Miracle-dz/UniFAR-FTUs huggingface dataset:
CDOL: a declarative platform for developing OODB applications

The authors present a rule-based database language known as CDOL (comprehensive declarative object language). CDOL provides sublanguages for the expression of derived data, constraints, updates, and integrity rules. The basic rule language provides an expressive approach to extending the stored database with virtual attributes and classes. The constraint sublanguage of CDOL allows explicit declarative specification of integrity constraints. The update sublanguage of CDOL enables ad-hoc declarative update requests, where the end-user is relieved from database consistency considerations. Integrity rules in CDOL are designed as active, user-transparent agents that supplement the declarative updates to complete update methods that preserve database consistency. An important contribution of CDOL is the active, integrity rule framework it establishes for integrating derived data, constraints and updates in a coherent and easy to use application-development platform for OODBs. <<ETX>>
Collaborating Through Shared Displays and Interacting Devices

Information devices are getting both smaller and larger as we move beyond the traditional desktop. On the one hand, the lighter, smaller and more portable smart phones and tablets are replacing devices such as desktop computers and laptops (see Figure 1). On the other hand, desktop displays have increased in size or have multiplied on a single desktop, and shared displays have grown to cover entire walls or to form rooms that users can enter. This trend has continued for more than a decade but has accelerated with the introduction of the iPhone, iPad, dense flash memory, and inexpensive large screen monitors.
Ceph: reliable, scalable, and high-performance distributed storage

As the size and performance requirements of storage systems have increased, file system designers have looked to new architectures to facilitate system scalability. The emerging object-based storage paradigm diverges from server-based (e. g. NFS) and SAN-based storage systems by coupling processors and memory with disk drives, allowing systems to delegate low-level file system operations (e. g. allocation and scheduling) to object storage devices (OSDs) and decouple I/O (read/write) from metadata (file open/close) operations. Even recent object-based systems inherit a variety of decades-old architectural choices going back to early UNIX file systems, however, limiting their ability to effectively scale. This dissertation shows that device intelligence can be leveraged to provide reliable, scalable, and high-performance file service in a dynamic cluster environment. It presents a distributed metadata management architecture that provides excellent performance and scalability by adapting to highly variable system workloads while tolerating arbitrary node crashes. A flexible and robust data distribution function places data objects in a large, dynamic cluster of storage devices, simplifying metadata and facilitating system scalability, while providing a uniform distribution of data, protection from correlated device failure, and efficient data migration. This placement algorithm facilitates the creation of a reliable and scalable object storage service that distributes the complexity of consistent data replication, failure detection, and recovery across a heterogeneous cluster of semi-autonomous devices. These architectural components, which have been implemented in the Ceph distributed file system, are evaluated under a variety of workloads that show superior I/O performance, scalable metadata management, and failure recovery.
The reaction of different Sorbus L. species to low temperatures during thaw in the Orel region

Five Sorbus L. species of different ecological and geographical origin growing in the VNIISPK arboretum were studied. The Institute is located 368 km southwest of Moscow, on the Central Russian upland in the European part of Russia. The studies were carried out in 2014–2016. The reaction of different Sorbus L. species to a three-day thaw +2°C with a subsequent decrease in temperature to –25°C in February and –30°C in March was studied in order to identify adapted species to the climatic conditions of the Orel region for use in ornamental horticulture. As a result of the experiment, we recommend Sorbus aria (L.) Crantz, Sorbus aucuparia L. and Sorbus alnifolia (Siebold. et Zucc.) K. Koch. as adapted species for the Orel region to create sustainable landscape compositions.
WAKEFIELD EXCITATION BY A LASER PULSE IN A DIELECTRIC MEDIUM

The process of Cherenkov electromagnetic field excitation by а laser pulse in the dielectric waveguide is investigated. Nonlinear electric polarization in an isotropic dielectric medium and, accordingly, polarization charges and currents induced by ponderomotive force of the laser pulse are determined. Spatial structure of the excited wakefield in a dielectric waveguide is obtained and investigated. It is shown, that the wakefield consists of polarization potential electric field, caused by the nonlinear polarization of medium, and a set of eigen electromagnetic waves of the dielectric waveguide. PACS: 41.75. Lx, 41.85. Ja, 41.69. Bq
THE ANALYSIS OF CONIFEROUS LOGS TOP DIAMETER MEASUREMENT ACCURACY USING HARVESTER AND 3 D SYSTEMS

