover, the highest publications are in social and science journals at 60.8%. When viewed through documents per author, Hasan N is the most author with four documents.
Local Information Based Attentional Opponent Modelling In Multi-agent Reinforcement Learning

Opponent modelling (OM) can enable agents to reason behaviors of others, in order to act accordingly and interact effectively in multi-agent settings. Most of the existing OM approaches perform explicit models based on opponent’s observations and actions during execution, where incessant message exchange is required to predict others’ real-time behavior to aid local decision. However, reliable communication is not available in many practical cases. In this paper, we propose attentional opponent modelling (ATOM) as an alternative approach, where the policy network depends on local observation without communication requirements during execution. The key consideration is that local observation usually contains knowledge of adjacent entities. By interaction-based attention mechanism, the opponent’s belief for each adjacent entity can be estimated. By aggregating such predicted beliefs, each agent can choose its action to promote cooperation. Experiments show that ATOM achieves superior performance over typical OM methods without extra messages exchange. Surprisingly, ATOM gets similar performance to approaches augmented with communication channels during execution.
Bursting Oscillations as well as the Bifurcation Mechanism of a Four-dimensional Laser System with Different Excitation Frequency Ratios

: Due to the complexity of the multi-scale effects in a nonlinear system under multiple excitation couplings, a non-smooth system with parametric and external excitations is explored. Firstly, by employing the Moivre formula, two excitation terms could be expressed by one slow-varying parameter. The obvious fast-slow effects in such systems could be presented when strictly adjusting both frequencies, making them much smaller than the natural frequency of the system. Furthermore, the stability of equilibria and possible bifurcations in fast subsystem are easily judged with the help of fast and slow analysis method. Notably, the frequency ratio between two excitations is the focus of the study. It is found that the number of fold and Hopf bifurcation points signiﬁcantly increases and the structure of equilibrium curves becomes more complicated as the ratio increases, so that the trajectory also exhibits a variety of mixed-mode oscillations. The oscillations of the system also perform two different symmetrical forms according to the two cases where the frequency ratio is integer or fractional.
Point of technique Endoscopic Resection of Lower Ureter in Upper Urinary Tract Tumors

Purpose: To evaluate the efficacy and safety of endoscopic resection of lower ureter in upper urinary tract tumor cases. Materials and Methods: Five patients with transitional cell carcinoma (TCC) of the upper urinary tract were enrolled in this study. Nephrectomy was carried out through a flank incision and distal ureter with a cuff of bladder, which was removed using endoscopic approach. Complications and recurrence rate were evaluated. Results: A total of 5 patients with upper urinary tract tumor underwent the endoscopic resection of lower ureter. All the patients had grade I transitional cell tumor. Two patients had suffered from bladder TCC treated previously. During the follow-up two cases developed bladder tumor: one, 18 months and another, one year postopera-tively, both in the base of bladder, which was managed successfully by transurethral resection (TUR). Conclusion: Endoscopic resection of lower ureter in selected patients with upper urinary tract tumors can lead to lower morbidity, shorter operation time, and higher patient's satisfaction. Despite the minority of cases in this study, it seems that this method is applicable in selected cases.
Reconfigurable Optical Chaotic Logic Operations with Fast Rate of Picoseconds

： In order to realize dynamic and reconfigurable optical chaotic logic operations ， a specific technical scheme based on Vertical Cavity Surface Emitting Laser （ VCSEL ） feedback by its own light and linear electro - optic modulation effect has been proposed. The normalized injection current is modulated as logic input ， the transverse electric field is modulated as control signal ， and the logic output is demodulated by the difference between the average value and the threshold value of the x - polarized light intensity from the output of VCSEL. By transforming the logic operation relationship between control signal and logic input ， the system can switch freely among basic logic operations such as NOT ， AND ， NAND ， OR ， NOR ， XOR and XNOR. When the code width is 600 ps and the noise intensity is as high as 2.75×10 9 ， the success probability of the logic operation still equals 1 ， indicating that the system has good anti - noise performance. And when the noise intensity equals 2.5×10 9 ， the success probability always equals 1 if the code width is at least 579 ps. The above results have great reference value for the development of fast and stable combinational logic operation devices.
Magnetic actuation of swimming soft microrobots with multiple ﬂagella

: The use of soft swimming microrobots as drug carriers is a rapidly developing sector of medical technol-ogy. In this research, simulations are run with a mathematical model that is capable of magnetic actuation of the head of soft microrobots. The actuation frequency, stifness of the tail and taillenght are variables that inﬂuence the swimming speed and travelpath of the microrobots. When increasing the amount of ﬂagella the propulsive force increases, but also the variable of phase diﬀerence is introduced. This new variable and the extra ﬂagella, results in a change in optimum variables and travelpath. It is shown that increasing the number of ﬂagella has a positive eﬀect on the swimming speed of the microrobot. But to optimize this increase in swimmingspeed, all variables need to be matched with the number of ﬂagella.
Formation and dynamics of solitary waves in plasmas

Solitary waves are small-scale structures in plasma that represent holes in the electron/ion phase space or density enhancements and depletions, depending on whether they are Bernstein-Greene-Kruskal (BGK) structures generated by a beam, two-stream, or kinetic Buneman type of instability an electron/ion acoustic mode an electron/ion are an of bipolar in