Miracle-dz/UniFAR-FTUs huggingface dataset:
On-Line Social Network Sites and Negative Social Capital, The Influences in Albanian Economy

In the terminology of political economy made a distinction between quantitative economic policy and structural economic policies. Quantitative policies are policies aimed at controlling short-term economic cycles through quantitative interventions: fiscal stimulus (decrease or increase taxes and / or government spending), the increase or decrease of the rate of interest, intervention by monetary policy; in other words, the policy aimed at orienting the economy in one or another direction through management macroeconomic parameters. These are policies which in most cases common concern to economists and state fiscal bureaucracy (such as ministries of finance or central bank), or even ideological opposite orientations politicians express the necessity of one or another kind. These groups often finds in dealing with economic problems dealing with the need for or the effects of this kind: for example, given arguments for the necessity of lowering taxes to businesses in order to encourage investment; need for to stimulate demand through increased public spending; debate on the reduction or increase of VAT or excise or tax rates etc. Foundation is totally debate revolves around the use of the macroeconomic mechanisms in response to cyclical economic developments. In this paper we want to illustrate the facts that both means of supplying markets exporting and production in those markets. Moreover, there are two international business activities that we are studying in our paper research. The main hypothesis is: “Is there a negative “Social Capital”? The database includes 1000 questionnaire about 50 relevant variables (collected during April, May, and June 2011 in Vlore city). The statistical program SPSS is used for creating, testing econometric models which links economic, social and demographic attributes of Internet users with frequencies of accessing / using of the Internet. The paper aims to reach conclusions for the city of Vlore, Albania, to figures out the chances that youth spend hours in Internet contributing in a negative “Social Capital”. DOI: 10.5901/ajis.2014. v3n1p157
Panduan Self Instruction dengan Pendekatan Structured Learning Approach untuk Menurunkan Prokrastinasi Akademik Siswa SMP

<div align="center"><table width="645" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="439"><p><strong>Abstract:</strong> The purpose of this research is to produce a training guide product that meets the acceptance criteria. This study uses Borg & Gall model research design. The data obtained in the form of quantitative data include aspects of accuracy, utility, propriety, and feasibility. The research subjects are BK experts, media experts, and potential users. The research instrument included BK experts instruments, media experts instrumen and scale of procrastination. Data analysis techniques used an interater agreement. The results show that the results from BK have a validity index 0,73 "medium" category, from media experts is 1 category "very high", and from prospective users is 1 "very high" category. It can be concluded that the developed guide meets the product acceptance criteria. </p><p class="Abstract"><strong>Abstrak:</strong><em> </em>Tujuan dalam penelitian ini adalah menghasilkan produk panduan pelatihan yang memenuhi kriteria keberterimaan. Penelitian ini menggunakan rancangan penelitian Borg & Gall. Data yang diperoleh berupa data kuantitatif mencakup aspek ketepatan, kegunaan, kemenarikan, dan kelayakan. Subjek penelitian yaitu ahli BK, ahli media, dan calon pengguna. Instrumen penelitian yang digunakan mencakup instrumen uji ahli BK, uji ahli media dan skala prokrastinasi. Teknik analisis data menggunakan <em>interater agreement. </em> Hasil uji lapangan menunjukkan hasil penilaian dari ahli BK memiliki indeks validitas sebesar 0,73 kategori “sedang”, dari ahli media yaitu 1 kategori “sangat tinggi”, dan dari calon pengguna yaitu 1 kategori “sangat tinggi”. Dapat disimpulkan bahwa panduan yang dikembangkan telah memenuhi kriteria keberterimaan produk. </p></td></tr></tbody></table></div>
Broadband UHF RFID tag antenna with parasitic patches for metallic objects

