Miracle-dz/UniFAR-FTUs huggingface dataset:
Contracting Outcomes with Communication and Learning

Abstract We show that allowing communication can increase optimal choices and efficiency in a multitask, incomplete contracting, principal–agent setting. We study two simple communication protocols, one allowing for one or more requests on non-contractible choices, and the other allowing for a request, promise and ex post payment. The protocol where principals are asked to communicate requests to the agent regarding non-contractible choices promotes better learning of optimal strategies on the part of the principals, but shows no tendency for coordination to superior outcomes. The benefits accrue mainly due to changes in the choices of principals, who issue communication, rather than those of agents. Coordination is promoted, and learning subdued, when the protocol permits promises and ex post payments, in addition to allowing a request. This protocol also increases efficiency, with the efficiency gains equal across the protocols. JEL Codes: L14, C91
A Methodology for Assessing the Impact of Node Connectivity on Resilience of Looped Water Distribution Networks

The analysis and design of water distribution networks has increasingly become a fascinating subject of research in recent decades, with objectives shifting from merely fulfilling consumers’ demands for pressure, flow and quality to more sophisticated optimisation, resilience and reliability considerations. This paper applies concepts of graph theory and network hydraulics to assess the resilience of water distribution networks by investigating node connectivity. A key finding reveals that the higher the node connectivity, the greater the network resilience.
Improved the Convergence of Iterative Methods for Solving Systems of Equations by Memetics Techniques

This work proposes proposed a technique inspired by memetic algorithm (MA) to improve the convergence of iterative methods for solving systems of equations. In the first phase the system of equations is transformed into an optimization problem. In this first phase, a memetics technique -ie a double optimization, local and global- is used to determine an initial vector favorable to a rapid convergence. In the second phase the system of equations is solved using an iterative method with the initial vector obtained in the previous phase. One can say that it is a hybrid method of solving systems of equations, both linear and nonlinear. The experimental results obtained with conjugate gradient, preconditioned conjugate gradient, Newton, Chebyshev and Broyden methods, serial and parallel versions, recommend the proposed method.
Review on Encrypt the Text by MD5 and RSA in Client Cloud Approach

Cloud computing is one of the emerging technology which is showing continuous advancement in the field of networking. Cloud computing is defined by National Institute of Standards and Technology (NIST)[1] as a model for enabling ubiquitous, on demand network access to a shared pool of configuration computing resources (e.g. computer networks, servers, storage, applications and services) ,which can be rapidly provisioned and release with minimal management effort. It is gaining popularity in all the areas. But still by far cloud computing sharing is behind one expected because of the security concerns (unauthorized access, modification or denial of services, etc). In this research paper, the proposed work plan is to eliminate security concerns using cryptographic algorithm and hashing algorithm.
Facilitating Collegial Exchange among Science Teachers: An Experiment in Computer-Based Conferencing. Technical Report 86-14.

Teacher isolation is a significant problem in the science teaching profession. Traditional inservice solutions are often plagued by logistical difficulties or occur too infrequently to build ongoing teacher networks. Educational Technology Center (ETC) researchers reasoned that computer-based conferencing might promote collegial exchange among science teachers by giving them a new way to communicate with each other--individually or in groups, from their own workplaces and homes, at whatever time suits them. Using "Common Ground" conferencing software created at ETC, these researchers established an electronic network and conducted two initial studies of its operation. Researchers studied both technical and substantive aspects of the network's operation. Initial feedback from teachers was quite positive, and data on their usage patterns yield several findings: (1) some participants need support and encouragement' in the initial stages of learning to use a conferencing system; (2) some participants encountered snags in setting up their own equipment or using their communications software; (3) access to equipment remains a problem for some school people; (4) inexperienced participants tend to send more private than public mes :ages; and (5) forum moderators and/or a network coordinator can play an important role in stimulating and sustaining substantive discussions. Half of the. document consists of appendices. They include magaine articles, case studies of teachers' use and evaluation of the network, sample telephone interviews, and sample network messages. (CW) *********************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ***********************************************************************
An Improved Particle Swarm Optimization Based on Self-Adaptive Escape Velocity

To deal with the problem of premature convergence and slow search speed, this paper proposes a novel particle swarm optimization (PSO) called self-adaptive escape PSO, which is guaranteed to converge to the global optimization solution with probability one. Considering that the organisms have the phenomena of escaping from the original cradle when they find the survival density is too high to live, this paper uses a special mutation –escape operator to make particles explore the search space more efficiently. The novel strategy produces a large speed value dynamically according to the variation of the speed, which makes the algorithm explore the local and global minima thoroughly at the same time. Experimental simulations show that the proposed method can not only significantly speed up the convergence, but also effectively solve the premature convergence problem .
Towards the Learning Experience Technology Usability framework

