Miracle-dz/UniFAR-FTUs huggingface dataset:
Microsoft Virtualization: Master Microsoft Server, Desktop, Application, and Presentation Virtualization

Virtualization technologies help IT organizations in three ways: cost-cutting, ease of administration, and the overall effect of IT on the environment. Virtualization cuts costs by reducing the amount of capital resources (equipment), power, and cooling to run an IT infrastructure. Because of the tools that are involved in virtualization, it also reduces the burden of IT management significantly. Finally, by reducing the amount of cooling, power, and other emissions from these servers, virtualization can help IT organizations become more "green. " Microsoft growth is up from 2006, when it held an 8% market share to 23%. When this report was released, Hyper-V had just started shipping, and is expected to make substantial market gain for Microsoft. A poor economy will actually help the growth of virtualization. Virtualization will gain IT dollars at the expense of other technologies for one reason: cost. Technologies that require high up-front expenditures but take time to generate ROI will be put on hold, while technologies like virtualization that promise immediate cost savings will enjoy broader adoption. Currenty, only 7% to 8% of servers are virtualized (worldwide) with many IT executives researching or planning to implement in the next 18 to 24 months. Covers Microsoft virtualization products completely, including Hyper-V Includes a special section on securing virtual infrastructure Gives hands-on instructions to help understand and implement Microsoft solutions Table of Contents Chapter 1: Introduction to Virtualization Chapter 2: Understanding Microsoft Virtualization Strategies Chapter 3: Installing Windows 2008 Server Core and Hyper-V Chapter 4: Managing Hyper-V Chapter 5: Installing and Configuring Virtual Machine Manager 2008 Chapter 6: Hyper-V and High Availability Chapter 7: Creating Virtual Machines and Templates Chapter 8: Performing Physical to Virtual and Virtual to Virtual Migrations Chapter 9: Monitoring and Managing a Virtual Infrastructure Chapter 10: Creating a Dynamic Datacenter with Microsoft System Center Chapter 11: Application Virtualization (Softgrid) Chapter 12: Deploying Softgrid Packages Chapter 13: Presentation Virtualization (Terminal Services) Chapter 14: Integrating Application and Presentation Virtualization Chapter 15: Desktop Virtualization Appendix A: Migrating Virtual Machines from Virtual Server 2005
Comparative Analysis of Model based Techniques

World Wide Web consists of huge amount of information and this amount is also increases day-by-day. Prediction of web user behavior is becoming a challenge of today competitive edge of World Wide Web. Only prediction of the next web page is not sufficient, evaluation of prediction models is important due to the advantages and disadvantages of every model. If high prediction accuracy is achieved with minimum complexity, then the result of prediction is helpful. In this paper we have evaluated and compare two probabilistic models Markov Model and Bayes Network on the basis of three parameter elapsed time during preprocessing, training time and prediction accuracy. Experiments are conducted on two different real datasets. To model the user navigation on the web and predict the next action taken by the user widely used model is traditional Markov Model. There are some serious limitations on Markov Model. Bayes network is another alternative to predict the next accessed web page but further they have some limitations due to which we can't achieve high prediction accuracy. In this paper we use the Back Propagation neural network algorithm with the combination of either Markov model or Bayes network so that the prediction accuracy can be improved till 95%.
A Smart Visitors’ Notification System with Automatic Secure Door Lock Using Mobile Communication Technology

The paper presents the development of an automated security system to automate the entry of visitors, providing more flexibility of managing their record and securing homes or workplaces. Face recognition is part of this system to authenticate the visitors. A cost effective and SMS based door security module has been developed and integrated with the GSM network and made part of this system to allow communication between system and owner. This system functions in real time as when the visitor’s arrived it will detect and recognizes his face and on the result of face recognition process it will open the door for authorized visitors or notifies and allows the owner’s to take further action in case of unauthorized visitor. The proposed system is developed and it is successfully ensuring security, managing records and operating gate without physical interaction of owner.
ANC System for Noisy Speech

