Miracle-dz/UniFAR-FTUs huggingface dataset:
Angka Kejadian Koagulasi Intravaskular Diseminata pada Pneumonia

Latar belakang. Pneumonia merupakan penyebab kematian utama pada bayi dan balita di negara berkembang. Sitokin pada pneumonia yang diproduksi akibat inflamasi paru secara berlebihan. Sehingga menyebabkan kaskade koagulasi sistemik teraktivasi yang berakhir pada trombosis sistemik yang akan menyebabkan keadaan kritis dan seringkali berakhir dengan kematian. Tujuan . Mengetahui profil koagulasi dan prevalensi koagulasi intravaskular diseminata (KID) pada pasien pneumonia yang dirawat inap. Metode. Studi deskriptif analitik dengan desain potong lintang dilakukan di ruang rawat Departemen Ilmu Kesehatan Anak RSCM antara 1 Februari 2010 sampai 28 Februari 2011. Hasil. Tiga puluh enam persen subjek penelitian mengalami trombositopenia, 13,4% mengalami pemanjangan protombine time (PT), dan 19,6% mengalami penurunan kadar fibrinogen. Didapatkan 83,5% subjek penelitian memiliki kadar D-dimer yang tinggi dan 64,9% di antaranya meningkat sangat tinggi. Kejadian KID 17,5% subjek dan seluruhnya mengalami perdarahan. Pada 88,2% pasien KID mengalami trombositopenia dengan rasio prevalens 32,5 (95% IK 6,70-157,57). Kesimpulan. Profil koagulasi pasien pneumonia yang dirawat di Departemen Ilmu Kesehatan Anak RSCM 36% mengalami trombositopenia, pemanjangan PT 13,4%, penurunan kadar fibrinogen 19,6%, dan peningkatan kadar D-dimer 83,5% . Koagulasi intravaskular diseminata terjadi 17,5% (17/97) pasien pneumonia yang dirawat.
Fast identification of state-space models via exploitation of displacement structure

A novel fast algorithm for the identification of state-space models is presented. This approach exploits the displacement and low-rank plus shift structures of the matrices that arise in the identification procedure to reduce the computational cost from O(MN/sup 2/+NM/sup 2/+M/sup 3/) to O(MN+M/sup 2/) flops, and storage from O(M/sup 2/+MN+N/sup 2/) to O(N+M/sup 2/) bytes. Such reductions of computational burden and storage requirement may allow online identification of state-space models in many potential applications. The proposed identification technique was applied to a two-input, two-output simulated system to validate the algorithm. <<ETX>>
Elementary Excitations In Solids

Thank you very much for downloading elementary excitations in solids. As you may know, people have look hundreds times for their favorite novels like this elementary excitations in solids, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some harmful virus inside their laptop. elementary excitations in solids is available in our digital library an online access to it is set as public so you can get it instantly. Our digital library spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the elementary excitations in solids is universally compatible with any devices to read.
Beheersing van transactionele relaties

Binnen het vakgebied ‘management accounting’ heeft de ‘make or buy’-beslissing van oudsher veel aandacht gekregen. Indien het management van een bedrijf overweegt om een activiteit die in eigen beheer wordt uitgevoerd, uit te besteden, moet dat volgens traditionele normatieve theorievorming worden gerechtvaardigd met een relevante kostenbenadering: beslissingsafhankelijke productiekosten van het alternatief ‘make’ moeten worden vergeleken met de inkoopprijs bij derden (‘buy’). Gietzmann (1996) heeft erop gewezen, dat de uit de neoklassieke economische theorie stammende relevante kostenbenadering berust op een wel erg simpel besluitvormingsmodel en op een wel erg simpel model van interactie tussen organisaties. Organisaties worden in feite gezien als productiefuncties, ingeklemd tussen markten. Er wordt van uitgegaan, dat elke organisatie wordt bestuurd door één actor, die kosteloos over alle benodigde informatie kan beschikken. Besturingsproblemen als gevolg van onzekerheden in de omgeving en van complexiteit in de productiefunctie worden niet als zodanig herkend. Als gevolg van onzekerheid en complexiteit ontstaat in de praktijk vaak een noodzaak tot decentralisatie van besluitvorming. Omdat de noodzaak daartoe niet past in de neoklassieke veronderstellingen, worden de uit decentralisatie voortvloeiende kosten van coördinatie en motivatie niet in de afweging van ‘make or buy’ betrokken. Hierdoor kunnen de economische consequenties van de keuze voor ‘make’ sterk worden onderschat. Hetzelfde geldt overigens voor het alternatief ‘buy’, dat om dezelfde genoemde redenen ook besturingskosten met zich meebrengt. In de praktijk zullen de besturingskosten van het alternatief ‘make’ uiteraard afwijken van die van het alternatief ‘buy’. Daarom is het wel degelijk van belang om met dergelijke kosten rekening te houden.
ADM Integration and software development methods