The availability of learning technology has increased over past decades; however, severe usability issues that cause adverse effects on the learning experience can be found in many available technologies. Learning solution usability is commonly evaluated by focusing on either technical or pedagogical usability and rarely both. This artificially separates the two important aspects of learning technology usability. This chapter provides a new framework for designing and evaluating learning solutions that synthesizes the above usability types to consider them a part of a complex and dynamic whole comprising of learning, technological design, content-related issues and context. The proposed Learning Experience Technology Usability (LETUS) framework will help bridge the gap between theory and practice to provide learning solutions that have usability in relation to both the technological and learning related aspects of the solution.
Efficient Adaptive Equalizer Combined with LDPC Code for Vehicular Communications

Low density parity check (LDPC) code is very powerful for the error correction in the communication systems. So, LDPC code has been adopted for the standard of IEEE 802.11p (vehicular ad-hoc networks) and digital video broadcasting-satellite2 (DVB-S2). Features of LDPC code are iterative decoding and sparse parity check matrix. However, when multipath fading channel is considered, LDPC code needs long parity check matrix and pretty big iteration number of decoding. We propose a fast and efficient adaptive equalizer with LDPC code for compensating the carrier frequency offset (CFO) and phase noise in the vehicular environments. In addition, this proposed system has less iterations than the conventional system without combining structure. So, the proposed system has lower complexity. In this paper, we investigate the system model and evaluate BER performance for the vehicular environments by the simulation results, considering the CFO and phase noise in the OFDM system. Keywords-LDPC; adapitve equalizer; CFO; phase noise; OFDM; Sparse Parity Check Matrix; iteration number.
Exploiting network redundancy for low-cost neural network realizations

A method is presented to optimize a trained neural network for physical realization styles. Target architectures are embedded microcontrollers or standard cell based ASIC designs. The approach exploits the redundancy in the network, required for successful training, to replace the synaptic weighting and the neuron transfer functions by ones that can be implemented with smaller cost. Redundancy indices are used to identify the network elements that are candidates for optimization to be performed by the judicious application of local, behaviour-invariant transformations. The usefulness of the presented approach is illustrated by a image processing application realized in our lab.
Scheduling of semiconductor test facility via Petri nets and hybrid heuristic search

This paper proposes and evaluates two Petri net-based hybrid heuristic search strategies and their applications to semiconductor test facility scheduling. To reduce the setup time, such as the time spent to bring the test facilities to the required temperatures, scheduling multiple lots for each job type together is desirable. Petri nets can concisely model multiple lot sizes for each job, the strict precedence constraints, multiple kinds of resources, concurrent activities and flexible routes. To cope with the complexities for multiple lots scheduling, this paper presents two Petri net-based hybrid heuristic search strategies. They combine the heuristic best-first strategy with the controlled back tracking strategy based on the execution of the Petri nets. The obtained scheduling results are compared and analyzed through a small-size test facility. The better algorithm is also applied to a more sizable facility containing types of resources with a total of 79 pieces and 30 jobs. The future work includes the real-time implementation of the proposed method and scheduling results in real industrial settings.
Vision based Pose domain characterization of an Unmanned Aerial Vehicle using Interval Analysis

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Vision based Pose domain characterization of an Unmanned Aerial Vehicle using Interval Analysis Ide-Flore Kenmogne, Vincent Drevelle, Eric Marchand
Juxtaposition of Load Balancing Algorithms in Cloud Computing using Cloud Analyst Simulator

Computing is a term which is generally used in reference to Internet. The whole Internet can be viewed as a cloud. The cloud is quickly changing a worldwide network of computers into the largest single, "virtual" computer in the world. This includes sharing of resources which increases the load on single machine. Thus the overall performance degrades and this problem is named as load balancing. Load Balancing is one of the challenging issues now a day. To overcome from this problem be reassign the load by implementing various algorithms introduced for this problem. In this paper we study and compare various algorithms, techniques used to solve the problem of Load Balancing and Distributed Load Balancing.
Control methods for data flow in communication networks