The paper explains the effectiveness of Active Noise Control (ANC) System based on adaptive filter for reducing noise from a noisy speech. ANC generally reduces low frequency noise and creates a quiet zone. In this paper a feedforward ANC is used for reducing low frequency noise from a noisy speech signal for improving speech quality. Secondary path transfer function has been compensated using FXNLMS (Filtered-X NLMS) algorithm. The proposed system is analyzed and simulated on a digital computer. The performance of the system is evaluated by measuring noise power reduction in the noisy speech by retaining the intelligibility of the speech signal. Simulation results reveal that the method can reduce noise power to a level of -11.6dB.
Cerebral Blood Flow at High Altitude

Abstract Ainslie, Philip N. , and Andrew W. Subudhi. Invited Review: Cerebral blood flow at high altitude. High Alt Med Biol. 15:133–140, 2014. —This brief review traces the last 50 years of research related to cerebral blood flow (CBF) in humans exposed to high altitude. The increase in CBF within the first 12 hours at high altitude and its return to near sea level values after 3–5 days of acclimatization was first documented with use of the Kety-Schmidt technique in 1964. The degree of change in CBF at high altitude is influenced by many variables, including arterial oxygen and carbon dioxide tensions, oxygen content, cerebral spinal fluid pH, and hematocrit, but can be collectively summarized in terms of the relative strengths of four key integrated reflexes: 1) hypoxic cerebral vasodilatation; 2) hypocapnic cerebral vasoconstriction; 3) hypoxic ventilatory response; and 4) hypercapnic ventilatory response. Understanding the mechanisms underlying these reflexes and their interactions with one another is .
The knowledge collective: a multi-layer, multi-agent framework for information management in an intelligent knowledge base

The Knowledge Collective (TKC) is a multi-layer, multi-agent framework for information management in an intelligent knowledge base that supports a collection of agents called MicroDroids. The MicroDroids provide information management capabilities through a variety of interfaces for experts, human users, and software components. This information is stored in a variety of internal structures (e.g., Java objects, rules, relational data). The main concept is that information is stored in a format that is natural to the type of information being maintained (e.g., data, metadata, ontologies, concept maps, lexicons, rules). The Knowledge Collective makes ontology-based information accessible to many end users, maintainable by domain experts and reusable by many users across many applications without their needing to know how or where the information is stored. The Knowledge Collective's first use is in version 4 of CIRCSIM-Tutor, an Intelligent Tutoring System developed by Martha Evens and her group at the Illinois Institute of Technology in Chicago, IL. The uniqueness of The Knowledge Collective is in the combination of technologies for problem solving and the use of a multi-agent system where each MicroDroid manages its own information and works with other MicroDroids to solve specific problems. Each MicroDroid reasons about the information it is managing using an Ontology Inference Engine (ONTIE) that is capable of combining all of its internal information structures for the purpose of access, maintenance and problem solving, especially involving Qualitative Reasoning.
Wearable Computing und RFID in Produktion und Logistik - Ansätze zur bereichsübergreifenden Nutzung digitaler

Logistics journal: Nicht referierte Veroffentlichungen, Vol. 2011, Iss. - Die voranschreitende Entwicklung von Konzepten und Systemen zur Nutzung digitaler Informationen im industriellen Umfeld eroffnet verschiedenste Moglichkeiten zur Optimierung der Informationsverarbeitung und damit der Prozesseffektivitat und -effizienz. Werden die relevanten Daten zu Produkten oder Prozessen jedoch lediglich in digitaler Form zur Verfugung gestellt, fallt ein Eingriff des Menschen in die virtuelle Welt immer schwerer. Auf Grundlage dessen wird am Beispiel der RFIDTechnologie dargestellt, inwiefern digitale Informationen durch die Verwendung von in den Arbeitsablauf integrierten Systemen fur den Menschen nutzbar werden. Durch die Entwicklung eines Systems zur papierlosen Produktion und Logistik werden exemplarisch Einsatzszenarien zur Unterstutzung des Mitarbeiters in Montageprozessen sowie zur Vermeidung von Fehlern in der Kommissionierung aufgezeigt. Dazu findet neben einer am Kopf getragenen Datenbrille zur Visualisierung der Informationen ein mobiles RFID-Lesegerat Anwendung, mit Hilfe dessen die digitalen Transponderdaten ohne zusatzlichen Aufwand fur den Anwender genutzt werden konnen.
Radiothérapie des cancers métastatiques ou oligométastatiques en dehors des irradiations à visée antalgique. État des lieux en 2010 avec focus sur l'Asco 2010

