Miracle-dz/UniFAR-FTUs huggingface dataset:
The evaluation of Persian Thesauri of Health and Biomedical Sciences Based

Establishing order, integrity, consistency, and accuracy in thesauri as information storage and retrieval systems plays an important role in the organization of information. The deployment of universally accepted standards, therefore, facilitates the accomplishment of this goal. To achieve this goal, the ANSI /NISO Z 39.19 -2005 standard offers certain rules and principles for constructing controlled vocabularies, including the thesauri, with regard to four dimensions of form construction, semantic relationships, displaying controlled vocabularies, and management systems. These dimensions served as a basis in this study to evaluate the accuracy of vocabulary construction in three Persian Thesauri of Health and Biomedical Sciences, namely, the thesaurus of biological sciences, the thesaurus of health promotion and the thesaurus of medicine. The research method utilized in this study was the analytical survey method. A sampling method was also used to establish samples of the terms contained in the latest edition of every thesaurus. The research instrument used in this study was a checklist defined in Microsoft Excel. The samples for the four dimensions were entered in the checklist and were evaluated on the basis of the relevant standards. The results of the study revealed that the thesauri under study had not given due attention to the standards related to the management dimension. The level of observance of standards for this dimension was only 14% in all of the thesauri. Regarding the dimension of displaying controlled vocabularies, the highest level of observance of the standards was 73% which belonged to the thesaurus of medicine, the lowest level was 54.5% which belonged to the thesaurus of biological sciences, and for the thesaurus of health promotion it was 59%. As for the dimensions of the semantic relations and form construction, the results of the study indicated a higher level of observance of the standards in the thesauri under study. Finally, it was concluded that possessing the required expertise, familiarity with the standards of thesauri construction, utilizing appropriate models, taking the needs of the end users into consideration are among the major factors that if observed could lead to the construction of more effective and efficient thesauri.
Analysis of Various Measures of Job Satisfaction of Syngenta Pakistan Limited

The purpose of this study was to find out the relationship between job satisfaction and the dimension of their employees in the pesticide sector. Hypothesis plays a significant role in job satisfaction, resulting in increased employee satisfaction and organizational performance. Thus the role of work environment and colleague & boss satisfaction was explored with samples from workers in two regions of Sygenta Pakistan. The implications of policies on employees were also investigated. A questionnaire was constructed, tested and administered to a total 130 subjects at two region employees. Out of that 100 usable surveys were analyzed with correlation and regression to test the hypotheses of the study. Findings showed that policies induced positive impact on job satisfaction of employees. Additionally the findings also showed that job satisfaction of employees stimulated their loyalty to the organization. However, a very high level of employee dissatisfaction was recorded for employee work environment. The study result highlights the role of employees’ job satisfaction and the responsibilities of organizations in fostering good quality human resource practices in the pesticide sectors, and offers an alternative pathway in job satisfaction and performance.
Empirical Evaluation of Software Design Patterns using Classification Algorithms based Design Metrics

Software engineering has become very important for the technology. It includes the study and application of the engineering in designing, developing and maintaining the software. The aim of software engineering is to produce quality software to be delivered on time keeping it within budget which satisfies the requirement. The patterns can be detected by code inspections, automatic techniques, dynamic techniques such as testing and assertions, using machine learning and by static techniques. These design patterns can be detected from the design metrics using machine learning algorithms This study emphasis on detecting software design pattern-based design metrics using machine learning algorithm. The results surely depict that the design metrics plays an important role in predicting the software design patterns. The algorithms used are Naive Bayes and SVM and they were able to predict the patterns from the software metrics and gave good perceptiveness.
RESIN-SECRETING TRICHOMES IN Maxillaria dichroma ROLFE ( ORCHIDACEAE : MAXILLARIINAE ) Ma ł gorzata

Resin-secreting, sunken, glandular trichomes have been described from the vegetative organs of Maxillaria and certain related taxa. However, until now, these hairs have not been recorded for Maxillaria flowers, nor have they been examined at the ultrastructural level for any part of the plant. Here for the first time, these hairs are described using LM, SEM and TEM, and their possible functions discussed.
Title Linear dispersion code with an orthogonal row structure forsimplifying sphere decoding