A novel low‐profile broadband UHF RFID tag antenna with two parasitic patches is proposed.The tag antenna's bandwidth can be greatly enhanced by adding parasitic patches which are gap coupled to the driven patch for the excitation of additional resonant modes. The half‐power bandwidth of the proposed antenna covers all the UHF RFID frequency bands, and the power reflection coefficient is lower than −7dB in the UHF RFID frequency bands (840–960 MHz). The proposed antenna can be easily fabricated at low cost by etching at a thin inexpensive FR4 substrate. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26049
Hybrid swarm evolutionary programming for optimal distributed generation in distribution system

This paper discusses the incorporation of the Hybrid Swarm Evolutionary Programming (SEP) for optimal distributed generation (DG) in the distribution system. High load demand will result in unstable control power distribution due to power transmission loss. The compensation process can be implemented by installing a compensation device to prevent this from happening. It is required the optimal sizing and location for the devices to achieve the objective and this can be done by using an optimization technique. Thus, this project aims to develop a hybrid computational intelligence technique is called hybrid SEP for loss minimization. The proposed method embedded the element of Particle Swarm Optimization (PSO) into traditional Evolutionary Programming (EP) to improve precision of traditional EP algorithm. The purpose of this study is to investigate the maximum benefits of DG integration to be gained. The proposed techniques are validated on IEEE-69 bus radial system with multiple units of DG. The results showed that the most effective type of DG inject to IEEE-69 bus radial system is with DG Type III, with 95% of active power loss reduction and the best on voltage profile improvement. Hybrid SEP shows superior to EP in term of loss minimization.
Application of varying‐frequency amplitude‐only technique for electrical characterization of hardened cement‐based materials

There is a need for characterization of cement‐based materials by a simple and inexpensive microwave measurement setup for industrial applications. Nondestructive and contactless characterization of these materials can be realized by free‐space reflection/transmission measurements. Reflection measurements are convenient for applications where the sensor can only be placed on one side of the material such as measurements on pavement, backfilled concrete wall, and roadway. In this article, we use varying‐frequency amplitude‐only technique for electrical characterization of cement‐based materials using reflection measurements at three different frequencies. We have demonstrated that measurements by the proposed method are in good agreement with those obtained from reflection and transmission measurements. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52:801–805, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.25057
Differentiated Knowledge Bases and the Nature of Innovation Networks

It is argued in this paper that the nature of innovation networks can vary substantially with regard to the type of knowledge that is critical for innovation. Subject to the knowledge base of an industry, networks between companies can differ in various aspects, such as their geographical configuration, their structure, the type of actors holding a strategic position and the type of relations between actors. The paper comprises a conceptual discussion on social capital theory and networks, followed by a theoretically informed discussion on differentiated knowledge bases and innovation networks, which is subsequently illustrated with empirical material. The empirical analysis is based on social network analysis in association with exclusive data about patterns of cooperation and knowledge exchange in a number of regional industries located in different parts of Europe. The findings suggest that networks in analytical industries are not much constrained by geographical distance; knowledge is exchanged in a highly selective manner between research units and scientists in globally configured epistemic communities. Synthetic industries source knowledge within nationally or regionally configured networks between suppliers and customers, and within communities of practice. Symbolic industries rely on knowledge that is culturally defined and highly context specific, resulting in localized networks that are temporary and flexible in nature.
ZERO VOLTAGE SWITCHING IN THE PWM HALF BRIDGE TOPOLOGY WITH COMPLEMENTARY CONTROL AND SYNCHRONOUS RECTIFICATION

A ha&=bridge DClDC converter with cnmplementury control und seydriven synchronous rectifcution is described in this paper. Zero Voltage Switching is unutyzed taking into account the eflect of the parasitic capuci&unces the synchronous rectijers cf the secondury side. The main udvuntuges of this converter, that are high eficiency for bw output voltuge, sop-switching for priinary urui secondary switches ami very smuN output jfilrrr, are shown in an acfuul prototype.
Energy management system in hybrid trains using fuzzy control: a comparative study