In this dissertation, we investigate various control methods for data flow in communication networks. First, we develop a rate-based flow controller for self-similar network traffic, which consists of a robust control block and an adaptive LMMSE capacity predictor. The controller guarantees robust stability against time-varying time delay uncertainties and improves the transient response by predicting the self-similar cross traffic. Window-based congestion control methods are also explored for TCP traffic on IP networks. We propose a variable structure approach in Active Queue Management (AQM) support Explicit Congestion Notification (ECN). By analyzing the robustness and performance of the control scheme for the nonlinear TCP/AQM model, we show that the proposed design has good performance and robustness with respect to the uncertainties of the round-trip time ( RTT) and the number of active TCP sessions, which are central to the notion of AQM. Alternatively, we design robust AQM controllers for the linearized TCP/AQM model, with the presence of uncertain time delays. The performance is analyzed and a switching control scheme is introduced to improve the system performance. Motivated by the Linear Parameter Varying (LPV) nature of the linearized TCP/AQM model, a switching control method is further investigated for LPV systems where we provide some stability conditions in terms of the dwell time and the average dwell time.
Estimate of signal probability in combinational logic networks

Two methods for the calculation of node signal probabilities in combinational networks are presented. These techniques provide a better accuracy than existing algorithms and a deeper insight in the effects of first-order correlations due to multiple fan-out reconvergences. The proposed algorithms are shown to compare favorably with existing procedures in the analysis of significant benchmarks, both in accuracy and in computational efficiency. <<ETX>>
Skeleton-Based Human Action Recognition via Screw Matrices

With the recent advent of low-cost acquisition depth cameras, extracting 3D body skeleton has become relatively easier, which significantly lighten many difficulties in 2D videos including occlusions, shadows and background extraction, etc. Directly perceived features, for example points, lines and planes, can be easily extracted from 3D videos such that we can employ rigid motions to represent skeletal motions in a geometric way. We apply screw matrices, acquired by using rotations and translations in 3D space, to model single and multi-body rigid motion. Since screw matrices are members of the special Euclidean group SE(3), an action can be represented as a point on a Lie group, which is a differentiable manifold. Using Lie-algebraic properties of screw algebra, isomorphic to se(3), the classical algorithms of machine learning in vector space can be expanded to manifold space. We evaluate our approached on three public 3D action datasets: MSR Action3D dataset, UCF Kinect dataset and Florence3D-Action Dataset. The experimental results show that our approaches either match or exceed state-of-the-art skeleton-based human action recognition approaches.
An Object-Oriented Software Model for Students’ Registration and Examination Result Processing in Nigerian Tertiary Institutions

The principles of Object-Oriented Software Engineering are employed to model a software application known as Undergraduate Registration and Examination Processing System (SPERU) for Nigerian Tertiary institutions. Rapid Application Development (RAD) tools are utilized in its implementation to achieve an excellent software system. SPERU is herein presented , as a typical instance of a well modelled software system, that testifies to the beauty, power and supremacy of the Object-Oriented paradigm The result of applying software predictor metrics indicates that SPERU is reliable and elegant.
A Survey of Delay Tolerant Technology in Internet of Things

Internet of Things (IoT) focuses on the IntelliSense interaction between the human, agriculture and the environment. This paper presents a survey on the delay-tolerant technology (DT) in IoT, which is no reliable end to end path and the storewaittransmit mechanism is used to ensure delivery success rate in the case of long delay. DT represents a fairly new networking paradigm that allows interconnection between devices that current networking technology cannot provide. This paper provides an overview of several DT models and discusses typical node mobility models in IoT, including mobility method, data delivery scheme and queue management scheme. Several representative routing algorithms of DT are discussed in detail for different IoT applications with high efficiency and low consumption.
Reading and Grammar Learning through Mobile Phones.

This paper describes an ongoing language-learning project, three years into its development. We examine both the feasibility and the limitations of developing English reading and grammar skills through the interface of mobile phones. Throughout the project, reading and grammar materials were regularly sent to students’ mobile phones. Students read or took part in any aspect of the materials that appealed to them. Information gathered from participants and server logs indicate that reading and learning grammar using mobile devices is regarded as a positive language experience. However, the data also indicate that the success of any mobile learning project could be limited unless certain criteria are applied. This includes (a) providing engaging learning materials that are neither too long nor overly-demanding; (b) a proper degree of teacher monitoring; (c) student involvement; (d) the need for incentives; (e) a respect for privacy; and (f) a safe and secure mobile-learning technical environment.
Survey of Indexing Techniques on Moving Objects in Spatio Temporal Networks for PPF