High productivity and more value-added production are the main strategies of the Latvian sawmills as sawing the appropriate products from each log has always been actual for each sawmill. The requirements of sawn timber specification have been used for the preparation of the roundwood specification, where top diameters, maximum diameters and length parameters have been determined. These parameters have been studied in a harvesting task where, for each top diameter group, the appropriate length dimensions were identified. Log recovery was organized by adjusting the cuts to each log according to sawn timber specifications. Therefore, almost all larger sawmills in Latvia are presorting the logs by the top diameter values divided in groups, often resulting in rejection or size reduction when the parameters measured by the sawmill’s 3D systems do not agree to the specifications. The goal of this study was to evaluate the effect of a harvester calibration system on the accuracy of coniferous logs top diameter measurements (under bark) by measuring the diameters in short intervals using electronic 3D systems.
Instruction scheduling for instruction level parallel processors

Nearly all personal computer and workstation processors, and virtually all high-performance embedded processor cores, now embody instruction level parallel (ILP) processing in the form of superscalar or very long instruction word (VLIW) architectures. ILP processors put much more of a burden on compilers; without "heroic" compiling techniques, most such processors fall far short of their performance goals. Those techniques are largely found in the high-level optimization phase and in the code generation phase; they are also collectively called instruction scheduling. This paper reviews the state of the art in code generation for ILP parallel processors. Modern ILP code generation methods move code across basic block boundaries. These methods grew out of techniques for generating horizontal microcode, so we introduce the problem by describing its history. Most modem approaches can be categorized by the shape of the scheduling "region. " Some of these regions are loops, and for those techniques known broadly as "Software Pipelining" are used. Software Pipelining techniques are only considered here when there are issues relevant to the region-based techniques presented. The selection of a type of region to use in this process is one of the most controversial questions in code generation; the paper surveys the best known alternatives. The paper then considers two questions: First, given a type of region, how does one pick specific regions of that type in the intermediate code. In conjunction with region selection, we consider region enlargement techniques such as unrolling and branch target expansion. The second question, how does one construct a schedule once regions have been selected, occupies the next section of the paper. Finally, schedule construction using recent, innovative resource modeling based on finite-state automata is then reexamined. The paper includes an extensive bibliography.
RELATIVE INFLUENCE OF NDVI IN THE ORGANIC MATTER CONTENT OF SEMIARID SOILS

Soil organic matter (SOM) is an important indicator of soil quality, being directly influenced by the carbon deposition of the present vegetation. The objective of this study was to evaluate the influence of vegetation density on soil organic matter contents. For this, deformed soil samples were collected in the 0-10 cm layer for each of the three Soil and Vegetation Association (SVA) areas, SVA1, SVA2 e SVA3, in the Aiuaba Experimental Basin (12km2), Ceará, Brazil, and the organic matter content (OMC) was determined from laboratory analysis. The vegetation density was estimated from orbital images obtained by TM-LandSat 8 satellite, from which the Normalized Difference Vegetation Index (NDVI) was calculated using the reflectance values of the bands 4 (red) and 5 (near infrared). The SOM contents were correlated with the NDVI values obtained for each of the pixels in the used image where the samples were collected and the coefficients of determination were obtained. The soil analysis showed higher values and a greater amplitude of the soil organic content in the Hypochromic Luvisol area (SVA2). Results showed a good correlation between a greater presence of vegetation and the presence of organic material in the initial soil layer, presenting a positive correlation when observed SVA1 and SVA2 areas. Despite these good correlation, aspects related to the physiology of the vegetation as well as the inherent features of the present soils should be considered. In conclusion, vegetation indexes obtained by orbital images, such as NDVI, by itself, do not make possible a reliable estimation of the OMC, but can be a good indicator of the levels of organic matter in semi-arid soils when associated to analysis of the vegetation behavior.
A Control Theoretic Approach for Throughput Optimisation in IEEE 802