Existe una amplia lista de metodologías, estándares y procesos en tecnologías de la información que sirven de guía al interesado para resolver o apoyar la solución de problemas, por ejemplo, ciclo de vida de desarrollo, calidad del producto, estandarización de procesos, gobierno de procesos, gestión de proyectos, arquitecturas de software, de sistemas o empresarial entre otras. El compendio es extenso y dinámico en la media que año tras año se crean nuevas metodologías, guías y estándares que intentan mejorar la solución o resolver nuevos problemas. El marco de trabajo empresarial TOGAF posee una facilidad natural para absorber estándares de manera dinámica gracias a su alto nivel de abstracción, esta característica le permite incorporar a su repositorio artefactos construidos a partir diferentes estándares o métodos de la industria, por ejemplo Cobit o Itil para gobernabilidad y gestión de infraestructura o inclusive entregables construidos en otros marcos de trabajo como Zachman. El presente artículo expone los enfoques que existen para articular las metodologías de desarrollo de software bien sea ágiles o disciplinadas con las fases de desarrollo del método ADM del marco de trabajo TOGAF.
Dynamic recurrent neural networks: Theory and applications

This special issue illustrates both the scientific trends of the early work in recurrent neural networks, and the mathematics of training when at least some recurrent terms of the network derivatives can be non-zero. Herein is a brief description of each of the papers. We have organized this description into two parts. The first part contains the papers that are mainly theoretical, and the second part contains the papers that are mainly applications. The order of papers is alphabetical by first author.
Text sentiment analysis based on ensemble learning method

The EL-based(Ensemble Learning)sentiment analysis method takes three different high-quality sentiment analysis models as basic classifiers, and combines these basic classifiers into a final classifier. In order to overcome the shortcoming of the traditional combination method that only considers the different results of the components, different features are also considered. Experimental results show that the accuracy rate of the proposed method on an English movie review corpus is 88.2%.
An Evaluation of SDN Based Network Virtualization Techniques

With the software-defined networking trend growing, several network virtualization controllers have been developed in recent years. These controllers, also called network hypervisors, attempt to manage physical SDN based networks so that multiple tenants can safely share the same forwarding plane hardware without risk of being affected by or affecting other tenants. However, many areas remain unexplored by current network hypervisor implementations. This thesis presents and evaluates some of the features offered by network hypervisors, such as full header space availability, isolation, and transparent traffic forwarding capabilities for tenants. Flow setup time and throughput are also measured and compared among different network hypervisors. Three different network hypervisors are evaluated: FlowVisor, VeRTIGO and OpenVirteX. These virtualization tools are assessed with experiments conducted on three different testbeds: an emulated Mininet scenario, a physical single-switch testbed, and also a remote GENI testbed. The results indicate that network hypervisors bring SDN flexibility to network virtualization, making it easier for network administrators to define with precision how the network is sliced and divided among tenants. This increased flexibility, however, may come with the cost of decreased performance, and also brings additional risks of interoperability due to a lack of standardization of virtualization methods.
A computationally efficient adaptive array algorithm for the uplink of WCDMA systems

A computationally efficient pilot symbol-assisted adaptive array algorithm, which combines LS-DRMTA adaptive algorithm with LMS adaptive algorithm, is developed and applied to the pilot symbol-assisted uplink in a WCDMA system. According to the uplink frame structure of WCDMA, the spreading sequences of pilot symbols of each slot are used as the reference signals for updating the weight vectors of the adaptive antenna arrays. The computational complexity of the new algorithm is much lower than LS-DRMTA, and thus it is better suited for WCDMA systems. Furthermore, the simulation results show the new algorithm can achieve better performance than LS-DRMTA in mobile communication environments.
An algorithm for removing cloud and mist from remote sensing images based on cloud layer coefficients

The procedure of processing digital image through wavelet decomposition is analyzed.The frequency distributions of wavelet decomposition coefficients are investigated.The approach to separate the cloud and mist from the scenery by wavelet transformation is presented.The prior theory of dark channel is discussed.Differences of dark pixel values between the cloud and mist and the scenery are analyzed.On this basis,the concept of cloud layer coefficients is put forward.An algorithm for removing the cloud and mist from remote sensing images is proposed.That is,thickness of the cloud and mist of every pixel is estimated according to its cloud layer coefficient.The cloud and mist is attenuated by processing detail coefficients in high levels,and the covered scenery is brought out by processing those in low levels.The implementation steps are described completely.Removing cloud and mist experiments are carried out and their results are evaluated.It is proved that the algorithm is superior to the weighted wavelet algorithm and wavelet threshold algorithm.
Uniqueness typing for a higher-order language

