Miracle-dz/UniFAR-FTUs huggingface dataset:
DESIGN OF CONTROLLER FOR MIXED DATA TYPE - A COMPOSITE FUZZY-NEURAL APPROACH

Input feature vectors in feed-forward neural network are generally processed by linear separation through plane or hyperplane. But discrete features are difficult to feed into these nonlinear computational processing elements. Even if the processing is carried out using some encoding mechanisms of quantization, retaining information of the original categorical variables appears to be difficult at times. This paper proposes a methodology to design an online controller through fuzzification of the discrete input features first and, then through supervised learning based on adaptive neuro-fuzzy inference system (ANFIS). Continuous feature spaces are processed simultaneously through multi-layered perceptrons (MLP) and both the systems are connected through a linear filter for prediction of response variables using log-likelihood cost function. This proposed architecture has been tested on standard data set for its efficacy. The system is proven to be more efficient as compared to the existing methods in terms of error metrics. The estimation is independent of the number of discrete input features and in case if the data set has several categorical features, this method will still be more effective than the available systems.
Analytical Study Guideline for Structural Health Monitoring of Steel Canister in Dry Cask Storage System by Using Multimodal Ultrasonic Lamb Waves

Guided Lamb waves have been successfully used for some years as a monitoring technique for damage in plates and pipes. Multimodal Lamb waves are typically observed in thick structures, e.g. steel canisters in dry cask storage systems. Different modes have different sensitivity for certain types of cracks, and it is usually desired to excite specific symmetric or antisymmetric Lamb wave modes. To quantify the participation of different modes, it is important to know the power that each mode shares when exciting multiple modes. This study presents an analytical development and numerical simulations of wave power distribution between different ultrasonic Lamb wave modes using normal mode expansion (NME) technique. Piezoelectric wafer active sensor (PWAS) transducers were used to excite ultrasonic Lamb waves in the structure. The interaction between the PWAS and the structure was studied. Numerical simulations were performed for (1) thin aluminum plate (1-mm) in which one symmetric and one antisymmetric modes exist, (2) thick steel plate (1⁄2") in which three symmetric and three antisymmetric modes exist. In the later case study, power partition between the 6 modes was presented, and a parametric study was performed for different transducer sizes and excitation frequencies.
Synthesis of Mesoporous Silica-Alumina from Lapindo Mud Using Gelatin from Catfish Bone as a Template: Effect of Extracting Temperature on Yield and Characteristic of Gelatin as well as Mesoporous Silica-Alumina

Mesoporous silica-alumina was synthesized from silica and alumina extracted from Lapindo mud with gelatin from catfish bone as a template. The bone was refluxed in demineralized water at 60, 70, 80 and 90 °C to extract the gelatin. Gelatin was analyzed by FTIR and SDS-PAGE. The alumina was separated from the mud by reflux method using HCl solution and the silica was separated form mud by reflux method using NaOH solution. The purity of silica and alumina were determined by XRF. The mesoporous silica-alumina was synthesized using SiO2 and Al2O3 from Lapindo mud and the catfish gelatin as a template under hydrothermal method at 100 °C for 24 h and calcined at 500 °C for 5 h and characterized by TEM and N2 adsorptiondesorption. The yield of extracted gelatin at 60, 70, 80 and 90 °C was 4.79%, 6.09%, 8.13% and 12.24. %, respectively. The purity of silica and alumina extracted from Lapindo mud were 100% and 89.69%. The synthesized silicaalumina showed mesoporous characters and had pore diameter of 105.14 Å, pore volume of 0.1974 cc/g and BET surface area of 75.105 m 2 /g.
Updating river basin models with radar altimetry Updating river basin models with radar altimetry

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Effect of Chess Training on Math Problem-Solving Ability of Elementary School Students

In this paper, we present the background and the results of a research on the effect of chess training on math problem-solving ability of elementary school students. This paper is an empirical study and is designed with pretestposttest control-group. The goal of this paper is to determine whether chess training affects the math problemsolving ability of fifth grade elementary school students. Thus, 25 male students were recruited as the experimental group from the fifth grade students of one of the southeast provinces of Iran using cluster random sampling; they were trained in chess for a period of six months. Another group consisting of 41 students was chosen as the control group. Both pretest and the posttest were based on the textbook content of fifth grade of the elementary school. Cronbach Alpha was used to determine the reliability; and for validity, the mean of the experts’ opinion was used as the criteria. Fifty-two chess training sessions were held as the educational intervention. The results show that the students who were under chess training (the experimental group) were better at math problem-solving than the control group (non-chess players). These results suggest that chess can be applied as an effective training tool to improve math problem-solving ability of the students.
Physically Based, Scalable SPICE Modeling Methodologies for Modern Power Electronic Devices

