Miracle-dz/UniFAR-FTUs huggingface dataset:
Estudio empírico sobre la influencia de la diversidad demográfica y funcional de los recursos humanos

The influence of workgroup diversity has aroused a growing interest in empirical literature on the field of human resources. However, previous research shows inconclusive findings, both positive and negative effects, and even some works do not evidence any impact. Extending previous studies, we analyse the influence of diversity at an organisational level. For that pur-pose, we first review some of the most accepted rationales regarding to the linkage between diverse composition in organizational groups and performance. We emphasize on some leading and specific approaches such as the organizational demography perspective and the relational demography research, additionally to the viewpoint of the information processing and decision making perspective. Using statistical methods, we present an empirical study in order to test whether both functional and gender diversity of human resources affects performance and finan-cial success objectives. We use a sample of Spanish firms during the 2008-2016 years, which is particularly interesting due to the crisis affecting the business world along such period. The results of our study indicate that diversity has a significant positive influence both on company outcomes and on sales volume.
Candidate Transaction Rank Accuracy Algorithm for Online Social Networks

In June 2015, Social Networks reported that a whopping of 20 billion users use the social networks which has boomed and made it essential for day-to-day life. Some of the obvious advantages of social networks are worldwide connectivity, commonality of interest and real-time information sharing ability that is able to search for users to add friend circle. It is important to get the appropriate results should return according to the user, with the increasing number of users in social networks. This paper states about the accuracy of KNN based classification, prediction or recommendation depends uniquely on a data model. The specific KNN algorithm is used to identify the criteria - Parsing, Indexing, Sorting and interaction that can be used to rank search results so that more appropriate results are presented to the user.
Convolutional neural network based sensor fusion for forward looking ground penetrating radar

Forward looking ground penetrating radar (FLGPR) is an alternative buried threat sensing technology designed to offer additional standoff compared to downward looking GPR systems. Due to additional flexibility in antenna configurations, FLGPR systems can accommodate multiple sensor modalities on the same platform that can provide complimentary information. The different sensor modalities present challenges in both developing informative feature extraction methods, and fusing sensor information in order to obtain the best discrimination performance. This work uses convolutional neural networks in order to jointly learn features across two sensor modalities and fuse the information in order to distinguish between target and non-target regions. This joint optimization is possible by modifying the traditional image-based convolutional neural network configuration to extract data from multiple sources. The filters generated by this process create a learned feature extraction method that is optimized to provide the best discrimination performance when fused. This paper presents the results of applying convolutional neural networks and compares these results to the use of fusion performed with a linear classifier. This paper also compares performance between convolutional neural networks architectures to show the benefit of fusing the sensor information in different ways.
Proceedings of the Workshop on Deep Linguistic Processing

This workshop was conceived with the aim of bringing together the different computational linguistic subcommunities which model language predominantly by way of theoretical syntax, either in the form of a particular theory (e.g. CCG, HPSG, LFG, TAG or the Prague School) or a more general framework which draws on theoretical and descriptive linguistics. We characterise this style of computational linguistic research as deep linguistic processing, due to it aspiring to model the complexity of natural language in rich linguistic representations. Aspects of this research have in the past had their own separate fora, such as the ACL 2005 workshop on deep lexical acquisition, as well as TAG+, Alpino, ParGram and DELPHIN meetings. However, since the fundamental approach of building a linguistically-founded system, as well as many of the techniques used to engineer efficient systems, are common across these projects and independent of the specific grammar formalism chosen, we felt the need for a common meeting in which experiences could be shared among a wider community.
Element Level Ontology Matching Based on Lexical Similarity

With the development of Semantic Web,the number of ontologies is increasing greatly.In order to use those ontologies effectively,different ontologies must be mapped,compared and integrated.As the basis of these three tasks,ontology matching has great practical significance.ISWC held a workshop called EON2004 to evaluate accuracy and recall of different ontology matching tools.This paper proposes an element level ontology matching algorithm,named LANA(Lexical Analyzer),to map the elements of two given ontologies by calculating lexical similarity.Compared with other element level matching algorithms in EON2004 competition,LANA has higher accuracy and recall without increasing complexity of matching.
Computational atmospheric acoustics

Abstract: Quite a number of numerical computation works contributed to the atmospheric acoustic propagation emerging constantly in recent years make the formation of a new developing sub-branch "Computational Atmospheric Acoustics" become just round the corner. The present paper provides a brief, clear, systematic and comprehensive introduction to this brand-new field and gives a relatively exhaustive demonstration of its main objects and methods, especially the parabolic equation (PE) method, the fast field program (FFP) and the Gaussian beam (GB) approach-may be regarded as a modified ray tracing procedure. A discussion concerning the comparison among the results obtained by these various methods cannot be included for the limitation of space, some opportunity for publishing these interesting materials separately would be expected.
Estimation and Simulation Study of LFM Signal Parameters

