Miracle-dz/UniFAR-FTUs huggingface dataset:
The Use of Balanced Scorecard in Implementation of the User-Driven Innovation Concept

Customers play a crucial role in innovation processes. Their importance is proved by numerous theories and innovation models which put users and clients in the heart of innovation processes. One of the newest concept, popular in Scandinavian countries, picking up this thread is the User–Driven Innovation (UDI). To increase probability of innovation success consumers must be involved in the firm’s business model / innovation strategy, becoming a part of the innovation processes and all other stakeholders should be aware of the significance and character of the linkage between customer and company. As a result, building, implementing and monitoring of the customer–oriented innovation strategy should take place. The Balanced Scorecard (BSC) may turn out to be very helpful in achieving the above. The aim of this paper is to show that BSC may be a device of implementing the User–Driven Innovation concept, helping to understand UDI assumptions and the role of customers in creating value. Examples of strategic goals and performance indicators presented in this paper may be used by enterprises, which intend to build UDI-based BSC.
Search and navigation for photo collections

Images play a more and more important role in sharing, expressing and exchanging information in our daily lives. Accompanying this revolution, mobile hand-held devices with embedded digital camera are also undergoing considerable progress. A typical user can take hundreds of photos, save and stack them in a hard disk, remaining unlabelled and improperly organized. There is a need to develop new ways of photo searching in a personal collection and give users a better experience when browsing them. In this document, the key components of an image retrieval system for personal image collections are presented and various critical aspects of their design are studied. A content-based method of retrieving images using a computational model based on Wavelets has been implemented and evaluated. An image retrieval interface has been implemented, incorporating the ability to execute query-by-example in collaboration with keyword information. In order to simplify image navigation, an unsupervised image clustering framework has been implemented through an adaptation of the k-means algorithm. The clustering method is based on hierarchical image grouping using content-based and metadata features. Experimental results demonstrate the performance of the proposed clustering methods on a real image database. Also, a new visualization and interaction method of image browsing is proposed for mobile devices. This technique is based on the previously calculated image hierarchical structure and is aimed for an optimal ratio between displayed content and screen area usage.
Biodegradationof low-molecular-weightalkanesundermesophilic , sulfate-reducing conditions : metabolic intermediates and communitypatterns

Biodegradationof low-molecular-weightalkanesundermesophilic, sulfate-reducing conditions:metabolic intermediates and communitypatterns Kristen N. Savage, Lee R. Krumholz, Lisa M. Gieg, Victoria A. Parisi, Joseph M. Suflita, Jon Allen, R. Paul Philp & Mostafa S. Elshahed Department of Microbiology and Molecular Genetics, Oklahoma State University, Stillwater, OK, USA; Department of Botany and Microbiology and Institute for Energy and the Environment, University of Oklahoma, Norman, OK, USA; and School of Geology and Geophysics, University of Oklahoma, Norman, OK, USA
Solving Large-Scale Multi-Label SVM Problems with A Tree Decomposition Approach

We propose a tree decomposition approach for solving large-scale multi-label classication problems. In this approach, we follow a convention of rst transforming the problem into a number of one-against-others classication problems. Then, to solve each transformed problem, we use a decision tree to decompose the corresponding data space and train local SVMs on the decomposed regions. The resultant classier is called decision tree support vector machine (DTSVM). The approach has the following advantages. First, when nonlinear SVM is used as the learning machine, DTSVM requires much shorter training time than global SVM (gSVM) while achieving comparable test accuracy. Second, when linear SVM is used as the learning machine, DTSVM often achieves higher test accuracy than gSVM. Third, in textual applications, linear DTSVM plays the leading role among linear gSVM, non-linear gSVM, and non-linear DTSVM for the following reason. Linear DTSVM achieves higher test accuracy than linear gSVM; moreover, it achieves comparable test accuracy to, but requires much less training time than, non-linear gSVM and non-linear DTSVM.
Effect of a Bacterial Grass Culture on the Plant Growth and Disease Control in Tomato