Efficient power electronic design hinges on the availability of accurate and predictive SPICE models. This paper proposes novel physical and scalable SPICE models for power electronic semiconductors including wide−bandgap devices. The models are based on process and layout parameters, enabling design optimization through a direct link between SPICE, physical design, and process technology. The models are used as key design components during technology development and for the proliferation of new products.
Recommendation of cold start product by socializing e-commerce

- Now a days online shopping has achieved a tremendous popularity within very less amount of time. Recently few ecommerce websites has been developed their functionalities to a extent such that they recommend the product for their users referring to the connectivity of the users to the social media and provide direct login from such social media (such as facebook, Google+ ,etc). For recommending the users that are totally new to the websites, we use novel solution for cross-site cold-start product recommendation that aims for recommending products from e-commerce websites. In specific, we propose learning both users and products feature representations from data collected from e-commerce websites using recurrent Matrix Factorization to transform user’s social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can manipulate the learnt user implanting for cold-start product recommendation.
A Stochastic Approach to LCA of Internal Insulation Solutions for Historic Buildings

Internal insulation is a typical renovation solution in historic buildings with valuable façades. However, it entails moisture-related risks, which affect the durability and life-cycle environmental performance. In this context, the EU project RIBuild developed a risk assessment method for both hygrothermal and life-cycle performance of internal insulation, to support decision-making. This paper presents the stochastic Life Cycle Assessment method developed, which couples the LCA model to a Monte-Carlo simulation, providing results expressed by probability distributions. It is applied to five insulation solutions, considering different uncertain input parameters and building heating scenarios. In addition, the influence of data variability and quality on the result is analyzed, by using input data from two sources: distributions derived from a generic Life Cycle Inventory database and “deterministic” data from Environmental Product Declarations. The outcomes highlight remarkable differences between the two datasets that lead to substantial variations on the systems performance ranking at the production stage. Looking at the life-cycle impact, the general trend of the output distributions is quite similar among simulation groups and insulation systems. Hence, while a ranking of the solutions based on a “deterministic” approach provides misleading information, the stochastic approach provides more realistic results in the context of decision-making.
ESRC SEMINAR SERIES: Restorative Approaches to Conflict in Schools

Introduction This paper reflects on using Restorative Approaches (RAs) with children and researching their impact. It draws on two research projects in different settings funded by local authorities, using different restorative approaches: FGCs (Family Group Conferences) in mainstream schools (see Hayden, 2009) and Restorative Justice in children’s residential care (Hayden and Gough, 2010). The paper sets out to consider how these two practical projects understood, used and demonstrated key values and practices associated with Restorative Approaches. In so doing it considers the transferability of Restorative Approaches to different contexts that care for children. Considerations to do with research design and ‘findings’ are presented to encourage discussion about how we go about researching RAs in a climate where performance management strongly influences ‘success’ criteria and how Children’s Services have to operate.
How Does the Stability of Loan Relations Depend on its Duration? Evidence from Firm- and Bank-Level Data

This paper empirically studies the stability of loan relations between Japanese listed rms and banks. By using a unique data set for Japanese bank loan market, rst, we estimate the hazard function for the loan relations through nonparametric duration models. Then, with considering empirical ndings that bank loan relations are systematically governed by the characteristics of rms, banks, and matches, the stability of relations is formally examined through semi-parametric and parametric duration analyses. The results support the existence of relationspeci c capital discussed in the theoretical literature. Key words: Bank loan relation; Stability; Duration analysis JEL Classi cation: G21, G32, C41 I thank Hugo Hopenhayn, Andy Atkeson, Lee Ohanian, Daniel Ackerberg, Isabelle Perrigne, Christian Hellwig, Pierre-Olivier Weill, Pierre-Yves Yanni, Shogo Hamasaki, Junichi Nakamura, Keiichiro Oda, Pramuan Bunkanwanicha and seminar participants at UCLA Monetary Economics Proseminar, Industrial Organization Proseminar, and DBJ Applied Economics Workshop for useful comments and suggestions. yResearch Institute of Capital Formation, Development Bank of Japan, 1-9-3 Otemachi Chiyoda-ku, Tokyo, 100-0004 JAPAN. E-mail: damiyak@dbj.jp.
Synthesis and characterization of photo-crosslinked poly(carbonate anhydrides)