Based on GRCRT and direct dechirp operation,an algorithm to estimate parameters of LFM signals with under-sampling is proposed.Because of the under-sampling LFM signal and its two same time delay conjugation outputs are both single tones,the chirp rate is estimated unambiguously by FFT and GRCRT.Then using the estimated chirp rate,the dechirp operations are carried out by the produced LFM signals with no carrier chirp for two same time delay undersampling LFM signals,and the initial frequency can be estimated by the same method.The proposed method overcomes the drawback when using CRT.The computer simulation results prove the feasibility and robustness of the proposed algorithm.
EFFECT OF HARVESTING STAGES ON JELLY SEED SYMPTOM OF PLANGO (Bouae burmanica) CV. THUNL KLAO FRUITS

Plangoor Marian plum (Bouae burmanica) has a short harvesting period and usually harvested at fully ripe fruit stage . Therefore, the jelly-seed often occurred inside the fruit . The jelly-seed is a physiological disorder and causes fruit softening and wilting . This symptom will affect the storage period and shelf-life of the fruit . Jelly-seed also found after harvesting . This study was determined the activities of two important cell wall degradation enzymes which werepolygalacturonase (PG) and pectin methyl esterase (PME)from 3harvesting stages of plan go fruits 75, 85 and 95 days after full bloom )DAFB . (Fruits were storage at 10 and 25°C . It was found that the jelly-seed symptom only occurred in the 95 DAFB fruits after harvest and storage at 25°C . This fruits also had the highest activity of PG. The PG activity also increased with the ripening stages and storage period . The activity of PG and PME were delayed when storage at 10°C compared with those of the fruit kept at
DESIGN AND IMPLEMENTATION OF A PRACTICAL INTERNET CONTENT COPYRIGHT PROTECTION SYSTEM

ICCP is designed as an Internet content copyright protection system for on line content security. It supports different media format and uses cryptology and authentication technolgy for persistent secuity. Meanwhile, this system also uses plug in technology to protect content and to decrypt content. ICCP is a practical Internet content copyright protection system for electronic publication and digital library.
Opinion evolution analysis based on social impact model

This paper develops a mathematical model concerning opinion evolution,and studies some corresponding dynamical properties by numerical simulations.Opinion evolution is investigated for different kinds of complex networks in terms of synchronization and invulnerability.By using the proposed social impact model,the results show that scale-free networks own robust-yet-fragile characteristic.The enhancement of network cohesion can increase the invulnerability of random network,but reduce that of scale-free network.Moreover,invasive strategy and noise play important roles in the network evolution.
Tracking Algorithm Based on Moving Slide Window for Manuevering Target

본 논문에서는 이동 창 함수 추적기라는 새로운 추적 알고리즘을 제안한다. 본 논문에서는 이동표적의 궤적을 효율적으로 추정하기 위해 과거 궤적의 정보를 포함하는 이동 구간이 선형이라는 가정을 한 선형 창 함수를 적용하여 구현한다. 제안된 알고리즘의 창 함수의 파라메터는 측정 잡음의 영향을 줄이기 위해 그리고 알파-베터 추적기와 비교하여 더 적은 계산량 증가로 빠른 이동 표적 추적을 구현하기 위해 적절하게 선택할 수 있다. 본 논문에서 제안한 창 함수 추적기를 검증하기 위해 잡음상황에서 선형과 비선형 궤적에 대한 컴퓨터 모의실험을 수행했다. 또한 제안된 창 함수 추적기는 초기값에 대한 둔감한 특성과 예측할 수 없는 시변 측정 환경에서 창 함수 추적기를 사용할 경우 더 높은 자유도를 가짐을 보였다.
The Study on the Adaptive Filtering Method for Eliminating the Motion Artifact in Pulse Oximetry Measurement

Objective The method of eliminating the motion artifact in the pulse oximetry measurement was studied in order to improve the performance character of the pulse oximeter. Methods The noise parameter was constructed by using light beat in the pulse oximetry system and the LMS(Least Mean Square) adaptive filter was used to eliminate the effect of motion artifact. Results The algorithm of eliminating the motion artifact in the pulse oximeter was developed. It can successfully extract the normal Photoplethysmographic signal from the motion artifact in calculating oxygen saturation. Conclusion This calculating method is simple and can be processed in real time, and its result is reliable. It establishes the fundament for further decreasing the noise of pulse oximeter.
Pronation in runners: Implications for injuries