The role of radiation therapy in metastatic disease has evolved from palliative to potentially curative intent for selected oligometastases using highly conformal radiation techniques, including extracranial stereotactic body radiotherapy (SBRT) in the last decade. SBRT has a potential to use small numbers of large doses aiming at achieving high rates of local control while preserving the quality of life even in highly pretreated patients. A wide range of techniques, doses, and dose fractionation schedules can be found. However, the 2-year local control is around 80% for lung metastases with corresponding 2-year survival of 50%, and a 5% rate of grade III or higher radiation toxicities. The 2-year local control varies between 57 and 92% for liver metastases and radiation-induced liver disease is exceptional provided that 700 cm3 of healthy liver are irradiated to less than 15 Gy in three fractions or more. Stereotactic radiation is also particularly interesting for spinal, and cranial metastases and reirradiations. Also, it has come into focus that associations of chemotherapy or targeted therapies and radiation may be used for optimized treatment of limited metastatic disease and that irradiation of the primary tumor may be recommended in the context of metastatic disease. It also appears that the definition of target volumes for palliative radiation therapy and scores to assess for life expectancy-based need for irradiation should be improved.
Free-riding Resilient Video Streaming in Peer-to-Peer Networks

Ministry of Economic Affairs through the BSIK program (BSIK 03025). This work was carried out at the ASCI graduate school. ASCI dissertation series number 190. Preface The thesis that you see in front of you would not be here if not for the many people who helped and supported me during my PhD track. After all, it is through interaction with others that we can shape our thoughts and derive solutions to the problems that we face. But also support outside of work is vital in order to sustain a project which takes several years to complete. Over the years, the list of people who deserve a big " thank you " has grown, as such things inevitably do. I start with my supervisor Dick Epema and my promotor Henk Sips. Not only did they teach me how scientific papers are written, their guidance and critical thinking were essential in shaping this work. They, and my other co-authors, aided me in the research and writing. But support and critical thinking was also provided by many other colleagues, such as Paweł Garbacki, Alexandru and Ana Iosup, and Gertjan Halkes. I would like to thank the Parallel and Distributed Systems Group at Delft University of Technology for providing me with an environment for obtaining a PhD. I thank Freeband Communication for the funding of my research, as well as for providing a research context in the form of the I-Share research project, which focuses on sharing technologies in virtual communities. For their strong support from home, I like to thank my wife Christie and my daughter Selene. Both of them provide the love that I need to function, to allow me to focus on the complex research questions, and to help deal with the inevitable stress. Similarly, my parents Marga and Nanne, as well as my sister Karin, have supported me throughout my PhD track. As you all know, it is impossible to provide a complete list. I thank you for your support, or at the very least, for reading this preface.
Ensemble methods for multi-label learning of compositional data

Compositional data are a speciﬁc type of multivariate data, in which individual variables represent relative contributions to a whole, typically expressed as 1 or 100%. Driven by a lot of potential applications in many domains, this paper presents various supervised algorithms for learning compositional data from other data sources, leading to a novel multi-label learning setting that bears strong similarities with multivariate regression, multi-label classiﬁcation and multi-class classiﬁcation. Building further upon our previous work on this topic, we compare in this paper several ensemble meth-ods that take into account speciﬁc properties about compositional data. We analyze three diﬀerent types of kernel base learners for bivariate compositions, respectively based on maximum likelihood estimation, least-squares minimization and a label transformation. We also investigate two approaches for aggregating the bivariate predictions of these base learners into multivariate compositions, respectively based on a pairwise and a tree-based decomposition technique. The comparison of the algorithms is supported by empirical results on synthetic data and a real-world application in bioinformatics.
Efficient and accurate representation of asynchronous network structure changing phenomena in digital real time simulators

Due to synchronization requirements related to the interfacing with external systems, digital real time simulators of electromagnetic transients for equipment testing employ a constant integration time step width for solving the network equations. Therefore, the network solution is only calculated at discrete and equidistantly spaced time instants while in reality the time domain is continuous. Changes in network structure that occur between the discrete solution points are generally not simulated exactly. This can lead to switching control mistakes and numerical problems. In this paper the novel clock synchronized structure changing concept, which allows the accurate and efficient simulation of structural changes at arbitrary time instants, is presented.
Remote glucose monitoring in cAMP setting reduces the risk of prolonged nocturnal hypoglycemia.