Biodegradable poly(carbonate anhydrides) based on poly(trimethylene carbonate) were synthesized by ring-open-ing polymerization. The hydroxyl-terminated oligomers were acid-functionalized with succinic anhydride and subsequently methacrylated to obtain photo-crosslinkable three-armed macromers with anhydride bonds. The degree of acid-functional-ization was over 96%, and the degree of methacrylation was over 80%. The macromers were photo-crosslinked into networks at room temperature in a nitrogen atmosphere. In vitro degradation experiments in phosphate-buffered solution (pH 7.4) at 37°C showed that the networks degraded rapidly with complete mass loss within 72 h. For networks prepared from the higher molecular weight, the presence of an alkenyl chain in the anhydride bond resulted in lower water uptake and conse-quently in a decrease in the degradation rate. The degradation mechanism of these networks showed characteristics of surface erosion.
REAL UNIT LABOR COSTS AND OUTPUT IN BUSINESS CYCLE MODELS: AN EMPIRICAL ASSESSMENT

Modern macroeconomic models of business cycle, which are based on real business cycle models enhanced by various types of both nominal and real rigidities, work with a relation between price inflation and real marginal costs, which captures the sources of inflation introduced much earlier as the Phillips curve. Although it is possible to formulate the relationship with output gap or unemployment gap instead of real marginal costs, it is the formulation with real marginal costs which dominates both in theoretical and empirical analysis. The paper uses VAR models with measures of real activity, inflation, exchange rate and interest rate as endogenous and measures of output of the German economy and oil price as exogenous variables to examine the behavior of real unit labor costs as a proxy for real marginal costs in a business cycle framework in cases of the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland and Slovakia. The results differ significantly across the sample, which means a differentiated approach must be taken when estimating such a relationship.
EFFECT OF IRON SUPPLEMENTATION AND NUTRITIONAL EDUCATION AMONG IRON DEFICIENT AND IRON DEFICIENT ANEMIC FEMALE ADOLESCENTS IN THE GAZA STRIP-PALESTINE

Iron deficiency (ID) is the most common form of malnutrition worldwide, affecting more than 2000 million people globally. Iron deficiency anemia (IDA) is highly widespread in developing countries. Adolescent female constitute about fifth of total female population in the world. Adolescent is one of the most challenging period in human development. The sudden changes create nutritional needs. As a period of growth and development, is considered the best time to intervene, to assist in physical and mental development, and to prevent later maternal anemia. The prevalence estimates of IDA among adolescents is 30–55% worldwide. Adolescence is an opportune time for interventions to address anaemia. Not only is there a need (growth, preparation for pregnancy), but large numbers of both male and female adolescents can be reached easily if school attendance or participation in other group activities is high. Also, adolescents are open to new information and new practices since they are often striving for physical or academic excellence. The present study designed to determine the prevalence of anemia, ID and IDA and to study the efficacy of iron-supplementation and nutritional education on hemoglobin and ferritin levels among female adolescents aged 15-19 years living in the Gaza strip-Palestine. The study has two phases: the first phase will be a cross sectional descriptive study, which will enroll randomly 374 female students aged 15-19 years in the Gaza strip-Palestine. The study population in the study is female students enrolled in the secondary schools. Five female secondary schools will be selected randomly from five governorates in the Gaza strip. In each school, one to two classes of each grade will be selected randomly as well. According to the list of the student’s names, the subjects will be selected upon odd number in the school records. The second phase is randomized controlled trial (intervention phase) that will be divided into three groups; the first group for iron supplementation, the second for nutritional education intervention and the last as control group. Data will be collected by questionnaires, anthropometric measurements, complete blood counts (CBC) and serum ferritin will be analysed. All ID and iron deficient anemic female adolescents will be monitored to evaluate the effectiveness of iron supplement and nutritional education. Statistical package for social science (IBM-SPSS) version 22 will be used for analysis of data.
Teacher’s Competency and Self-Efficacy Beliefs as the Predictor of Attitude towards Teaching Profession

Accepted: 24.10. 2014 Many studies have focused on finding the level of effect that teacher’s competency, self-efficacy beliefs and teaching profession have had on teaching profession, and providing a separate explanation ratio for each. The relationship among the effects of the teacher competency beliefs, teacher self-efficacy beliefs and attitude towards teaching profession with each other and explanation ratios of relationships to each other were tested in this research. Participants in the study consisted of a total of 417 teacher candidates enrolled in the first and second grade in Faculty of Education, at Private University in Anatolian part of Turkey. The data collected during spring semester of the 2013-2014 academic year. This study conducted to use the relational survey model. Scale of Teachers’ Competency Beliefs, Scale of Teachers’ Self-Efficacy Beliefs and Attitude Scale of Teaching Profession were used as data collection instruments. Data were analyzed via SPSS 16.0 and AMOS 17.0 softwares. The result of this study indicated that teacher competency beliefs and teacher self-efficacy beliefs together significantly and positively affect and account for attitude towards teaching profession. The finding of this study is also found that teacher competency beliefs and teacher self-efficacy beliefs are crucial predictors of the attitude towards teaching profession.
From the editor: new frontiers

