Miracle-dz/UniFAR-FTUs huggingface dataset:
A Metaheuristic Approach for Conservation Voltage Reduction in Unbalanced Active Distribution Networks

This work proposes a multi-objective optimization formulation to solve the Conservation Voltage Reduction (CVR) problem for three-phase unbalanced active distribution systems. CVR is a tool deployed for reducing power consumption by exploiting the voltage dependency of loads. Here, the node voltage magnitudes are kept near to its lower limits, as a strategy. Voltage Regulators (VRs), Capacitor Banks (CBs), On- Load Tap Changers (OLTCs), and reactive power output from smart inverters are used to achieve this objective. Along with minimizing the load demand, minimization of the losses is also considered as an objective. Since many of the devices are operated separately across each phase, the grid suffers from increased voltage unbalances. This issue is handled by choosing Voltage Unbalance Factors (VUFs) at all nodes as constraints. Minimization of unbalance current flow in the substation transformer is also added as an objective in the optimization problem to reduce associated ill-effects. The optimization problem solved using Multi-Objective Particle Swarm Optimization (MOPSO), is tested on modified IEEE 13-bus and 34-bus systems. Obtained results show a reduction in losses and demand while ensuring acceptable voltage profiles throughout the feeders. Results show that the load profile and the R/X ratio of the lines profoundly influence the effectiveness of CVR.
Implementing Term Frequency-Inverse Term Frequency at Tweets in Indonesian Fraud Crime Cases

Crime analysis is a methodical approach to identifying and analyzing patterns and trends in crime. Using crime analysis and text mining, we can analyze the modus operandi of crime to reduce the offenders. However, many fraud victims rarely report their problems to the police and tend to share their fraud case stories with their social media. Therefore, it needs a capable dataset to further analyze the fraud case. TFIDF as a weighting approach is used to find out the importance of a word. Thus, this study makes data derived from original data into data that can be processed for analysis. The data used are data from social media Twitter with 39,964 data that have keyword “penipuan” in Indonesian. This study uses text preprocessing techniques to clean the data from information which is not useful for the analysis process. The phases are data crawling, data cleansing, stemming, filtering, tokenizing, and visualizing data. After preprocessing data, the data will be processed into the terms frequency that appears and visualizes it. As a result, in the TF-IDF approach, the word “nomer” is the first for the word that often appear. It can be hypothesized that victims usually share their experiences of fraud that had related to the victim’s personal number.
Dynamic Sliding-Mode Control for Piecewise Affine Systems

This paper investigates the problem of dynamic sliding-mode control through piecewise affine systems (PWAs). An uncertain piecewise affine system is utilized to equivalently represent a general nonlinear system on a compact region around the origin. A piecewise dynamic sliding-mode control law is then constructed for robustly stabilizing the uncertain piecewise affine system and, consequently, for asymptotic stabilization of the corresponding non-affine continuous-time nonlinear system. The constructed approach holds a favorable feature: it removes some assumptions on the system matrices, thus the developed scheme is more relaxed compared with the published approaches. The simplicity and advantages of the developed scheme is illustrated by a numerical simulation.
An Improved Intelligent Pricing Model for Recycled Mobile Phones

Nowadays the market of recycled mobile phones has become so big that the autonomous pricing problem for the phones is attracting more and more attention. The pricing problem of recycled mobile phones is full of nonlinear mapping relationships and fuzzy concepts, which makes it difficult to accurately evaluate the value of recycled mobile phones. In order to improve pricing accuracy, an improved pricing model based on Fuzzy Neural Network with Momentum in Updating the Parameters (FNN-MUP) is proposed. First, we used principal component analysis to select the key features that affect the pricing of recycled mobile phones; second, we established a pricing model for recycled mobile phones based on fuzzy neural networks to achieve the mapping between key feature variables and cell phone price; finally, we applied momentum method to optimize the parameters of the fuzzy neural network to update the parameters. Experiments were conducted based on 1,200 pieces of data generated in real transactions for recycled mobile phones. The model was compared with other 6 pricing methods. The results show that the average relative error of this model is lower, and the prediction accuracy is significantly better than the contrasts.
Lead Forecasting using LSTM based Deep Learning Architecture for Sentiment Analysis