This study aimed to investigate the plant growth-promoting and biocontrol potential of a grass culture with Paenibacillus ehimensis KWN8 on tomato. For this experiment, treatments of a chemical fertilizer (F), a bacteri al grass culture (G), a 1/3 volume of G plus 2/3 F (GF), and F plus a synthetic fungicide (FSf) were applied to to mato leaves and roots. The result showed that the severity of Alternaria solani and Botrytis cinerea symptoms were significantly reduced after the application of the bacterial grass culture (G and GF) and FSf. In addition, root mortality in G and GF was lower compared to F. Tomato plants treated with G or GF had better vegeta tive growth and yield compared to F. Application of G affected the fungal and bacterial populations in the soil. In conclusion, treatment with a bacterial grass culture decreased disease severity and increased tomato growth parameters. However, there were no statistically significant correlations between disease occurrence and tomato yields. This experiment presents the possibility to manage diseases of tomato in an environmen tally friendly manner and to also increase the yield of tomato by using a grass culture broth containing P. ehimensis KWN38.
Soil microorganisms in soil cleanup: How can we improve our understanding?

Successful in situ biodegradation must depend on microbial catalysis as well as physical transport. While there has been much effort directed toward understanding vadose zone transport processes, our understanding of the microbial ecology of the indigenous catalysts limits our ability to manage biodegradation processes in soil. The environmental factors commonly listed as controlling in situ biodegradation are water, oxygen, redox potential, nutrients, pH, and temperature. Simplistic statements concerning the environmental determinants of in situ biodegradation may reflect a naive understanding of microbial ecology and may in fact direct management efforts in inappropriate directions. We discuss what we need to know about soil microbial ecology to elevate in situ biodegradation to a reliable and well-understood remediation option. We need to know the following: What controls the presence of the desired metabolic capability; the distribution of degrading communities relative to contaminant source; and what controls activities of relevant communities? 45 refs., 7 figs., 1 tab.
Volatility behaviour of BRIC capital markets in the 2008 international financial crisis

Brazil, Russia, India and China (BRIC) are pointed as the most probable countries to enter the select group of industrialised countries, also appearing among the world’s twelve largest economies. The main objective of the present study is to assess whether the capital market behaviour of the BRIC’s emerging countries in the 2008 international crisis had already been equivalent to that of industrialised countries (USA, Japan, United Kingdom, and Germany). Three univariate approaches were applied for modelling the market volatilities (GARCH, EGARCH and TARCH). The results showed similar behaviours between both market groups regarding the presence of persistent effects of shocks on volatility, volatility asymmetry, and delayed volatility reaction to market changes. The BRIC’s markets showed less persistence to volatility shocks, less asymmetry, and faster reactions of volatility to market changes. Key words: Volatility, BRIC, emerging markets, GARCH models, financial crisis.
Reconfiguration of distribution systems to improve reliability and reduce power losses using Imperialist Competitive Algorithm

Distribution systems can be operated in multiple configurations since they arepossible combinations of radial and loop feeders. Each configuration leads to its own power losses and reliability level of supplying electric energy to customers. In order to obtain the optimal configuration of power networks, their reconfiguration is formulated as a complex optimization problem with different objective functions and network operating constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with objective functions of minimization of power losses, System Average Interruption Frequency Index(SAIFI), System Average Interruption Duration Index (SAIDI), Average Energy Not Supplied (AENS), and Average Service Unavailability Index (ASUI). The optimization problem is solved by the Imperialist Competitive Algorithm (ICA) as one of the most modern heuristic tools. Since objective functions have different scales, a fuzzy membership is utilized here to transform objective functions into a same scale and then to determine the satisfaction level of the afforded solution using the fuzzy fitness. The efficiency of the proposed method is confirmed by testing it on 32-bus and 69-bus distribution test systems. Simulation results demonstrate that the proposed method not only presents intensified exploration ability but also has a better converge rate compared with previous methods.
Technology and Standardization Strategies Related to The Diffusion of Smart Houses: The Case of ECHONET in Japan