In this article a fuzzy logic energy management system, for hybrid light weight trains, is designed and verified. The low axle load, medium-to-low speed, and short stopping distances are from characteristics of light rail vehicles, which make them suitable for implementing hybrid technology, as discussed in this article. In this research work, batteries and flywheels are considered as onboard energy storage devices and a light diesel generator as an onboard energy supply system. Efficient utilization of the mentioned energy sources throughout a cycle of movement from one stopping point to the next and also on the entire route is the aim of the energy management system, investigated in this article. The performance of the fuzzy logic energy management system, is analysed and compared with a standalone diesel and also a hybrid train using a thermostat on/off control strategy.
Detecção Inteligente de Retinopatia Diabética com Redes Neurais Convolucionais Profundas

—This work describes the experimental results of using Convolutional Neural Networks to detect diabetic retino-pathy in medical images. Canonical architectures were considered and the best results obtained have F 1 - Score equal of 75 . 83 % with Inception architecture, highlighting the potential of using such models in this Medical Imagiology problem.
Causality between terrorism and economic growth

This article analyzes the causal relationship between terrorism and economic growth, running a series of tests for Granger non–causality with panel data for a maximum of 160 countries from 1970 to 2007. The authors find that the causal relationship between terrorism and growth is heterogeneous over time and across space. They argue that the temporal causal heterogeneity can be explained by shifting geographical and ideological patterns in terrorism associated with the end of the Cold War. Different causal mechanics across countries are ascribed to a variety of country–specific factors (the level of politico–economic development, a country’s cultural affiliation, the intensity and persistence of terrorist activity, and the level of political instability). These factors govern a country’s robustness to shocks from terrorism and the extent to which terrorism is motivated by economic factors. For the Cold War era, economic growth is found to have swayed terrorism for Latin American countries in intermediate development positions that were politically unstable and experienced strong terrorist activity. For the post–Cold War era, terrorism is found to be detrimental to growth for African and Islamic countries with low levels of political openness, high levels of political instability, and strong terrorist activity. The study’s findings help to better understand the conflicting evidence on the terrorism–economy nexus and to give more solid counter-terrorism advice.
Redução de Ruído em Implantes Cocleares utilizando uma Rede Neural Recorrente baseada na Estimação da Envoltória da Fala

— This work presents a noise reduction method for cochlear implants using a recurrent neural network. Learning is performed from estimates of the noisy speech power and an ideal time-frequency mask, which aims to estimate the speech envelope. Computational simulations using an objective criterion indicate a significant intelligibility increase in comparison with the practical implementation (using a real signal to noise ratio estimator) of the mask employed in the training phase. The results obtained suggest that the recurrent neural network performance gets closer of the ideal mask in the analyzed scenarios.
The effect of mycorrhizal inoculation and liquid organic fertilizer on growth and yield of red chili

Red chili is one of the strategic horticultural commodities in Indonesia. Improved cultivation technology is required to increase the production of red chili. This research aim to determines the optimal dosage of arbuscular mycorrhizal fungi (AMF) and the concentration of liquid organic fertilizer (LOF) to increase the growth and yield of red chili. The research was designed in a Factorial Randomized Complete Block. The first factor was mycorrhizae with three dosages levels: 0, 5, and 10 g plant-1. The other factor was liquid organic fertilizer with 4 level concentrations of 0, 5, 10, and 15 ml l-1. The result shows that mycorrhizal inoculation increase the root absorption area. Liquid organic fertilizer increased nutrient sources for plants and improved the physical, biological, and chemical soil. Mycorrhizal inoculation and LOF improved the growth of red chili, there were plant height, number of branches, stem diameter, header width, and leaf area index. The yield components also increased the number of fruit, fruit length, fruit weight, and productivity. The highest productivity was resulted by the treatment of AMF 10 g plant-1 and 15 ml l-1 LOF (11.16 t ha-1), that was 33% higher than without treatment.
INFLUENCE OF VEHICLE MODEL COMPLEXITY IN AUTONOMOUS EMERGENCY MANOEUVRE PLANNING