Articles Page 21 Resource caravans and resource caravan passageways: a new paradigm for trauma responding Stevan Hobfoll Page 33 War experiences, daily stressors and mental health ¢ve years on: elaborations and future directions Kenneth E. Miller & Andrew Rasmussen Page 43 Addressing collective trauma: conceptualisations and interventions Daya Somasundaram Page 61 Using mixed methods to build knowledge of refugee mental health StevanMerrillWeine, Aqsa Durrani & Chloe Polutnik Page 78 Guidelines for the implementation of culturally sensitive cognitive behavioural therapy among refugees and in global contexts Devon E. Hinton & Baland Jalal Page 94 Dissemination and implementation of evidence based, mental health interventions in post con£ict, low resource settings Laura K. Murray, Wietse Tol, Mark Jordans, Goran Sabir, Ahmed Mohammed Amin, Paul Bolton, Judith Bass, FranciscoJavier BonillaEscobar&GrahamThornicroft Page 113 The role of mental health and psychosocial support nongovernmental organisations: re£ections from post con£ict Nepal Nawaraj Upadhaya, Nagendra P. Luitel, Suraj Koirala, Ramesh P. Adhikari, Dristy Gurung, Pragya Shrestha, Wietse A. Tol, Brandon A. Kohrt & MarkJ.D. Jordans
IMPROVED EFFICIENCY AND REAL TIME TEMPERATURE MONITORING IN THE FOOD SUPPLY CHAIN

Within the EC Project CHILL-ON, supply chain management of perishable food is seen as the process of planning, implementing, and controlling operations to ensure traceability and maintain low temperature as efficiently as possible. The key issues in food production, namely safety coupled with industry's demand for transparency and quality assurance, are the main objectives of the various tools being developed in the project. The concept of the Chain Information Management System, called “TRACECHILL”, is to tackle the most crucial points and design and implement novel solutions for the cold chain. This includes chilling technologies, real time temperature monitoring, logistic traceability, smart labels as time temperature indicators (TTIs) and molecular diagnostic tools (qPCR) for pathogenic and spoilage bacteria. Quantitative Microbial Risk Assessment and Shelf Life Prediction models have been developed and linked with a decision support system for immediate responses to potential hazards in the food supply chain.
Picosecond laser induced selective removal of functional layers on CIGS thin film solar cells

Picosecond laser pulses provide a controlled laser based removal used for micro structuring of functional layers, such as copper-indium-gallium-diselenide (CIGS), due to a reduced thermal penetration depth, compared to nanosecond pulses. It is shown that with 7 ps pulse width at a wavelength of 532 nm the P2 and P3 processing of thin film solar cells on glass substrates and flexible polyimide substrates is possible. A Gaussian as well as a top-hat energy distribution were utilized for the experiments. With adjusted laser and processing parameters they allow for the fabrication of precise isolation trenches (width << 100 © 2013 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of the German Scientific Laser Society (WLT e.V.)
Optimization Algorithms of the Industrial Clusters’ Innovative Development Programs

The article considers the task of forming an effective program of innovative processes’ management in the territorial industrial clusters as a problem of the knapsack with its own values of items’ combinations for whose solving a wide class of algorithms can be used. Due to the NP-completeness of this problem and in order to reduce the time of calculations it is proposed to use approximation algorithms (such as greedy algorithm), allowing to get results close to the optimal solution. It is shown that another approach to the practical implementation of approximating algorithms can be considered an approach based on the use of artificial Hopfield network, which can be attributed to the class of optimizing networks (filters). In contrast to already known algorithms for solving the knapsack problem the algorithms which are considered additionally take into account the possible synergistic effects from the joint implementation of selected activities of the innovative processes’ management program in the territorial industrial clusters. The authors proposed the structure of an artificial neural Hopfield network and the recommendations on the choice of energy function consisting of three components: representing the target function in the form maximizing the effect of the programme activities’ implementation, effectuating restrictions on the validity of the solution and maximizing the synergistic effect of selected events’ combinations. The results of computational experiments of the speed rating approximation algorithms and the degree of closeness of the result to the exact solution showed that, in practice, to solve this problem in the presence of high-speed computers and a relatively small set of events (less than 200), it is advisable to use algorithms «intelligent brute force». With tight time constraints to develop solutions for high-dimensional problems (over 500 events) and the lack of critical accuracy requirements to the result it is possible to apply a «greedy» algorithm. In the cases when in a relatively short time with high-dimensional problems it is necessary to obtain an exact solution, neural network algorithm based on Hopfield network is preferred. Selected depending on the initial problem conditions, algorithms described in the article can be used as a component of algorithmic support of decision-making information systems for innovation management, being implemented in the industrial clusters of different types.