In this paper, an analysis is made of the technology and standardization strategies regarding ECHONET and KNX, which are the de jure standards for smart houses in Japan and Europe. Eleven interviews with the main actors related to the ECHONET Consortium and KNX were conducted. Three research questions were set. What are the technology strategy related concerns of the main actors related to ECHONET? What are the issues related to the diffusion of smart houses? What are the underlying strengths and weaknesses of ECHONET when compared with KNX? The analyses showed that the strategies of the various actors towards the diffusion of smart houses were different, based on their different perspectives, visions and competences. A comparison between Japanese and European case highlighted the different standardization strategies and areas of focus. The main bottlenecks towards the diffusion of smart houses were identified.
Valuing the Environment through Contingent Valuation

Contingent valuation is now used around the world to value many types of public goods, including transportation, sanitation, health, and education, as well as the environment. The author describes how researchers go about making such surveys reliable, mentioning recent innovations in sampling, questionnaire design, and data analysis, including formulating the valuation as a closed-ended question about voting in a referendum to raise taxes for a particular purpose. He addresses various objections that contingent valuation results are incompatible with economic theory. Even without a market, there still exists a latent demand curve for nonmarket goods; contingent valuation represents a way to tease this out.
Mixture Modeling for Lifespan Developmental Research

As part of the Generalized Structural Equation Modeling framework, mixture models are person-centered analyses seeking to identify distinct subpopulations, or profiles, of participants differing quantitatively and qualitatively from one another on a configuration of indicators and/or relations among these indicators. Mixture models are typological (resulting in a classification system), probabilistic (each participant having a probability of membership into all profiles based on prototypical similarity), and exploratory (the optimal model is typically selected based on a comparison of alternative specifications) in nature, and can take different forms. Latent profile analyses seek to identify subpopulations of participants differing from one another on a configuration of indicators and can be extended to factor mixture analyses allowing for the incorporation of latent factors to the model. In contrast, mixture regression analyses seek to identify subpopulations of participants’ differing from one another in terms of relations among profile indicators. These analyses can be extended to the multiple-group and/or longitudinal analyses, allowing researchers to conduct tests of profile similarity across different samples of participants or time points, and latent transition analyses can be used to assess probabilities of profiles transition over time among a sample of participants (i.e., within person stability and change in profile membership). Finally, growth mixture analyses are built from latent curve models and seek to identify subpopulations of participants following quantitatively and qualitatively distinct trajectories over time. All of these models can accommodate covariates, used either as predictors, correlates, or outcomes, and can even be extended to tests of mediation and moderation.
Bacterial activity and genetic richness along an estuarine gradient (Rhone River plume, France)

Bacterial diversity and activity were simultaneously investigated by microbial ecological and molecular biological methods along an estuarine gradient from the Rhone River to the Mediterranean Sea. Following a Lagrangian strategy, we sampled plume, frontal and marine layers. The sampled estuarine gradient exhibited large changes both in physico-chemical and in microbiological characteristics. Bacterial abundances and activities showed a more drastic decrease in the low salinity range of the gradient than expected from simple dilution models, indicating that an important fraction of freshwater bacteria disappeared in the mixing area. High specific activities, in particular for leucine, in the marine end-part of the gradient suggested important bacterial protein synthesis, which may be a sign of an active survival strategy for bacterial communities subjected to oligotrophic conditions. Bacterial genetic diversity of the sampled estuarine area, as estimated by the number of DNA-derived denaturing gradient gel electrophoresis (DGGE) bands, was high (13 to 55 bands) compared to that reported in other aquatic ecosystems. This high diversity may be the consequence of the interface position of estuaries. The proportion of active populations was estimated using the ratio of DGGE bands derived from RNA and DNA. This ratio was lower in Rhone water than in marine water, indicating that only a part of the constitutive populations were active, while the activity was distributed within a larger fraction of populations in the marine assemblage. Very few DGGE bands detected in freshwater samples were also detected in the marine end-part of the gradient, suggesting that a very limited number of freshwater bacteria could survive under marine conditions. Detection of these freshwater populations from RNA might indicate that these bacteria were able to synthesize different stress proteins as the result of a survival strategy or that these bacteria were able to maintain metabolic activity under marine conditions. The structure of marine communities was strongly affected by decreasing salinity. However, it seems that the decrease of DNA-derived bands may simply have been the consequence of the mixing of marine and freshwater. No obvious relationship between genetic richness and activity changes was observed. This lack of a relationship may be the consequence of a very short residence time of water in the mixing area studied.
Sensör işaretlerinden cinsiyet tanıma için yerel ikili örüntüler tabanlı yeni yaklaşımlar