In this paper the effectiveness of an optimal reference manoeuvre is analysed w.r. t. the complexity of the vehicle model used within the optimal control algorithm. The optimal reference manoeuvre is computed by means of a Nonlinear Receding Horizon planning (NRHP) strategy which is based on a simplified vehicle model. The reference manoeuvre is tracked by a controller implemented on a low level faster loop. The system is able to perform autonomously lane change and obstacle avoidance manoeuvres by tracking the computed reference one. The quality of the performed manoeuvres depends on the reference manoeuvre and consequently on the vehicle model used by the NRHP. For manoeuvres with low or mild lateral accelerations reduced order models might yield realistic and reliable reference manoeuvres. However, critical conditions (e.g. evasive manoeuvre) require a manoeuvre planner able to catch highly non-linear vehicle dynamics that characterizes such situations. On the other hand, being the NRHP computational cost generally high and related to the number of equations of the mathematical model, a trade-off between computational efficiency and model complexity is required. The work analyses the reference manoeuvres produced by two vehicle models of increasing complexity used as reference within the NRHP. Optimal planner performance evaluation on evasive manoeuvre in critical conditions will be presented with simulations results.Copyright © 2008 by ASME
Ant Colony Optimization Applied to Discrete and Continuous Structural Problems

Ant colony optimization is described and applied on two structural benchmark problems. The problems, being the gear ratio optimization and the geometrical optimization of a composite leaf spring, are chosen of discrete and continuous domain nature to investigate the effectiveness of the algorithm dealing with both types. The results compared with the global optimum obtained by enumeration or with the results of genetic algorithm clearly demonstrate the capabilities of ACO as a promising method to be used in structural optimization.
Control of PMSM chaos using backstepping-based adaptive fuzzy method in the presence of uncertainty and disturbance

This paper presents a novel nonlinear control strategy based on a backstepping fuzzy adaptive approach to avoid chaos in a synchronous motor. In the controller design and stability proof, the parameter uncertainty and the system disturbance are taken into account. The matching condition is not satisfied in this model, and disturbances with an unknown upper bound are also exerted on the system. The disturbance and uncertainty are considered in one manifold with an unspecified upper bound. The system stability is verified using the Lyapunov method. The cuckoo optimization algorithm is employed to optimize the adaptive and backstepping control coefficients.
Particle Swarm Optimization For Neural Network Learning Enhancement

Algoritma rambatan balik telah digunakan secara meluas dalam menyelesaikan pelbagai masalah dengan menggunakan konsep perceptron multi aras. Namun begitu terdapat banyak isu utama pada algoritma ini seperti kadar penumpuan yang lambat dan kekerapan terperangkap di dalam minimum setempat. Bagi mengatasi masalah ini, Algoritma Genetik (AG) digunakan untuk menentukan nilai yang optimal bagi mendapatkan parameter yang sesuai seperti kadar pembelajaran dan kadar momentum serta pengoptimuman pemberat. Walaupun AG berjaya meningkatkan keupayaan pembelajaran bagi Rangkaian Neural (RN) menggunakan rambatan balik, masih terdapat beberapa masalah lain seperti latihan untuk mengeluarkan output mengambil masa yang lama dan penggunaan fungsi yang rumit seperti perhitungan pilihan, silangan dan mutasi. Kajian ini mengemukakan teknik pengoptimuman yang terkini, iaitu pengoptimuman partikel secara berkumpulan yang dicerap di dalam proses pembelajaran RN, bagi meningkatkan masa penumpuan dan ketepatan pengelasan. Dua uji kaji telah dilaksanakan, iaitu RN ke hadapan menggunakan pengoptimuman partikel secara berkumpulan dan RN rambatan balik menggunakan AG. Hasil kajian mendapati bahawa RN ke hadapan dengan pengoptimuman partikel secara berkumpulan memberikan keputusan yang lebih baik dari aspek masa penumpuan dan ketepatan pengelasan, berbanding dengan RN rambatan balik menggunakan AG. Kata kunci: Partikel berkumpulan; rangkaian neural; algoritma genetik; rambatan balik; kepintaran berkumpulan Backpropagation (BP) algorithm is widely used to solve many real world problems by using the concept of Multilayer Perceptron (MLP). However, major disadvantages of BP are its convergence rate is relatively slow and always being trapped at the local minima. To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning and momentum rate and, also for weight optimization. Although GA has successfully improved Backpropagation Neural Network (BPNN) learning, there are still some issues such as longer training time to produce the output and usage of complex functions in selection, crossover and mutation calculation. In this study, Particle Swarm Optimization (PSO) algorithm has been chosen and applied in feedforward neural network to enhance the learning process in terms of convergence rate and classification accuracy. Two experiments have been conducted; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). The results show that PSONN give promising results in terms of convergence rate and classification accuracy compared to GANN. Key words: Particle swarm; neural network; genetic algorithm; backpropagation; swarm intelligence
Prediction of Turbulent Heat Transfer and Fluid Flow in 2D Channels Roughened by Square and Deformed Ribs