In spite of some significant progress in the understanding of the biomechanics of the ankle joint complex, especially the coupling mechanism between foot and leg, various mechanisms causing overuse injuries in the lower extremities are still poorly understood. Some increased pronation of the foot is often physiological, but excessive pronation is potentially harmful. Compensatory overpronation may occur for anatomical reasons. However, not only the amount of foot eversion, but also the way this eversion is transferred into tibial rotation may be crucial to the overloading stress on the knee. In other words, the individual transfer mechanism of foot eversion into internal tibial rotation may be of some predictable value for lower extremity overloading and related injuries. Further research is necessary to improve the functional understanding of anatomical and biomechanical abnormalities and their pathological value in predicting overuse injuries.
An Enhanced Case-Based Reasoning Model for Supporting Inference Missing Attribute and Its Feature Weight

Case-based reasoning (CBR) methodology corresponds to problem solving by retrieving similar cases from a case base. In most research, the attribute values of each case are assumed to be complete. However, in reality, we encounter a situation that cases are collected from many different sources (e.g., books, papers) when a case base is built. Different sources with different attribute collections result in some null attribute values, which affect reasoning accuracy. The present study proposes an enhanced CBR model to improve accuracy when missing values occur in a case base. Association rules are applied to find the possible missing values, and rule's confidence is used to justify the feature weight. However, using the whole case base to mine the rules may involve the ”noise” of different classifications, which affects the rules. To improve the quality of rules, classification is performed before rules are mined. The UCI Machine Learning Repository was used for evaluation to show the improved reasoning correctness with the proposed method. Our adapted CBR method has higher accuracy than unclassified and original case base reasoning.
Survey on Image and Video Painterly Rendering

Image and video painterly rendering is an important problem in Non-Photorealistic Rendering(NPR),which has various applications in many fields,like cartoon animation,digital entertainment,etc.This paper reviewed the deve-lopment of painterly rendering,whilst some typical approaches were investigated and classified,and the characteristic of each technique was fully analyzed.Based on this,some challenges and possible directions in the domain of image and vi-deo painterly rendering were discussed for reference.
Design for verification for concurrent and distributed programs

In this dissertation we present a design for verification (DFV) approach that embeds intentions of developers into software and makes software systems amenable to automated verification; hence, making the automated verification techniques scalable to large systems. In this DFV approach, we use (1) behavioral interfaces that isolate the behavior and enable modular verification, (2) an assume-guarantee style verification strategy that separates verification of the behavior from the verification of the conformance to the interface specifications, (3) a general model checking technique for interface verification, and (4) domain specific and specialized verification techniques for behavior verification. We realize our DFV approach for concurrent programming by introducing the concurrency controller pattern. We aim to eliminate synchronization errors in concurrent Java programs. We use the Action Language Verifier to verify the concurrency controller behaviors by an automated translation from their Java implementations. We have applied this framework to two software systems: a concurrent text editor and a safety critical air traffic control software called TSAFE. To demonstrate the applicability of our DFV approach to another application domain, we introduce the peer controller pattern for asynchronously communicating web services. Our goal is both to analyze properties of interactions among the participating peers and to validate the conformance of peer implementations to their behavioral specifications. We use the SPIN model checker to verify the interaction properties. We adapt synchronizability analysis to enable behavior verification with respect to unbounded asynchronous communication queues. We extend this approach with an hierarchical interface model for compact representation of peer interfaces. We use the Java PathFinder for interface verification in both application domains. We present techniques for thread isolation which improve the efficiency of interface verification.
Interaction with images using hand gestures

Author(s) Title Number of Pages Date Suman Basnet Interaction with images using hand gestures 24 pages + 2 appendices 31 May 2016 Degree Bachelor of Engineering Degree Programme Electronics Specialisation option Instructor(s) Janne Mäntykoski, Senior Lecturer, Helsinki Metropolia AMK The main objective of this Final Year Project (FYP) is to achieve prototype of an embedded system where any user can control the flow of the images in the Graphical User Interface (GUI). This report starts with working mechanism of the sensors where gesture recognition pattern of the sensors is discussed. Then, the hardware and software requirements are enlisted with their features’ description in the system specifications heading. Eventually, stepwise elaboration of two different phases of the system is discussed in the methodology heading. The main constituents of this FYP are Arduino Nano, Ultrasonic sensors and Python Programming Language. The whole system activates when ultrasonic sensors connected to the Arduino Nano follow the hand gestures of the user. After that the Arduino Nano forward the information about the hand movements to the serial port of the computer and Python Programming language executes the commands indicated by the hand movement, changing the images in the Graphical User Interface (GUI) accordingly. Finally; challenges, limitations and possible upgrade in the system design are discussed in the conclusion part of this report.
Modelling agent’s questions for analysing user’s affects, appreciations and judgements in human-agent interaction (Modélisation des questions de l’agent pour l’analyse des affects, jugements et appréciations de l’utilisateur dans les interactions humain-agent) [in French]