Marketers adopt various strategies to improve the efficiency of lead conversion by understanding more about their prospective customers. Advancements in data mining and machine leaning techniques helped industry to adopt these techniques to the business benefit. Use of modern deep learning technology for marketing industry is limited. This paper proposes a methodology for identifying the probability of conversion of a lead by employing a structured and unstructured data analysis and modelling. A binary classification model is built using feed forward neural network for structured data classification. The unstructured user comments data is represented using a long short term memory (LSTM) network which has the ability to capture context information effectively. This method provide a comprehensive approach to consider both structured and unstructured data so as to utilize the data effectively to know the customer more and there by improve the probability of predicting the lead conversion. This methodology provide a strong basis for using LSTM based sentiment analysis forecasting of unstructured data along with the classification performed using structured data.
Integrated Technological Tools for Effective Blended Learning

Higher Education of India encourages blended learning in the universities by introducing a wide range of online courses. Presently, India is good at integrating Information and Communication Technology (ICT) which enables educators and learners to adopt blended and flipped teaching and learning in the classrooms. This unexpected COVID-19 pandemic situation doubles the leverage of technology and stimulates teachers and students to go online. This research paper explores various technological tools for effective blended teaching and learning. When online classes are started students and teachers are apprehensive but gradually engrossed in this uncanny situation to resume the process. In the course of the journey, how effectively these technological tools are used to recommence the studies are the objectives of this paper. The students’ performance records were assessed as a measure of quality learning through the tools. The research was conducted in order to identify the students’ adaptability to the present situation as well as blended learning. The research has focused on specific technological tools like Google Classroom, Docs, Slides, Sheets, Forms, Hangouts, Meet, etc for teaching and learning and assessments. The results of the students show that blended teaching and learning is an effective approach by using technological tools.
A Fast Cornering Method Based On Model Predictive Control

In the automatic driving of vehicles, it is a very common way to separate the motion control into two levels, the first is trajectory planning and the next is path tracking. In this paper, we introduce a fast cornering way for the vehicle based on the two steps. First, choosing a better trajectory rather than centerline of the road to follow in order to reduce the passing time. The desired trajectory is described as the optimal linear combination of the shortest path and the fastest speed path. It was expressed as a bounded optimal problem to solve. Once the trajectory has been determined, it is necessary to design a path tracker. We construct a controller based on vehicle’s dynamics and environmental conditions using model predictive control (MPC). Then an experiment was implemented on CARSIM and MATLAB joint simulation. And the results showed that the presented approach is able to reduce the passing time and keep the vehicle within the lane.
Semi-autonomous greenhouse environment control by combining expert knowledge and machine learning

The concept of "autonomous greenhouse" hints the automatic setting of control target, and giving orders on facilities to reach these targets (set point). Information and communication technologies are widely used, but how to integrate common sense or knowledge in decision-making is still challenging. Semi-autonomous greenhouse control is to set rules with joint advantages of experienced grower and powerful machinery, with the support of knowledge graph and semantic analysis. The contribution of each side is dependent on the intelligence level of computers, the availability of data, etc. In this work, the hybrid system between human and machinery is shown with the temperature control in greenhouse. The target is set mainly by expert knowledge, while the temperature controlled by vent opening is decided by an algorithm. Result shows that the target is better reached compared to that of the experience-based approach. This example shows the feasibility of human-machine hybrid intelligence system for greenhouse environment control. Although this approach is tested for temperature control, it can be extended to control multiple factors simultaneously (temperature, light intensity, humidity, etc.) by driving multiple facilities (heating, lightening, venting, etc.).
Design of Dynamic Surface Controller Based on Nonlinear Observer for Ship Dynamic Positioning System

Considering that vessels need to position more quickly and accurately in complex environments, a control system combining a nonlinear observer and dynamic surface controller is proposed. In order to simplify calculation and increase practicality in engineering, dynamic surface control technology is introduced. For getting a more accurate velocity, a nonlinear passive observer can be introduced to estimate them which is impossible to measure accurately. Stability is proved by selecting an appropriate Lyapunov function and the appropriate parameters are chosen to ensure all signals are uniformly bounded. The simulation results show that the ship's center of gravity can reach and stabilize in the desired position within a short time. Therefore, the designed control law is effective.
GPS Receiver Frontend Design for Radio Frequency Interferences and Noise Cancellations

This article proposes integrated GPS receiver frontend design, performance optimization and low power dissipation. The proposed frequency synthesizer with a cross coupled negative-resistance multiple-gated circuit (NRMGC) voltage-controlled oscillator (VCO) by employing a transformer-based LC-tank achieves low phase noise. The proposed design chooses decoupling effect to decrease coupling inductances and then decrease quality factors to obtain higher oscillation frequency and wide tuning range. The eye pattern measured results demonstrate that receiver frontend for radio frequency interferences achieves optimized GPS (global positioning system) performance.
Risk‐based corrective action, natural attenuation, and changing regulatory paradigms