In this paper, we propose a family of full diversity fast decodable Linear Dispersion Codes (LDCs) for use in MIMO systems. These codes have as many as possible the orthogonal rows in the dispersion matrices of the LDC. One of the main advantages of this family of LDCs is that it can be used in MIMO systems with arbitrary numbers of transmitted and received antennas and arbitrary transmission rates. We also develop a simplified Sphere Decoding (SD) algorithm to significantly reduce the decoding complexity for this family of LDCs. Monte Carlo simulation shows that the optimum LDCs with or without this orthogonal structure have nearly identical bit-error rate (BER) performances, but the complexity can be significantly reduced. For a 2×4 MIMO system transmitting 8 QPSK symbols in a block length of 4, the reduction is about 28-52%, and for a 3×3 MIMO system transmitting 10 QPSK symbols in a block length of 6, the reduction is about 28-49%. KeywordsMIMO, Sphere decoding, orthogonal, complexity
The Effectiveness Of Idea Capture Schemes

Innovation at work is mainly driven by employees' ideas. This paper reports a study of the effectiveness (e.g., rate of suggestion making) of schemes for capturing these ideas. Based on a survey of 182 UK organizations, the study shows that decentralized suggestion schemes and work-based systems are more effective than centralized and informal schemes. The extent of planning, publicity, feedback and management support given to the scheme, and the type of reward offered to employees, also independently account for variation in effectiveness. Publicity and non-monetary rewards, though, are found to be most decisive, regardless of scheme type. Learning culture also affects the rate of suggestion making, though the effect is greater for centralized and decentralized schemes than for the others. The key implication of the findings is that by paying particular attention to how they are advertised and how participation is rewarded, organizations could improve the return on their idea capture schemes.
MONGKIE: Integrated network analysis and visualization platform for multi-omics data

MONGKIE: Integrated network analysis and visualization platform for multi-omics data Yeongjun Jang Interdisciplinary Program in Bioinformatics The Graduate School Seoul National University Network-based integrative analysis is a powerful technique for extracting biological insights from multi-layered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. The result of case study showed that network-based analysis in MONGKIE can identify and extract biologically relevant genes and pathways that play important roles in GBM tumorigenesis. MONGKIE is a java-based open-source application built on top of plug-in architecture, thus being platform-independent and easily extensible with additional functionalities. It is available under GNU AGPL v3 license at http://yjjang.github. io/mongkie. keywords : Network visualization, Network modeling, Graph clustering, Omics data analysis, Over-representation analysis Student Number : 2014-20341
EFFICIENCY MEASUREMENT FOR INTERNATIONAL CONTAINER PORTS OF TAIWAN AND SURROUNDING AREAS BY FUZZY DATA ENVELOPMENT ANALYSIS

International container ports are critical hubs for global logistics, and high efficiency is a particularly important requirement for managing these ports. International container ports in Taiwan and surrounding areas have to deal with increasingly larger amounts of cargo in recent years. As a result, it has become more difficult to measure these ports’ efficiency. This study offers a new approach for measuring the efficiency of international ports. Twelve international container ports in Taiwan and surrounding areas were chosen as the samples, and their six inputs (application service process, service personnel ability, service personnel attitude, advisory services, harbor rates and stevedoring rates), and seven outputs (tug boat operation, rope untwisting operation, pilot operation, stevedoring efficiency, low damage rate for goods, awaiting unloading and working, and service flexibility) are analyzed herein with fuzzy data envelopment analysis (DEA). This approach allows objective and easy measurement of international container port efficiency.
Environmental Sustainability and Social Desirability Issues in Pig Feeding

Feeding pigs used to be a means of managing domestic resources that may otherwise have been wasted into valuable animal protein. Feeding pigs thus was a form of husbandry. Following recent rapid industrial development, pig rearing has changed from extensive to intensive, but this transformation has been associated with major concerns. The concentration of large amounts of pig manure in small arrears is environmentally hazardous. Moreover, high densities of animals in intensive production systems also impose a health threat for both animals and humans. Furthermore, the use of growth promoters and preventive medicines for higher production efficiencies, such as in-feed antibiotics, also induces microbial resistance thus affects human therapeutics. In addition, consumers are questioning the ethics of treating animals in intensive production systems. Animal welfare, environmental and bio-safe issues are re-shaping the nature of pig production systems. Feeding pigs thus involves not only the consideration of economic traits, but also welfare traits and environmental traits. Thus, a focus on technological feasibility, environmental sustainability and social desirability is essential for successful feeding operations. Feeding pigs now involves multiple projects with different sustainability goals, but goal conflicts exist since no pattern or scenario can fulfill all sustainability goals and the disagreements are complicated by reduced or even no use of in-feed antibiotics. Thus it is difficult to feed pigs in a manner that meets all goals of high quality, safe product, eco- and bio-sustainability, animal welfare and profit. A sustainable pig production system thus requires a prioritization of goals based on understanding among consumers, society and producers and needs to view from both a local and global perspective.
BEAM INDUCED DAMAGE - WHAT IS A SAFE BEAM?