This paper tackles the issue of user's attitudinal expressions in an human-agent interaction. It introduces a method for analysing the user's anwers to the agent's yes/no questions about attitude. In order to build a user model, this method relies on a formalization of the agent's questions and a linguistic analysis of the user's answer. This formalization comprises a set of attributes regarding the attitude expressed and the morphosyntaxic form of the question. The answer is then analyzed by using a set of semantic and syntactic rules included in a formal grammar. Finally, the semantic value of the answer can be calculated by using the results provided by this analysis and the information given by the question formalization. This computation is next integrated in the user model.
Which Change Sets in Git Repositories Are Related

Software repositories contain valuable information about the history of software changes. Using data mining, researchers have identified file changes that happened together frequently to present hints for necessary changes to developers. However, not all file change sets are related. This can affect the recommendations about coupled file changes negatively by delivering irrelevant couplings to the developers. The commit time and branching characteristics of Git have not been investigated together in previous heuristics for grouping related change sets. We exploit the mappings between commit messages and issue ids for judging the relatedness of change sets. We propose a heuristic for Git and investigate the influence of two factors, the time between the commits and their branching on the relatedness of change sets using the repositories of five open-source systems using logistic regression. According to our findings, the combination of these two factors influences the relatedness of change sets. Individually measured, only the time significantly influences the relatedness, the branching itself does not. Our results support previous heuristic that also in Git repositories the commit time is important for grouping related change sets.
Green Energy in Data Centers

Green energy paradigm has been gaining popularity in the computing system from the software, hardware, infrastructure and application perspectives. Within that concept, data center greening is of utmost importance at the moment since data centers are one of the most energy conserving elements. Data centers are seen as the technology era’s black energy-swallowing secret. Reducing energy consumption at data centers can reduce carbon footprint effect tremendously. Not addressing the issue immediately will lead to significant energy usage by data centers and will hinder the growth of data centers. The call for sustainable energy efficient data center leads to venturing into data center green computing. The green computing concept can be achieved by using several methods adopted by researchers including renewable energy, virtualization through cloud computing, proper cooling system, identifying suitable location to harvest energy whilst reducing the need for air-conditioning and employing suitable networking and information technology infrastructure. This paper focuses into several approaches used by researches to reduce energy consumption at data centers while deploying efficient database management system. This paper differs from others in the literature by giving some suitable solutions by looking into a hybrid model for green computing in data centers.
Modern Messaging for Distributed Sytems

Modern software applications rarely live in isolation and nowadays it is common practice to rely on services or consume information provided by remote entities. In such a distributed architecture, integration is key. Messaging, for more than a decade, is the reference solution to tackle challenges of a distributed nature, such as network unreliability, strong-coupling of producers and consumers and the heterogeneity of applications. Thanks to a strong community and a common effort towards standards and consolidation, message brokers are today the transport layer building blocks in many projects and services, both within the physics community and outside. Moreover, in recent years, a new generation of messaging services has appeared, with a focus on low-latency and high-performance use cases, pushing the boundaries of messaging applications. This paper will present messaging solutions for distributed applications going through an overview of the main concepts, technologies and services.
Organized Labor and Inventory Stockpiling

We document that managers stockpile excess inventory to mitigate the operational risk posed by labor unions and to maintain bargaining power in labor negotiations. Inventory levels are higher for union firms and are incrementally higher preceding the renegotiation of collective bargaining agreements with unions. Inventory stockpiling at union firms is more salient when capital market pressure for transparency or information spillover from peers constrains managers from using disclosure strategies. We further show that managers weigh the costs and benefits of inventory stockpiling, as holding excess inventory due to the presence of a union is negatively associated with future profitability but provides the benefits of avoiding a stockout and mitigating negative outcomes from a strike. Our findings highlight the importance of a major stakeholder, i.e., labor, in managers' investment decision-making.
Assessment of Reaeration Equations for River Tungabhadra, Karnataka, India and Generation of the Refined Equation

The ability of a water body to self-purify itself is dependent on its re-aeration rate (Ka). This rate is necessary to calculate the dissolved oxygen content in the waterbody. This rate also depends on some variables that include the stream velocity, stream bed slope, cross section area, water depth, frictional velocity, discharge rate, Froude’s number and a number of other things. For the purpose of this study, thirteen empirical equations are considered when evaluating the performance of the re-aeration rates. This is done with respect to the size of the Tungabhadra river. Observation of the re-aeration rate for this study was done using mass balance approach. The data needed for this was gotten from field investigation data obtained from 288 separate samples (6 different sites) between the period March, 2017 to December, 2018. The performance evaluation of the re-aeration equation was done via the implementation of least square techniques. The following statistical error methods were applied in due course; standard error, normal mean method and mean multiplicative method. The results of the methods are 0.16, -0.0006 and 2.75. The coefficient of correlation for this was 0.91 and by interpretation, it shows an efficient outcome.