- In spatial-temporal applications, moving objects identify the particular locations called location based services and update the locations continuously to the server. Due to the enormous collections of moving objects, many spatial-temporal access techniques are developed to process user queries efficiently. Spatial-temporal access methods are classified into four categories: (1) Indexing the past data, (2) Indexing the current data, (3) Indexing the future data, and (4) Indexing data at all points of time [1]. Spatial objects whose position changes for every seconds. It helps to find the moving objects i.e., vehicles moving on the road networks, finding the position of the aeroplanes or any criminals etc. To achieve this an innovative indexing techniques needed to update data frequently.
UNIVERSIDADE FEDERAL DO PARÁ INSTITUTO DE TECNOLOGIA PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA EXPERIMENTOS DE MINERAÇÃO DE DADOS APLICADOS A SISTEMAS SCADA DE USINAS HIDRELÉTRICAS

O atual modelo do setor eletrico brasileiro permite igualdade de condicoes a todos os agentes e reduz o papel do Estado no setor. Esse modelo obriga as empresas do setor a melhorarem cada vez mais a qualidade de seu produto e, como requisito para este objetivo, devem fazer uso mais efetivo da enorme quantidade de dados operacionais que sao armazenados em bancos de dados, provenientes da operacao dos seus sistemas eletricos e que tem nas Usinas Hidreletricas (UHE) a sua principal fonte de geracao de energia. Uma das principais ferramentas para gerenciamento dessas usinas sao os sistemas de Supervisao, Controle e Aquisicao de Dados (Supervisory Control And Data Acquisition - SCADA). Assim, a imensa quantidade de dados acumulados nos bancos de dados pelos sistemas SCADA, muito provavelmente contendo informacoes relevantes, deve ser tratada para descobrir relacoes e padroes e assim ajudar na compreensao de muitos aspectos operacionais importantes e avaliar o desempenho dos sistemas eletricos de potencia. O processo de Descoberta de Conhecimento em Banco de Dados (Knowledge Discovery in Database - KDD) e o processo de identificar, em grandes conjuntos de dados, padroes que sejam validos, novos, uteis e compreensiveis, para melhorar o entendimento de um problema ou um procedimento de tomada de decisao. A Mineracao de Dados (ou Data Mining) e o passo dentro do KDD que permite extrair informacoes uteis em grandes bases de dados. Neste cenario, o presente trabalho se propoe a realizar experimentos de mineracao de dados nos dados gerados por sistemas SCADA em UHE, a fim de produzir informacoes relevantes para auxiliar no planejamento, operacao, manutencao e seguranca das hidreletricas e na implantacao da cultura da mineracao de dados aplicada a estas usinas.
Software for the calculation of genetic linkage maps

JoinMap is developed by Kyazma B.V. in collaboration with statistical geneticists of Biometris of Wageningen UR (www.biometris.wur.nl). The sales and support are taken care of by Kyazma B.V. Kyazma is a trademark of Kyazma B.V. Other brand and product names are (registered) trademarks of their respective holders.
TRAC Innovative Visualization Techniques

Abstract : The purpose of this report is to discuss a method to design visualizations. A mission essential task of the TRADOC Analysis Center (TRAC) is to conduct studies that inform key decisions my by Training and Doctrine Command (TRADOC), Army, and Joint leaders. Because of the complexity of these decisions, TRAC analysts have a constant challenge to present complex analysis results in a simple and sophisticated way. Therefore, TRAC analysts need a way to analyze the effectiveness of their visualization design choices. Currently, TRAC does not have a methodology to analyze visualizations used to support an analysis story. Our research team developed a visualization design methodology to create effective visualizations that support an analysis story. First, we based our methodology on the latest research on design thinking, cognitive learning, and visualization principles. Second, our methodology provides a solid foundation to develop, analyze, and present visualizations. We accomplish this by utilizing a story planning outline and presentation format that is audience focused and presents the most critical information necessary for decision knowledge. Finally, our methodology extends the goodness of the current TRAC documentation standard by fostering communication focused on the decision maker; rapidly prototyping visualizations that foster innovation and creativity; and utilizing a repeatable methodology that provides credibility to the visualization choices used in a presentation to a decision maker.
Computer- und korpuslinguistische Verfahren für die Analyse massenmedialer politischer Kommunikation: Humanitäre und militärische Interventionen im Spiegel der Presse

Zusammenfassung. Dieser Beitrag zeigt am Beispiel eines aktuellen Forschungsprojekts auf, welche Potenziale computerund korpuslinguistische Verfahren für eine multilinguale politikwissenschaftliche Medientext-Analyse bieten. Wir führen in die Forschungsfragen ein, die in der an der FU Berlin angesiedelten Medienanalyse zu militärischen und humanitären Interventionen bearbeitet werden, erläutern die Erfahrungen, die dabei mit vorhandenen computerlinguistischen Verfahren bisher gemacht wurden und diskutieren die Möglichkeiten, die innovative Werkzeuge der Computerlinguisten der Universität Potsdam erschließen.