Miracle-dz/UniFAR-FTUs huggingface dataset:
AEROACOUSTIC SOUND PREDICTION OF A DIAPHRAGM BY A HYBRID METHOD

Most of the noise prediction methods, which has already been used, only applicable at low frequency range, below the first transverse duct mode. A developed method at this work, which suggested by Schram, avoided many simplification assumptions and is quite powerful for high Helmholtz numbers, i.e. when the turbulence/body interaction region is acoustically non-compact. By using numerical methods and an appropriate Green function, the method is applied to the prediction of sound in a duct obstructed by a diaphragm. The source fluctuations of the flow field are computed by a large-eddy simulation (LES) and are fed to the following acoustical computation as input data.The predicted power spectrum shows a fairly good agreement with a direct noise computation (DNC) results.Copyright © 2013 by ASME
Generalized, Three-Dimensional Definition, Description, and Derived Limits of the Triaxial Failure of Metals

Metal failure in many applications, such as ballistic impact, containment, shielding, metal forming, and crashworthiness, occurs while the material is in a three-dimensional state of stress. Many previous definitions of triaxiality use two invariants to define the relative stress state in a virtual element, leading to a characterization that can be better thought of as biaxial. In this paper, an additional parameter based upon the third stress invariant is defined, which extends the characterization of the state of stress to three dimensions and to true triaxiality. The relation of the two parameters is explored and limits are found in the failure surface, which is used in defining the critical failure regions. Standard tests are examined to determine if they can provide enough data to construct these regions of interest and new tests are proposed, which envelope the limits and thus define this failure surface.
A Text Mining using Web Scraping for Meaningful Insights

This research involves the usage of Machine Learning technology and Natural Language Processing (NLP) along with the Natural Language Tool-Kit (NLTK). This helps develop a logical Text Summarization tool, which uses the Extractive approach to generate an accurate and a fluent summary. The aim of this tool is to efficiently extract a concise and a coherent version, having only the main needed outline points from the long text or the input document avoiding any type of repetitions of the same text or information that has already been mentioned earlier in the text. The text to be summarized can be inherited from the web using the process of web scraping or entering the textual data manually on the platform i.e., the tool. The summarization process can be quite beneficial for the users as these long texts, needs to be shortened to help them to refer to the input quickly and understand points that might be out of their scope to understand.
Design of Decision Based Recursive Weighted Median Filter With Exponential Weights

The prescribed algorithm for removing impulse noise effectively even under high noise densities without causing any loss of image details. Hence a cascaded section of median filters that, involves an Decision-based Median Filter followed by a Recursive Weighted Median (RWM) Filter employing exponential weights are used. The median controlled algorithm is employed to calculate the exponential weights. In the algorithms that where proposed in earlier which involves a cascaded section of the median with the RWM filters provided lesser Peak Signal/Noise Ratio (PSNR) and greater Mean Square Error(MSE) values. Hence the output appeared to be distorted for higher noise levels. These drawbacks have been eliminated in this proposed algorithm.
Tongue movements and syllable onset complexity:Ultrasound study

In this study ultrasound was used to investigate tongue movements in syllables with different number and type of onset consonants. Ultrasound recordings provided the information of the distance the tongue travels over a target, and audio recordings of the time needed. The speed of the tongue’s travel was calculated from the two measurements. Results of ten speakers have shown that both duration and distance travelled increase with an increased number of onset segments, but that distance travelled is additionally influenced by the type of the segment, as is speed. Duration also seemed to be the least speaker-dependant of the three parameters.
MRDRL-ROS: a Multi Robot Deep Reinforcement Learning Platform based on Robot Operating System

Deep reinforcement learning (DRL) has greatly improved the intelligence of AI in recent years and the community has proposed several common software to facilitate the development of DRL. However, in robotics the utility of common DRL software is limited and the development is time-consuming due to the complexity of various robot software. In this paper, we propose a software engineering approach leveraging modularity to facilitate robot DRL development. The platform decouples learning environment into task, simulator and hierarchical robot modules, which in turn enables diverse environment generation using existing modules as building blocks, regardless of the underlying robot software details. Experimental results show that our platform provides composable environment building, introduces high module reuse and efficiently facilitates robot DRL.
Total dose performance at 77 K of a radiation hard 0.35 /spl mu/m CMOS SOI technology

This paper is the first demonstration that a 0.35 /spl mu/m CMOS technology designed to be radiation hard at room temperature is total ionizing dose radiation hard at 77 K to 1 Mrd (SiO/sub 2/). We compare radiation results from 0.35 /spl mu/m n-FET's irradiated with /sup 60/Co gamma rays at both 77 K and 300 K. We have demonstrated that interface traps play no appreciable role in the radiation performance of this technology at cryogenic temperatures.
ADDICTA: THE TURKISH JOURNAL ON ADDICTIONS