Abstract Since the late 1980s, more than half of all known underground storage tanks (USTs) in the United States have been closed. Many of these tanks are known to have leaked, and new releases are still being reported. Correcting the resulting soil and groundwater contamination has turned out to be an expensive undertaking. In response, regulators and other interested parties have worked together to adopt risk‐based approaches to setting cleanup goals and to promote innovative cleanup technologies such as natural attenuation. These changes have dramatically affected the way in which leaking USTs are regulated and cleaned up.
Characterization of laser-fired contacts processed on wafers with different resistivity

To evaluate the feasibility of transferring the patented Laser-Fired Contact (LFC) process scheme into industrial solar cell production investigations of highly efficient and LFC contacted silicon solar cells on different resistivities have been carried out. These cells feature inverted pyramids on the front side and a thermally grown silicon oxide as surface passivation. Besides the higher efficiencies (up to 21.4% on 0.5 /spl Omega/cm material) of the LFC cells compared to the PERC references (20.9% on 0.5 /spl Omega/cm material), especially the superior value for V/sub oc/ (57.2 mV higher V/sub oc/ on 10 /spl Omega/cm) is an indication for the formation of a local aluminium BSF. The laser alloying process of aluminium into the silicon was studied by L-SNMS measurements and visualised by EBIC scans of solar cell test structures processed on n-type FZ silicon bulk material.
Continuum source atomic absorption spectrometry : past, present and future aspects – a critical review

This review article covers 1½ centuries of history of continuum source atomic absorption spectrometry (CS AAS), starting with the early experiments of Kirchhoff and Bunsen in the 1860s. It also tries to explain why the technique was abandoned in the first half of the 20th century, why it was "re-discovered" in the 1960s in the USA, where several research groups worked intensively on the development of CS AAS for about four decades, and why they finally failed. This review also discusses the major advantages of modern high-resolution CS AAS (HR-CS AAS), which uses a high-resolution double monochromator and a charge coupled device array detector, which adds the wavelength as third dimension to the usual display of absorbance over time. The literature about applications of this technique has been carefully revised. Finally an attempt will be made to foresee future developments of this technique, which is obviously not an easy task.
Effective potentials between gold nano crystals – functional dependence on temperature

A method is presented that allows to combine the effective potential between two nano crystals (NC), the potential of mean force (PMF), as obtained from all-atomistic molecular dynamics simulations with perturbation theory. In this way, a functional dependence of the PMF on temperature is derived, which enables the prediction of the PMF in a wide temperature range. We applied the method to systems of capped gold NCs of different size. They show very good agreement with data from atomistic simulations.
The mechanism of polymerisation of butyl cyanoacrylate in aqueous dispersions

Butyl cyanoacrylate has been polymerised by dispersion in acidified water to yield nanoparticles. Reactions have been carried out at various temperatures and the molecular weight of the growing polymer measured. In all cases polymerisation proceeds by generation of discrete populations of oligomers, which are then re-initiated and undergo further growth. The peak molecular weight is around 1300 g/mol and it is considered that a stepwise initiation, termination and re-initiation process continues until diffusionally limited by the internal viscosity within the nanoparticle.
Microprobe techniques for determining diffusivities and respiration rates in microbial slime systems

A microprobe electrode was used to determine dissolved oxygen concentrations near the surface and within a bacterial slime mass supplied with a continuous flow of nutrient solution. With dilute medium, the oxygen profile became level at high concentrations within the film, indicating substrate‐limited respiration. More concentrated medium caused the profile to fall to low oxygen concentrations characteristic of oxygen‐limited respiration. Oxygen responses to sudden changes in concentration of nutrient medium were measured. Estimates of microbial respiration rate and of diffusivity of oxygen were based on well‐known diffusion equations.
Client Contact in Self-Help Therapy for Anxiety and Depression: Necessary But Can Take a Variety of Forms Beside Therapist Contact

Self-administered therapies (SATs) have been promoted as a way to increase access to evidence-based mental health services. Recent meta-analyses and literature reviews suggest that SATs with clinical guidance are more effective than SATs with no contact for the treatment of anxiety and depression. However, little attention has been paid to the role of nonguidance contact, contact that does not involve the provision of assistance in the application of specific therapy techniques such as emails to encourage treatment adherence. The present article examines the impact of nonguidance contact on the outcomes of SATs for anxiety and depression. Electronic databases were searched to identify studies conducted over the past two decades by independent research teams that have tested cognitive-behavioural SATs over multiple trials. Findings suggest that the involvement or guidance of a therapist is not essential for SATs to produce significant benefits as long as nonguidance contact is provided. It is suggested that even very minimal levels of nonguidance contact increase SAT's outcomes by motivating treatment engagement and improving adherence. The benefit of SATs that can be accessed directly by large numbers of individuals and that do not require therapist involvement to ensure efficacy can potentially significantly increase the cost effectiveness and quality of mental health service delivery.
Broadband thin flat lens at sub-THz frequencies