OBJECTIVE This study tested the feasibility and effectiveness of remote continuous glucose monitoring (CGM) in a diabetes camp setting. SUBJECTS AND METHODS Twenty campers (7-21 years old) with type 1 diabetes were enrolled at each of three camp sessions lasting 5-6 days. On alternating nights, 10 campers were randomized to usual wear of a Dexcom (San Diego, CA) G4™ PLATINUM CGM system, and 10 were randomized to remote monitoring with the Dexcom G4 PLATINUM communicating with the Diabetes Assistant, a cell phone platform, to allow wireless transmission of CGM values. Up to 15 individual graphs and sensor values could be displayed on a single remote monitor or portable tablet. An alarm was triggered for values <70 mg/dL, and treatment was given for meter-confirmed hypoglycemia. The primary end point was to decrease the duration of hypoglycemic episodes <50 mg/dL. RESULTS There were 320 nights of CGM data and 197 hypoglycemic events. Of the remote monitoring alarms, 79% were true (meter reading of <70 mg/dL). With remote monitoring, 100% of alarms were responded to, whereas without remote monitoring only 54% of alarms were responded to. The median duration of hypoglycemic events <70 mg/dL was 35 min without remote monitoring and 30 min with remote monitoring (P=0.078). Remote monitoring significantly decreased prolonged hypoglycemic events, eliminating all events <50 mg/dL lasting longer than 30 min as well as all events <70 mg/dL lasting more than 2 h. CONCLUSIONS Remote monitoring is feasible at diabetes camps and effective in reducing the risk of prolonged nocturnal hypoglycemia. This technology will facilitate forthcoming studies to evaluate the efficacy of automated closed-loop systems in the camp setting.
Study of Present Probability of 26 English Letters in Chinese Characters Spelling Yard

针对当前汉字输入法以全拼音输入法为主,而目前键盘布局没有考虑到全拼音码中26个英文字母出现的概率的现实,利用Visual FoxPro 6. 0作基本工具,针对多方面的汉字内容进行统计,得出了汉字全拼音码中26个英文字母出现的概率分布,为全拼码输入法26个英文字母的键盘分布提供了依据.
VLSI implementation of a neural network memory with several hundreds of neurons

We designed an Electronic Neural Network (ENN) memory with 256 neurons on a single chip using a combination of analog and digital VLSI technology plus a custom microfabrication process. Amplifiers with inverting and noninverting outputs are used for the neurons to make inhibitory and excitatory connections. The connections between the individual neurons are provided by amorphous‐silicon resistors which are placed on the CMOS chip in the last fabrication step. This technique allows a very dense packing of the neurons. Electron‐beam direct‐writing is used to pattern the resistors making it easy to change the information stored in the network from one chip to the next.
Mathematical Model for the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem.

The present paper proposes a multi–level lot sizing and scheduling problem with parallel machines, capacity constraints and sequencedependent setup costs and times. This problem was motivated by a real situation found in some industrial settings, mainly soft drink companies. In this kind of industrial process, the production involves two interdependent levels with decisions about raw material storage and soft drink bottling. The various raw materials are stored in tanks, from which they flow to bottling production lines. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and also in the bottling lines, where setup costs and times depend on the previous items stored and bottled. We call this problem a Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem (SITLSP). A mixed-integer linear model is proposed with various combined constraints that are not usually dealt with in the literature. This complex model was solved by the GAMS/CPLEX software. The lack of similar
The Computer-Extended Ensemble

Until recently, there have been two basic models of how electronics interact with a performer in a performance situation, and these have been derived from tape music and keyboard performance. Both impose rigid constraints on the dynamics of the ensemble situation. Recent developments have shown these models to be end points of a continuum, and the region between is rich and largely unexplored. We examine one sojourn into this realm: Wildlife, which is a work by the authors written for Zeta violin, Radio Drum, and two computers. It is available on CD in the CDCM Computer Music Series (volume 15 from Centaur Records).
PAPEL INMUNOMODULADOR DE LAS DIETAS LIPÍDICAS EN UN MODELO MURINO INMUNOSUPRIMIDO E INFECTADO CON LISTERIA MONOCYTOGENES