The knowledge of damage levels is vital to define protection schemes, beam loss monitor thresholds, safe beam limits for setting up the machines, etc. This talk will try to revisit our present knowledge and assumptions on damage levels in the LHC in terms of lost beam intensity, beam momentum and emittance. It is clear that with the LHC’s unprecedented energy reach, benchmark tests to cross-check energy deposition simulations for all possible energies before LHC start-up have not been possible. Also, the definition of when equipment is damaged is not always straight forward. In view of the obvious limitations to our knowledge of damage levels, operational commissioning and LHC running strategies will be re-discussed, open questions will be highlighted and proposals will be presented where possible.
R ESEARCHES OVERLAPPING AND DISJOINT COMMUNITY DETECTION IN SOCIAL NETWORKS-A REVIEW

Of late, social networks have become very popular and have attained the maximum consideration because of its utility in various sectors such as healthcare, management, computer science and the sociology domain. Moreover, identification of communities within the networks was a significant task because, in real-time, weighted networks are more general that has the overlapping communities such that the node could depend on many communities. Moreover, it provides response to various queries based on the person’s interaction patterns and their behavior. However, identification of the community is a major concern in the social network system for exploring and understanding the network frame. Moreover, the community denotes individuals getting grouped into sub-groups based on the provided framework which is specific to the social interactions. This study an overall review of the various techniques utilized to identify communities within the network. Moreover, it also analyses the conventional community detection overlapping, non-overlapping algorithms and the existing quality metrics. The major goal of this study is to investigate the varied overlapping and disjoint community detection techniques in the network. Even though there are numerous studies relating to this community detection, there are drawbacks such as larger processing time. Hence, a need for an efficient algorithm is proposed for detecting communities with larger network within a limited process time.
A BL-CSC Converter fed BLDC Motor Drive with Power Factor Correction

This paper presents a power factor correction (PFC) based bridgeless-canonical switching cell (BL-CSC) converter fed brushless DC (BLDC) motor drive. The proposed BL-CSC converter operating in a discontinuous inductor current mode is used to achieve a unity power factor at the AC mains using a single voltage sensor. The speed of BLDC motor is controlled by varying the DC bus voltage of the voltage source inverter (VSI) feeding BLDC motor via a PFC converter. Therefore, the BLDC motor is electronically commutated such that the VSI operates in fundamental frequency switching for reduced switching losses. Moreover, the bridgeless configuration of CSC converter offers low conduction losses due to partial elimination of diode bridge rectifier at the front end. The proposed configuration shows a considerable increase in efficiency as compared to the conventional scheme,a combination of switch, capacitor (C1) and diode (D) is known as a ‘canonical switching cell’ and this cell combined with an inductor (Li) and a DC link capacitor (Cd) is known as a CSC converter.With proper design and selection of parameters, this combination is used to achieve PFC operation when fed by a single phase supply via a DBR (Diode Bridge Rectifier) and a DC filter.
Kalman filtering and smoothing for linear wave equations with model error

Filtering is a widely used methodology for the incorporation of observed data into time-evolving systems. It provides an online approach to state estimation inverse problems when data are acquired sequentially. The Kalman filter plays a central role in many applications because it is exact for linear systems subject to Gaussian noise, and because it forms the basis for many approximate filters which are used in high-dimensional systems. The aim of this paper is to study the effect of model error on the Kalman filter, in the context of linear wave propagation problems. A consistency result is proved when no model error is present, showing recovery of the true signal in the large data limit. This result, however, is not robust: it is also proved that arbitrarily small model error can lead to inconsistent recovery of the signal in the large data limit. If the model error is in the form of a constant shift to the velocity, the filtering and smoothing distributions only recover a partial Fourier expansion, a phenomenon related to aliasing. On the other hand, for a class of wave velocity model errors which are time dependent, it is possible to recover the filtering distribution exactly, but not the smoothing distribution. Numerical results are presented which corroborate the theory, and also propose a computational approach which overcomes the inconsistency in the presence of model error, by relaxing the model.
A Survey on Single Channel Speech Separation by Signal-Noise-dependent DNNs