We recently showed (Savini 2012) the use of stacked graded photolithographic capacitive metal-mesh structures on polypropylene substrates to produce a thin flat Wood lens working in a wide (90%) bandwidth. Here an additional impedance-matched layer is designed to improve the original lens efficiency in a wide band around the central frequency of operation.
New aspect of chemoselective hydrogenation utilizing heterogeneous palladium catalysts supported by nitrogen- and oxygen-containing macromolecules

Heterogeneous palladium catalysts supported on nitrogen-containing macromolecules, such as fibroin (Fib), polyethyleneimine (PEI), boron nitride (BN), and molecular sieves (MS), oxygen-containing macromolecules were developed. The Pd/Fib, Pd/PEI, Pd/BN, Pd/MS3A and Pd/MS5A were used for the novel chemoselective hydrogenation of the reducible functionalities. These catalysts were easy to handle and easily prepared by stirring a macromolecule-suspended palladium diacetate solution in methanol at room temperature. The absorption effect of the Pd species to the macromolecules and the catalyst activity were partially controlled by the lone pairs of the nitrogen atoms in the macromolecule. Pd/Fib, Pd/MS or Pd/BN mainly enabled the chemoselective hydrogenation of azide, alkene and alkyne in the presence of other reducible functionalities. Furthermore, the chemoselective semi-hydrogenation of alkynes to alkenes could be achieved using Pd/PEI or Pd/BN with a nitrogen-containing base catalyst.
Changes of LiCoO2 Cathode Material for Lithium-Ion Battery during Long Cycling

Changes of the cathode material LiCoO 2 of our homemade lithium-ion batteries with good uniformity, high capacity, and good cycling were investigated after 500, 1060, and 1600 cycles. The results show clearly that the cathode partially contributes to capacity fading of lithium-ion batteries due to two factors: (i) reactions between the electrolytes and LiCoO 2 , which produce a continuously growing surface layer on the cathode, leading to the increase of the charge transfer resistance, and (ii) the fading of LiCoO 2 structure. These results provide valuable clues to extend the cycling life for lithium-ion batteries.
Experimental measurements of solvation forces in nonpolar liquids

Forces between molecularly smooth mica surfaces immersed in tetrachloromethane, benzene, and 2,2,4‐trimethylpentane have been measured. In tetrachloromethane and benzene the force law is an oscillatory function of the separation between the mica surfaces, with a periodicity equal to the mean molecular diameter and a measurable range of appoximately ten periods, or about 5 nm. Beyond this separation, the oscillations merge into a purely attractive ‘‘tail’’. In 2,2,4‐trimethylpentane the force law shows only short‐range oscillatory behavior, below 2 nm; at larger separations the force is everywhere attractive. The results are compared with measurements on cyclohexane, octamethylcyclotetrasiloxane and n‐octane, including some repeat measurements. When the distance scale is normalized by the mean periodicity of the force curve for each liquid, the results for the four fairly rigid molecules benzene, tetrachloromethane, cyclohexane, and octamethylcyclotetrasiloxane are very similar; minor differences possibly .
Child Neuropsychology

This study examines the processing of prosodic cues to linguistic structure and to affect, drawing on fMRI and behavioral data from 16 high-functioning adolescents with autism spectrum disorders (ASD) and 11 typically developing controls. Stimuli were carefully matched on pitch, intensity, and duration, while varying systematically in conditions of affective prosody (angry versus neutral speech) and grammatical prosody (questions versus statement). To avoid conscious attention to prosody, which normalizes responses in young people with ASD, the implicit comprehension task directed attention to semantic aspects of the stimuli. Results showed that when perceiving prosodic cues, both affective and grammatical, activation of neural regions was more generalized in ASD than in typical development, and areas recruited reﬂect heightened reliance on cognitive control, reading of intentions, attentional management, and visualization. This broader recruitment of executive and “mind-reading” brain areas for a relative simple language-processing task may be interpreted to suggest that speakers with high-functioning autism (HFA) have developed less automaticity in language processing and may also suggest that “mind-reading” or theory of mind deﬁcits are intricately bound up in language processing. Data provide support for both a right-lateralized as well as a bilateral model of prosodic processing in typical individuals, depending upon the function of the prosodic information.