We investigate type-based analysis for a higher-order channel passing language with strong update, whereby messages of a dierent kind are communicated over the same channel. In order to reason about such pro- grams, our type system employs the concept of uniqueness to be able to assert when it is safe to change the object type a channel. We design a type system based on this concept and prove that our type system is sound, meaning that it only accepts programs that do not produce runtime errors.
Local Salient Regions Based Natural Scene Recognition

Scene recognition is a key problem in mobile robot topological navigation.For unknown environments,a natural scene recognition approach based on visual local salient regions is presented.Firstly,a feedback saliency detection model(FSDM)is presented to carry out bottom-up scene image analysis.Then,according to the salient positions,automatic scale selection is realized based on fractal dimension to build the local salient regions with appropriate size.Those salient regions are represented by 3 invariant features of gradient orientation,moment and canonical hue.They are used for scene recognition in terms of their match ratio.Experiments show that FSDM can obtain higher accuracy.The scene recognition experiments in both indoor and outdoor environments show that the approach has high stability and tolerance compared to the method based on global appearance when scale and viewpoint etc changed.The accuracy of recognition for static scene is higher.
Multilingual Collaboration in Electronic Meetings

Groups in which participants do not speak the same language frequently find communication difficult. Yet, multilingual meetings are common as a form of collaboration. To overcome this language barrier, banks, government agencies, hospitals, the courts, and many other institutions have relied upon human translators to enable meeting participants to exchange ideas and opinions. For example, the United Nations General Assembly’s discussions, conferences within the European Union, multinational corporations’ business negotiations, and many other meetings are conducted almost daily, requiring large amounts of interpreters’ scarce expertise and time. In addition to the problems of translation efficiency and effectiveness, these meetings have the same limitations as those involving a single language: (1) only one participant can speak at a time, (2) comments must be transcribed manually for a permanent record, and (3) many group members do not participate because of shyness or because other speakers monopolize the conversation. Group support systems (GSS) have automated the meeting process and improved the productivity of groups needing to share ideas (Dennis, George, Jessup, Nunamaker, & Vogel, 1988). By integrating machine translation (MT) with a GSS, multilingual groups can enjoy the same benefits as monolingual groups. This paper summarizes research conducted using automatic and semi-automatic natural language translation in electronic meetings and shows how a multilingual GSS (MGSS) can improve communication and collaboration.
Using Technology to Build a Community of Writers in Developmental Writing.

Using technology in a developmental classroom, particularly a classroom platform such as WebCT, can help provide a sense of community in a developmental writing course. The rationale for designing a hybrid developmental writing course is discussed as well as the ways in which students perceived themselves as “real writers” as a result of the way that their writing was submitted and critiqued on WebCT. A blended learning environment has become an integrated component of writing instruction at the two-year branch campus that is the location of this study.
Development of object oriented CAD system for broach

Overall design plan and modular function of CAD system for broach based on objectARX for AutoCAD2000 are introduced. Utilizing application of MFC for Visual C6 0 in objectARX, the object oriented CAD system for broach is developed. By means of this system, the integration of design and drawing for broach is accomplished.
Spatio-temporal adaptive penalized splines with application to Neuroscience

Data analysed here derive from experiments conducted to study neurons' activity in the visual cortex of behaving monkeys. We consider a spatio-temporal adaptive penalized spline (P-spline) approach for modelling the firing rate of visual neurons. To the best of our knowledge, this is the first attempt in the statistical literature for locally adaptive smoothing in three dimensions. Estimation is based on the Separation of Overlapping Penalties (SOP) algorithm, which provides the stability and speed we look for.
Second Language Learning and Teaching: Complementary Perspectives

“Second Language Learning and Teaching: Complementary Perspectives” is a research-based book contain 8 chapters, primarily designed as a reference book for both undergraduate and graduate students as well as researchers in language acquisition and teaching. It is also an up-to-date text for teacher trainers who want to keep up with developments in field, and stay informed about predominant theories.
Focused Crawler Based on Simulated Anneal Algorithm

Focused crawler is the core and foundation of the topic-specific search engine.Special crawling strategy quality gives a direct impact on search results.In order to select more relevant pages,through using the simulated annealing mechanism to choose the next link to visit,makes those high "overall value "link have the opportunity to be selected early in the search,and using "Tunneling" to broaden the searching scope.When calculating the link value,consider the value of the page content and the link text synchronously,and according their different impact to the link value,gives them different weight.Experiments indicate that the method has a good effectiveness.
MICROCONTROLLER BASED ISOLATED BOOST DC-DC CONVERTER