Introduction of roughness by ribs in flow passages is a popular method of enhancing heat transfer in the cooling passages, e.g., of turbine blades and combustors. It is essential to accurately predict the enhancement of heat transfer generated by the ribs to ensure good design decisions. In most of the studies square ribs have been considered, but in practice such ribs may appear rounded due to improper manufacturing or wear during operation. This study is focused on the effect of the rib deformations, based on computational fluid dynamics (CFD). One of the main difficulties in CFD is the reliable modeling of the underlying physics of the turbulence. This paper describes some recent efforts to validate and apply RANS-based models for predictions of turbulent flow and heat transfer in ribbed ducts, relevant to gas turbine cooling. The evaluated turbulence models include a basic low-Re k - e model (AKN), and two promising higher order models: namely, the explicit algebraic stress model (EASM), and the V2F model. All these models are validated with available 2D experimental heat transfer and fluid flow data. Some conclusions are reached on their suitable application situations. The effect of the roundedness on heat transfer and fluid flow is presented in detail. Some possible improvements, i.e., of the deformed ribs, are proposed to suppress the hot spots, and/or to enhance the overall thermal and hydraulic performance. (Less)
Competing Risk Analysis of Fuzzy Lifetime Data

—Competing risks arise in reliability and life- testing studies when units under test face the risk of failure due to multiple causes. In such studies, time to failure and cause of failure of units are observed, and competing risk analysis is carried out to assess failure behaviour of the unit due to any particular cause. In many cases, the time to failure of units might be reported imprecisely or inaccurately. The analysis of such data can be performed with higher accuracy by considering the lifetimes to be fuzzy. This paper discusses the maximum likelihood and Bayesian estimation of component reliability measures using fuzzy series system lifetime data. We carry out an extensive simulation study to observe the effect of different membership functions on the considered estimators. Finally, we analyse a real data set of small electric appliances.
A Bi-Directional Isolated DC/DC Converter as a Core Circuit of the Next-Generation Medium-Voltage Power Conversion System

This paper describes a bi-directional isolated dc/dc converter considered as a core circuit of 3.3-kV/6.6-kV high-power-density power conversion systems in the next generation. The dc/dc converter is intended to use power switching devices based on SiC and/or GaN, which will be available on the market in the near future. A 350-V, 10-kW and 20-kHz dc/dc converter is designed, constructed and tested. It consists of two single-phase full-bridge converters with the latest trench-gate Si-IGBTs and a 20-kHz transformer with a nano-crystalline soft-magnetic material core and litz wires. The transformer plays an essential role in achieving galvanic isolation between the two full-bridge converters. The overall efficiency from the dc-input to dc-output terminals is accurately measured to be as high as 97%, excluding gate drive circuit and control circuit losses from the whole loss. Moreover, loss analysis is carried out to estimate effectiveness in using SiC-based power switching devices. The loss analysis clarifies that the use of SiC-based power devices may bring a significant reduction in conducting and switching losses to the dc/dc converter. As a result, the overall efficiency may reach 99% or higher.