To cite this article: Ekşi, F. (2019). The mediating role of social media disorder in the relationship of experiential avoidance with psychological symptoms. Addicta: The Turkish Journal on Addictions, 6, 497–507. http://dx.doi. org/10.15805/addicta.2019. 6.3. 0025 1 Correspondence to: Fusun Ekşi (PhD), Faculty of Educational Sciences, Istanbul Medeniyet University, Kartal Istanbul 34862 Turkey. Email: eksifusun@gmail.com Abstract Experiential avoidance (EA) is an important process and risk factor in behavioral disorders. This study aims to examine the mediating effect of social media disorder on the relationship of EA with negative psychological symptoms (depression, anxiety, and stress). The study group consists of a total of 333 undergraduate students, 86 males (25.8%) and 247 females (74.2%). Mediation has been tested using structural equation modeling (SEM) with bootstrapping. Significant zero-order correlations have been found among the involved variables, as well as mediating effects from distress aversion (β = .09, p < .001, 95% CI = .10 .06), repression/denial (β = .07, p < .001, 95% CI = .08 .05), and behavioral avoidance (β = -.05, p < .05, 95% CI = -.06 .05) to indirectly predict psychological symptoms through partial mediation of social media disorder scores, as presumed. The results have the potential to contribute to a better understanding of EA on maladaptive social media use.
A direct approximation technique of log magnitude response for digital filters

A new direct approximation technique of log magnitude response for digital filters is presented in this paper. The facts that the log magnitude response of digital filters can be expanded into Fourier series and a fairly accurate cosine type log magnitude response can be realized by the elemental digital filter presented in this paper are used in the present technique. The system functions obtained by this method provide the best mean-square approximation to an arbitrarily prescribed log magnitude response. The resulting digital filters are realized in the cascade form of the elemental digital filters, and they give relatively low coefficient sensitivity. The elemental filter is recursive but its form is very simple. Its coefficients are easily obtained by the cepstrum of the impulse response which is the Fourier transform of the desired log magnitude response. This method is very powerful in the realization of digital filters for speech synthesis filters with complicated log magnitude responses.
High-Resolution North Sulawesi Drought Hazzard Mapping Based on Consecutive Dry Days (CDD)

North Sulawesi is one of the Province in northern Indonesia with high spatial annual rainfall variations and influenced by global climate anomaly that can lead to extreme events and disaster occurrence, such as flood, landslide, drought, etc. The purpose of this study is to generate high-resolution meteorological hazard map based on long-term historical consecutive dry days (CDD) over the North Sulawesi region. CDD was calculated based on observed daily precipitation data from Indonesia Agency for Meteorology, Climatology, and Geophysics (BMKG) surface observation station network (CDDobs) and the daily-improved Climate Hazards group Infrared Precipitation with Stations (CHIRPS) version 2.0 (CDDCHIRPS) during 1981 – 2010 period. The Japanese 55-year Reanalysis (JRA-55) data obtained from iTacs (Interactive Tool for Analysis of the Climate System) with the same time scale period also used to explain physical – dynamical atmospheric properties related to drought hazard over this region. The Geostatistical approach using regression kriging method was applied as spatial interpolation technique to generate high resolution gridded (0.05° × 0.05°) drought hazard map. This method combines a regression of CDDobs as dependent variable (target variable) on CDDCHIRPS as predictors with kriging of the prediction residuals. The results show that most of the areas were categorized as medium drought hazard level with CDD values ranging from 80-100 days. Meanwhile, small islands around main Sulawesi island such as Sangihe and Karakelong island are dominated by low drought hazard levels with CDD values ranging from 50-60 days. The highest levels of drought hazard area are located in South Bolaang Mongondow Regency.
Frequency and phase-lag effects on transport of particulates by an AC electric field

The dynamics of a charged particulate transported by a three-phase AC electric field is analyzed. The electric field is imposed by a series of parallel electrodes disposed inside a flat dielectric panel. An exact solution for the motion equation is proposed utilizing a new technique. The investigated conditions are for the curtain mode. The analysis shows that the forces acting on the particulate are much greater near the electrodes. This and the fact that the phase lag of the displacement vis-a-vis electric force exceeds a quarter cycle cause a great repulsion force to act on the particle when it passes through the bottom half of the trajectory, whereas a smaller attraction force acts during the top half. The difference between the repulsion and attraction momentums balances gravity and results in continuous levitation. The phase lag is sensitive to the applied electrical frequency; thus, only a limited range of frequencies causes continuous levitation. >
Modelling the Effects of Changes in the Exchange Rate, Oil Price and Real Wages on the Trade Balance in South Africa