Introduction: Dietary fatty acids immunomodulatory capacity in immunosuppression conditions may differ according to the type of fatty acid present in the diet. Objective: To analyze the effect of different types of dietary lipids on the immune resistance of immunosuppressed and immunocompetent animals, against experimental infection with a virulent strain of Listeria monocytogenes. Methods: Balb/c mice were divided into four experimental groups, according to their immunosuppressive treatment: control (PBS), cyclophosphamide (CPA), GK 1.5 and RB6-8C5. Each group was subdivided into four groups according to the lipid diet used which: control, with corn oil 5% (BG); olive oil 20% (AO); fish oil 20% (AP) and sunflower oil 20% (AG). The animals were fed for a month before treatment and subsequently infected with L. monocytogenes. Results: We show increases in the number of viable bacteria in spleen and liver, and low survival rates in all groups of immunosuppressed mice and also in the PBS group and fed with AP. Furthermore, increases in the lymphocyte proliferation were observed, in the spleen of mice fed with AO and treated with CPA. Discussion: The AP diet produces a significant decrease the host resistance in situations of immunosuppression. On the contrary, the AO and AG diets show major efficiency in the elimination of L. monocytogenes and major immunological advantages in immunosuppressed mice. Treatment with RB6-8C5, produces a reduction in the survival of the mice in all groups studied, which leads us to establish that granulocytes play a key role in the control of infection.
Switched-source-impedance CMOS circuit for low standby subthreshold current giga-scale LSI's

The reduction of exponentially increasing standby subthreshold current due to threshold-voltage (V/sub T/) scaling is one of the most important design issues for giga-scale LSIs operating at room temperature. This paper proposes a switched-source-impedance CMOS circuit featuring the subthreshold current reduction of LSIs in standby mode by 34 decades with minimum speed penalty in active mode. The circuit also features V/sub T/ variation immunity due to the negative feedback effect through the source impedance. This scheme permits battery backup even for giga-scale LSIs.
UPC: Distributed Shared-Memory Programming

Preface. 1. Introductory Tutorial. 1.1 Getting Started. 1.2 Private and Shared Data. 1.3 Shared Arrays and Affinity of Shared Data. 1.4 Synchronization and Memory Consistency. 1.5 Work Sharing. 1.6 UPC Pointers. 1.7 Summary. Exercises. 2. Programming View and UPC Data Types. 2.1 Programming Models. 2.2 UPC Programming Model. 2.3 Shared and Private Variables. 2.4 Shared and Private Arrays. 2.5 Blocked Shared Arrays. 2.6 Compiling Environments and Shared Arrays. 2.7 Summary. Exercises. 3. Pointers and Arrays. 3.1 UPC Pointers. 3.2 Pointer Arithmetic. 3.3 Pointer Casting and Usage Practices. 3.4 Pointer Information and Manipulation Functions. 3.5 More Pointer Examples. 3.6 Summary. Exercises. 4. Work Sharing and Domain Decomposition. 4.1 Basic Work Distribution. 4.2 Parallel Iterations. 4.3 Multidimensional Data. 4.4 Distributing Trees. 4.5 Summary. Exercises. 5. Dynamic Shared Memory Allocation. 5.1 Allocating a Global Shared Memory Space Collectively. 5.2 Allocating Multiple Global Spaces. 5.3 Allocating Local Shared Spaces. 5.4 Freeing Allocated Spaces. 5.5 Summary. Exercises. 6. Synchronization and Memory Consistency. 6.1 Barriers. 6.2 Split-Phase Barriers. 6.3 Locks. 6.4 Memory Consistency. 6.5 Summary. Exercises. 7. Performance Tuning and Optimization. 7.1 Parallel System Architectures. 7.2 Performance Issues in Parallel Programming. 7.3 Role of Compilers and Run-Time Systems. 7.4 UPC Hand Optimization. 7.5 Case Studies. 7.6 Summary. Exercises. 8. UPC Libraries. 8.1 UPC Collective Library. 8.2 UPC-IO Library. 8.3 Summary. References. Appendix A: UPC Language Specifications, v1.1. 1. Appendix B: UPC Collective Operations Specifications, v1.0. Appendix C: UPC-IO Specifications, v1.0. Appendix D: How to Compile and Run UPC Programs. Appendix E: Quick UPC Reference. Index.