The task of separating speech in complex acoustic environments such as a single voice in a cocktail party is an extremely difficult challenge. The goal of speech separation, to be precise, is to singling out the voice of each speaker in the mixed speech signals. Many speech enhancement or separation techniques cannot accommodate the situation where both target and interference have the same characteristic because both are speech signals. This project is concerned with applying a novel data-driven approach to single-channel speech separation based on deep neural networks (DNNs). A semi-supervised method to separate speech of the target speaker from an unknown interrupting speaker, which is more flexible than the conventional supervised mode with known information of both the target and interrupting speakers, is reviewed. Two key issues are investigated; initially, propose a DNN architecture with dual outputs of the features of both the target and interrupting speakers, which is shown to achieve a better generalization capacity than that with output features of only the target speaker. Then, introduce a set of multiple DNNs, each intending to be signal-noise-dependent (SND), keeping in mind the difficulty that one single general DNN could not well accommodate all the speakers mixing variability at different signal-to-noise ratio (SNR) levels.
Best-subset model selection based on multitudinal assessments of likelihood improvements

ABSTRACT A common model selection approach is to select the best model, according to some criterion, from among the collection of models defined by all possible subsets of the explanatory variables. Identifying an optimal subset has proven to be a challenging problem, both statistically and computationally. Our model selection procedure allows the researcher to nominate, a priori, the probability at which models containing false or spurious variables will be selected from among all possible subsets. The procedure determines whether inclusion of each candidate variable results in a sufficiently improved fitting term – and is hence named the SIFT procedure. Two variants are proposed: a naive method based on a set of restrictive assumptions and an empirical permutation-based method. Properties of these methods are investigated within the standard linear modeling framework and performance is evaluated against other model selection techniques. The SIFT procedure behaves as designed – asymptotically selecting variables that characterize the underlying data generating mechanism, while limiting selection of spurious variables to the desired level. The SIFT methodology offers researchers a promising new approach to model selection, providing the ability to control the probability of selecting a model that includes spurious variables to a level based on the context of the application.
REACTIVE POWER OPTIMIZATION USING INTELLIGENT SEARCH ALGORITHMS CONSIDERING VOLTAGE STABILITY INDEX

The ever-increasing demand for the electric power has caused speeding up expansion of power systems to be able to fulfil costumers’ needs for reliable, cheap, and high quality electric power. Active power losses reduction in transmission system is known as an important respect which is raising among popularity of specialists and usually it is very important from the economical point of view in which the needs of power systems and high-tech approaches combine together to achieve remarkable objectives. This paper investigates the subject of reactive power optimization in order to decrease active power losses considering voltage stability index and voltage deviation reduction. In addition, simulation of reactive power optimization problem and analyzing data of performed methods including Genetic Algorithm, Particle Swarm Optimization, Pattern Search and their combinations on IEEE 6-Bus and 14-Bus system are approached using DIgSILENT and MATLAB software. Finally, the mixture as PSO with Pattern Search algorithm are introduced as the best optimization approach for the purposes of reactive power optimization.
AND LESBIANS IN LATE ADULTHOOD

Introduction Sexual behaviors in late adulthood are studied more and more often and betimate aspect of life of older people may result from a general increase of concern about the quality of older people`s lives, in conjunction with the data suggesting an increase of the population for the discussed age group. The studies on the sexuality of people in late adulthood most often concern groups of heterosexual persons
Main Concepts of Building Information Modeling-BIM Fields

The article is addressed to provide a comprehensive review on recently accelerated development of the Information Technology within project market such as industrial, engineering, procurement and construction. Author’s aim is to cover the last decades of the growth of the Information and Communication Technology in construction industry in particular Building Information Modeling and testifies that the problem of a choice of the effective project realization method not only has not lost its urgency, but has also transformed into one of the major condition of the intensive technology development. All of it has created a great impulse on shortening the project duration and has led to the development of various schedule compression techniques what becomes a focus of modern construction.