Trade, which includes exports and imports, is one of the main engines of economic growth for both developed and developing countries. International trade is however affected and influenced by many factors, such as the exchange rate, commodity prices, production factors, etc. The purpose of this study was to analyse the responsiveness and relationship between the trade balance and factors such as the oil price, the exchange rate and real wage shocks. The study employed quarterly data covering the period from the first quarter of 1994 to the fourth quarter of 2018. The study adopted various statistical and econometric approaches and these approaches included an autoregressive distributed lag (ARDL) model, an error correction model and the Toda-Yamamoto causality test. The results from the ARDL model suggested long-run cointegration amongst the variables. The regression analysis revealed that all explanatory variables negatively impact on the trade balance. However, the magnitude of their effects differs from one variable to the other. Comparing all independent variables, the exchange rate was found to have the strongest long-term effect on the trade balance compared to the effect of both crude oil price and real wages. Interestingly, the error correction model (ECM) results indicated that the exchange rate can positively affect the trade balance. Additionally, the Toda-Yamamoto results demonstrated that both the exchange rate and oil price shocks can assist in forecasting trade balance fluctuations in the shortterm. Based on these findings, and since South Africa has no control over the oil price, it is imperative that the South African Reserve Bank implement strategies that may stabilise the exchange rate, in an attempt to increase opportunities that facilitate a positive trade balance, which is required for economic growth.
A THEORY-BASED MODEL OF CROWDFUNDING INVESTMENT INTENTION : The role of sustainability orientation on funder ’ s trust and investment intention

Background: Reward-based crowdfunding has gained in popularity over the years. Simultaneously, there has been an increasing demand for sustainability initiatives in Europe. The question arises as to what influence sustainability orientation has on rewardbased crowdfunding. This study addresses the gap between what influence sustainability orientation has on reward-based crowdfunding by focusing on how sustainability orientation influences funder’s trust and investment intention. Aim: This research aims to uncover how sustainability orientation influences funder’s trust and investment intention in reward-based crowdfunding projects. Methodology: A quantitative study will be conducted through an online questionnaire. Two real-life crowdfunding projects will be taken from Kickstarter: One crowdfunding project with a sustainability orientation and one without. Both will be presented to the respondents through an online questionnaire. Contributions: This study contributes to close the gap present within the crowdfunding literature on how sustainability orientation impacts crowdfunding. From a practical viewpoint, it enables entrepreneurs to more accurately predict the funder’s investment intention for their crowdfunding project. Furthermore, the study provides social entrepreneurs with a framework to garner funders’ trust in reward-based crowdfunding projects, increasing the likelihood that the crowdfunding project succeeds. From a societal perspective, this study will help to understand the importance of sustainability for everyday crowdfunding projects, which helps to make sustainability in crowdfunding more mainstream.
A Wireless Power-Free Pressure Sensor for Real-TimeIn VivoGastrointestinal Pressure Monitoring

A wireless and power-free pressure sensor system capable of real time in vivo gastrointestinal pressure monitoring has been developed. This system contains a sensor unit and a detection unit. Based on mutual inductance detection mechanism, the sensor is featured with simple device structure and therefore low cost. The packaged sensor unit was tested. Results obtained from experiment demonstrated that this sensor has a sensitivity of 0.2115 kHz / kPa within a pressure range-10~30 kPa. The in vivo testing result not only indicates a period of 2 contractions per minute peristalsis of rabbit stomach but also validates the feasibility of this real time wireless gastrointestinal pressure monitoring system.
User‐Vendor Relationships in the Scottish Electronics Industry

User‐vendor relationships are examined in a sector of the electronics industry where the manufacturing process is sensitive to the performance of vendors in terms of price, quality and delivery. Two similar user companies with different vendor management approaches are considered and the effects these have on vendor performance and the subsequent results for aspects of the companies' performance examined. Vendors supplying both companies were interviewed on the rationale of their behaviour towards the companies. It is shown how, for this type of manufacturing process, forgoing short‐term price opportunities by developing long‐term relationships with vendors can lead to greater overall benefits for the manufacturing process.
Exploring the Influence of Self-determination in the Collective Intelligence of Collaborative Organizations

In recent years, positive correlations between some factors of collaborative group task processes and the increasing of collective intelligence (CI) have been presented. This work introduces an hypothesis that argues the existence of a new factor of positive influence for the increasing of collective intelligence in collaborative group tasks operating in cooperative environments: self-determination . Therefore, we present an argumentation based on Cooperative Multiagent Systems that spotlights the significance of self-determination in these particular environments. Furthermore, we also introduce a preliminary design of an experimental setup and a methodological framework for validating the hypothesis empirically in human organizations. Our propose consists on measuring, on the one hand, the level of self-determination from the individuals that participate on the decision-making processes
Bagging Model for Product Title Quality with Noise ∗