Son zamanlarda kimlik tanima basta olmak uzere, yas tanima ve cinsiyet tanima gibi konular hem akademik hem de diger alanlarda (sanayi, bilisim, saglik vb.) yaygin olarak uzerinde arastirma yapilan konulardandir. Cinsiyet tanima (CT) erkek ve kadin arasinda ayrim yapan ozelliklere dayali olarak bireyin cinsiyetini belirlemektir. Yapay zeka alaninda, CT oruntu tanima yonteminin en onemli uygulamalarindan biri olarak kabul edilmektedir. Bu calismada kisilerin 5 farkli bolgesine takilmis olan ivmeolcer, manyetometre ve jiroskop sensorlerinden elde edilen isaretler kullanilarak cinsiyet tanima (CT) icin uc (3) farkli oznitelik cikarim metodu onerilmistir. Isaretlerden oznitelik cikarimi CT’nin en onemli asamalarindan biridir. Cunku CT’nin basarisi cikarilan ozniteliklere baglidir. Ancak CT icin uygun ozniteliklerin cikarim zor bir problemdir. Sensorlerden elde edilen isaretlere Bir Boyutlu Yerel Ikili Oruntuler (1B-YIO), Bir Boyutlu Saglam Yerel Ikili Oruntuler (1B-SYIO) ve Agirliklandirilmis Bir Boyutlu Saglam Yerel Ikili Oruntuler (A-1B-SYIO) olmak uzere farkli donusum yontemleri uygulanmistir. Donusum islemlerinden sonra yeni olusan isaretlerde istatistiksel oznitelikler elde edilmistir. Bu oznitelikler kullanilarak farkli makine ogrenmesi yontemler (SVM, RF, YSA, Knn) ile siniflandirma islemleri gerceklestirilmistir. Elde edilen sonuclara gore 1B-YIO (%96.04), 1B-SYIO (%96.72) ve A-1B-SYIO (%97.28) yontemlerin CT icin etkin oznitelikler sagladigi gorulmustur. Bu calismada onerilen yeni yaklasimlar sayesinde sensor isaretleri kullanilarak CT isleminin yuksek bir basari orani ile gerceklestirildigi belirlenmistir.
The Potential Molecular Therapeutic Approach in Targeting Ovarian Clear Cell Carcinoma

Ovarian Clear Cell Carcinoma (OCCC) is a distinctive subtype of Epithelial Ovarian Cancer (EOC). Compared with other subtypes of EOC, CCC has relatively poor in prognosis and bad outcome in current clinical management using maximal cytoreduction and platinum plus paclitaxel–based combined chemotherapy. Therefore, the investigation of molecular therapeutic approaches targeting at signaling pathways associated with chemoresistance is needed. This review describes some recent potential signaling pathway targets and also suggests putative small molecule kinase inhibitors as well as natural anti-cancer agents in combating this disease.
MOLECULAR CHARACTERIZATION AND EXPRESSION PATTERN OF A NOVEL CADMIUM RESISTANCE GENE OF TOBACCO CARACTERIZAÇÃO E PADRÃO DE EXPRESSÃO MOLECULAR DE UM NOVO