ZVS-PWM isolated boost DC-DC converter. It takes the supply from fuel cell battery at the input side compared to the previous full bridge converter, This half bridge converter to produce the same efficiency. The advantages of the paper is to reduce the number of devices and the mean time to reduce the losses, correspondingly to reduce the space and design cost. The system is simple and easy to operate the entire circle without more additional devices. It is used for medium and high power application. Zero voltage switching is applied in all the inverters. It is achieved the power flow in either direction. The circuit is compact packaging and reduce the losses. The simulation results are of closely agree with the theoretical approach a high efficiency achieved by using a minimal number of electronic devices working in the soft switching mode. It is operated at the frequency of 55 khz. Terms DC-DC converter, soft switching, bi-directional power flow, conduction, losses, zero current switching and zero voltage switching.
An Analysis of Non-Hardware Characteristics of Laptop Computers by using Hedonic Price Model

The main purpose of this study is to analyze whether or not prices of laptop computers reflect their varying degrees of non-hardware characteristics such as the number of aftersale service center and the inclusion of OS software. For this purpose, we have employed Hedonic Price Model by which the interactions among hardware and non-hardware components could be analyzed. As a result, we have found that the number of after-sales service center and the inclusion of OS have a tendency to increase the prices of the laptop computers. This result is consistent with the following hypothesis: the more the number of after-sales service center is, the higher consumers are willing to pay for the laptop computers, when all other things being equal or held constant. The same conclusion can be applied to the case of the inclusion of OS; consumers are willing to pay more with the inclusion of OS. We have also found that after-sale service provided by laptop computer manufactures is not free, so that manufactures have a motivation to provide more aftersale service centers to get more profit.
Iranian EFL learners’ identity construction in a critical reflective course: a case of an online course

ABSTRACT The present mixed-methods research examined the identity and attitude of Iranian English language learners as a result of their participation in an online critical reflective course. The participants were 38 English language students who attended ten online sessions within a five-month English language course. Their online posts underwent inductive qualitative content analysis and subsequently five themes were extracted. In addition, the content of the first and last two sessions were analysed quantitatively. A validated questionnaire was also administered and 18 participants were interviewed. Qualitative and quantitative content analyses of the data revealed eight finalised codes. The analysis of the findings showed that although the participants’ identity and attitudes did not undergo material changes, their awareness of the intercultural and interlingual issues, between Persian and English language and culture, was sharpened. In addition, their online identities proved to be not set off from their offline identities nor identical to them but interrelated.
A Survey on Scalable Data Security and Load Balancing in Multi Cloud Environment

Internet and network application are growing very fast and use of cloud computing has increased rapidly in today’s world. Cloud computing provides many advantages such as low cost, on-line, on-demand services pay per use basis and accessibility of data. Security in cloud computing is major issue, as user often store sensitive information in cloud storage provider but these providers may be untrusted. Encryption algorithms play a main role in information security systems. Several issues as scalability, security, performance, integrity etc. are discussed so far. This paper surveys recent research related to multi cloud security and address possible solution. This paper introduces a better load balance technique for public cloud based on data distribution system over the database server. It is found in research that use of multi-cloud providers to maintain security has received less attention than single clouds. This work aims to promote the use of multi cloud due to its ability to reduce security risks that affect the cloud computing user. The way to secure the data using different compression and encryption algorithms and to hide its location fro m the users that stores and retrieves it.
Mixture density networks for distribution and uncertainty estimation

The deep learning techniques have made neural networks the leading option for solving some computational problems and it has been shown the production of the state-of-the-art results in many fields like computer vision, automatic speech recognition, natural language processing, and audio recognition. In fact, we may be tempted to make use of neural networks directly, as we know them nowadays, in order to make predictions and solve many problems, but if the decision that has to be taken is of high risk. For instance, we could have a problem regarding the control of a nuclear power plant or the prediction of the shares evolution in the market; in this case, it would be important to look for methods that allowed us to add more information concerning the certainty of those predictions. This Master’s thesis is divided into three parts: Firstly, we will analyse the state-of-the-art regarding Mixture Density Network models to predict an entire probability distribution for the output and we will develop an implementation to give solutions for many of the numerical stability problems that characterise this type of models. Secondly, in order to propose an initial solution for the uncertainty problems introduced above, we will focus on the extraction of a confidence factor by using neural network outputs of a problem for which we are only interested in the prediction of something if we have a minimum certainty about the prediction we made. In order to do it, we will compile the current literature methods to measure uncertainty through Mixture Density Networks and we will implement all of these works. Consequently, we are going to to go into detail about the concept of uncertainty and we will see to what extent we are able to propose a solution by using neural network models for the different aspects that include such concept. Finally, the third part will refer to several proposals to measure the confidence factor obtained with the use of Mixture Density Network concerning the problem proposed. After all the work, our goals will be achieved: we are going to make a stable implementation for all the problems that we have proposed for Mixture Density Networks and we will publish it publicly in our GitHub repository[9]. We will be able to implement the state-of-theart methods that will allow us to obtain a confidence factor and finally we will be able to propose a method that obtains the expected results regarding the parameters that represent the confidence factor.