We present our winning approach for the Lazada Product Title Quality Challenge for the CIKM Cup 2017 where the data set was annotated as conciseness and clarity by Lazada QA staffs. The participants were asked to build machine learning model to predict conciseness and clarity of an SKU based on product title, short description, product categories, price, country, and product type. As sellers could freely enter anything for title and description, they might contain typos or misspelling words. Moreover, there were many annotators labelling the data so there must be disagreement on the true label of an SKU. This makes the problem difficult to solve if one is solely using traditional natural language processing and machine learning techniques. In our proposed approach, we adapted text mining and machine learning methods which take into account both feature and label noises. Specifically, we are using bagging methods to deal with label noise where the whole training data cannot be used to build our models. Moreover, we think that for each SKU, conciseness and clarity would be annotated by the same QA. It means that conciseness and clarity should be co-related in a certain manner. Therefore, we extended our bagging approach by considering out of fold leakage to take advantage of co-relation information. Our proposed approach achieved the root mean squared error (RMSE) of 0.3294 and 0.2417 on the test data for conciseness and clarity , respectively.
Secondary control in islanded smart distribution systems considering renewable resources and energy storage: A centralized approach based on convex optimization

This thesis proposes a receding horizon strategy for the secondary control of islanded microgrids. The proposed control takes into account the action of the primary control as well as the references given by the tertiary control. A convex optimization model is solved in each time step, based on a linear approximation of the frequency-dependent power flow equations. The main objective of the control is to carry out frequency and voltages to suitable values, taking into account capacity limits of renewable sources and energy-storage devices. As shown along this document, there are several techniques implemented to deal with the secondary control problem in scientific literature. Neveretheless, the innovation of this proposal lays on the fact that using convex optimization, as a tool for the receding horizon scheme and the hierarchical control structure, allows the algotithm to reach the global best solution that reduces the system frequency deviation around the nominal value. Numerical experiments on the CIGRE low-voltage benchmark test system were implemented to demonstrate the performance of the proposed control. The algorithm has demonstrated that under different load scenarios the best solution is found.
HEIGHTS OF AUTOMORPHIC FORMS AND MOTIVES

The “height” of a cohomological automorphic form is, roughly speaking, the L2 norm of an integrally normalized representative for the cohomology class. We conjecture this notion is closely related to the the Kato-Koshikawa arithmetic height of the associated motive, and examine how this conjecture is related to the Bloch-Kato conjecture for the adjoint L-function.
Novel Teletraffic Analysis of GSM/EDGE Orthogonal Sub Channel (OSC) and Application to Spectrum Re-farming

Abstract GSM network operators are required to free up some of the spectrum allocated for voice traffic in order to serve 3G and 4G users. Re-farming 900 MHz and 1800 MHz bands into HSPA, W-CDMA (UMTS) and LTE is a challenge faced by operators with growing GSM voice traffic as 3G systems require 5 MHz bandwidth which is 25 times more bandwidth than a typical GSM channel. 4G systems (LTE) may even use 10 MHz to show superiority over the 5 MHz 3G systems. It is required to cope with the GSM voice traffic with significantly less bandwidth in order to accommodate 3/4G users. Orthogonal Sub Channel (OSC) is a novel technique offering efficient hardware utilization that can result in doubling GSM voice capacity. This is achieved by allowing two users to share the same physical radio resources. OSC can be used in phasing-out GSM networks to release significant frequency spectrum for 3/4G users. In this work, a thorough analysis on OSC performance gain is presented. The hard capacity gain offered by OSC is calculated as a function of the OSC penetration and compared with system level simulations. It is shown that hard capacity can be maintained with less number of TRXs (transceivers), and consequently, narrower spectrum. This paves the way for re-farming the released GSM spectrum into 3/4G traffic.
Optimal household energy management using V2H flexibilities

Purpose – The use of energy storage devices helps the consumers to utilize the benefits and flexibilities brought by smart networks. One of the major energy storage solutions is using electric vehicle batteries. The purpose of this paper is to develop an optimal energy management strategy for a consumer connected to the power grid equipped with Vehicle-to-Home (V2H) power supply and renewable power generation unit (PV). Design/methodology/approach – The problem of energy flow management is formulated and solved as an optimization problem using a linear programming model. The total energy cost of the consumer is optimized. The optimal values of decision variables are found using CPLEX solver. Findings – The simulation results demonstrated that if the optimal decisions are made regarding the V2H operation and managing the produced power by solar panels then the total energy payments are significantly reduced. Originality/value – The gap that the proposed model is trying to fill is the holistic determination.