Cadmium (Cd) of tobacco is a pollutant that is extremely toxic to the health of humans. Protein plant cadmium resistance 8 gene has been characterized to increase the plant Cd resistance. In present experiment, the complete mRNA sequence of tobacco protein plant cadmium resistance 8 gene was amplified using the rapid amplification of cDNA ends methods. The full-length tobacco protein plant cadmium resistance 8 gene mRNA was 887bp containing an 555 bp open reading frame, which encodes a protein of 184 amino acids. BLAST analysis revealed that tobacco protein plant cadmium resistance 8 protein shares high homology with the protein plant cadmium resistance 8 of potato (81%), Lycopersicon esculentum (80%), Eutrema salsugineum (60%), Capsella rubella (58%) and thale cress (57%). Results also showed that tobacco protein plant cadmium resistance 8 gene has a closer genetic relationship with the protein plant cadmium resistance 8 gene of Lycopersicon esculentum. The expression profile was studied and the results indicated that tobacco protein plant cadmium resistance 8 gene was highly expressed in root, moderately expressed in stem, and hardly expressed in flower and leaf. These results established the primary foundation of utilizing tobacco protein plant cadmium resistance 8 gene to decrease the cadmium content of tobacco and benefit the health of humans in the future.
CONFINEMENT OF THE 0.5…4.5 keV PLASMA IONS IN LOW DENSITY DISCHARGES OF THE U-3M TORSATRON

U-3M plasma volume is about 0.3 m 3 and its chamber volume is about 70 m 3 . The hydrogen pressure feeding level used in U-3M discharges is about 10 -5 Torr. In the case when all hydrogen will be ionized and accumulate in the confinement region the plasma density should achieve a value about 10 14 cm -3 . This density is two orders of magnitude higher than practically achieved densities in U-3M discharges. Evidently, substantial flux of the neutrals with mean free path longer than U-3M plasma size from large U-3M vacuum vessel should sustain main channel of the ion energy loss via the charge exchange (CX) collisions in the low density discharges of U-3M. According to set of previous articles [3-6], confinement of fast ions in U-3M was considered as collisionless. The electron-ion and ion-ion collision times are longer than the neoclassical confinement time of these ions, thus the confinement of the 0.5…4.5 keV ions is collisionless, if we are not taking into account CX collisions. Due to substantial difference in confinement of trapped and passing ions the confinement time of energetic ions with major part of the energy perpendicular to the magnetic field lines is significantly shorter than the confinement time of the ions with major part of the energy parallel to the magnetic field in the collisionless stellarator plasma. We can estimate the role of the CX ions cooling by the comparison of the parallel ion energy and perpendicular ion energy confinement times. If these times are comparable, then CX cooling is dominant channel of the ion energy loss and U-3M confinement cannot be considered as the collisionless. In this paper, the evidence of extremely short parallel ion energy and perpendicular ion energy confinement times is shown in low density U-3M discharges. These times are shorter that temporal resolution of the NPAs and less than 0.5 ms. 1. EXPERIMENTAL SET-UP
Pedestrian monitoring techniques for crowd-flow prediction

The high concentration and flow rate of people in train stations during rush hours can pose a prominent risk to passenger safety and comfort. In situ counting systems are a critical element for predicting pedestrian flows in real time, and their capabilities must be rigorously tested in live environments. The focus of this paper is on evaluating the reliability of two alternative counting systems, the first using an array of infrared depth sensors and the second a visible light (RGB) camera. Both proposed systems were installed at a busy walkway in London Bridge station. The data were collected over a period of 2 months, after which, portions of the data set were labelled for quantitative evaluation against ground truth. In this paper, the implementation of the two different counting technologies is described, and the accuracy and limitations of both approaches under different conditions are discussed. The results show that the developed RGB-based system performs reliably across a wide range of conditions, while the depth-based approach proves to be a useful complement in conditions without significant ambient sunlight, such as underground passageways.