The MAC layer of the 802.11 standard, based on the CSMA/CA mechanism, specifies a set of parameters to control the aggressiveness of stations when trying to access the channel. However, these parameters are statically set independently of the conditions of the WLAN (e.g. the number of contending stations), leading to poor performance for most scenarios. To overcome this limitation previous work proposes to adapt the value of one of those parameters, namely the CW, based on an estimation of the conditions of the WLAN. However, these approaches suffer from two major drawbacks: i) they require extending the capabilities of standard devices or ii) are based on heuristics. This thesis proposes a control theoretic approach to adapt the CW to the conditions of the WLAN, based on an analytical model of its operation, that is fully compliant with the 802.11e standard. We use a Proportional Integrator controller in order to drive the WLAN to its optimal point of operation and perform a theoretic analysis to determine its configuration. We show by means of an exhaustive performance evaluation that our algorithm maximises the total throughput of the WLAN and substantially outperforms previous standardcompliant proposals.
WIRELEDD RFID FOR HEART RATE MONITORING

Radio Frequency Identification (RFID) is one of the many emerging technologies that are part of many industries. It uses electromagnetic fields attached to any tags to identify and track objects. This technology has seen significant growth seen in its applications in the medical industry, which has its emphasis on patient safety.Wireless heart monitoring is a technology that can save lives and restore peace of mind to those with heart disease and those at-risk. Heart disease is the most prevalent health problem in the United States currently. The RFID technology has not had a major role in cardiac healthcare systems; however, it is an ideal technology for wireless heart monitoring devices. Remote healthcare monitoring allows people to continue to stay at home rather than in expensive healthcare facilities such as hospitals or nursing homes. It thus provides an efficient and cost-effective alternative to on-site clinical monitoring. Such systems equipped with non-invasive and unobtrusive wearable sensors can be viable diagnostic tools to the healthcare personnel for monitoring important physiological signs and activities of the patients in real-time, from a distant facility. Wearable RFID tags can monitor and record real-time information about one's physiological condition and motion activities. Wearable sensor-based health monitoring systems may comprise different types of flexible sensors that integrated into textile fiber, clothes, and elastic bands or directly attached to the human body. The sensors are capable of measuring physiological signs such as electrocardiogram (ECG), electromyogram (EMG), heart rate (HR), body temperature, electro dermal activity (EDA), arterial oxygen saturation (SpO2), blood pressure (BP) and respiration rate (RR). Continuous monitoring of physiological signals could help to detect and diagnose several cardiovascular, neurological and pulmonary diseases at their early onset. In addition, real-time monitoring of an individual’s motion activities could be useful in fall detection, gait pattern and posture analysis, or in sleep assessment.
PHOENIX CENTER POLICY PAPER SERIES Phoenix Center Policy Paper Number 27: Tort Liability for Software Developers: A Law & Economics Perspective

This POLICY PAPER explores the economic rationale for applying product liability law to computer software. As demonstrated below, a well-designed liability regime must place liability upon all parties who economically control the risks of accidents. Accordingly, this POLICY PAPER finds that strict liability may be appropriate for certain types of “intrinsic” software, but not for other types of software require that the customer be actively involved in the selection, operation and maintenance thereof. We show that for this type of “extrinsic” software, a strict liability rule is unlikely to be economically optimal. Choosing a generic liability regime applicable to all forms of software is illadvised. Instead, a more nuanced approach is required to achieve a desirable outcome.
Asymptotic Behavior of Magnetostrictive Elasticity for Microstructured Materials

Abstract According to the classical theory of Weiss, Landau, and Lifshitz, in a ferromagnetic body there is a spontaneous magnetization field m, such that ∥m∥ = τ0 = const in all points of this material Ω. In any stationary configuration, this ferromagnetic body consists of areas (Weiss domains) in which the magnetization is uniform (i.e. m = const) separated by thin transition layers (Bloch walls). Such stationary configuration corresponds to the minimum point of the magnetostrictive free energy E. We are considering an elastic magnetostrictive body in our paper. The elastic magnetostrictive free energy Eδ depends on a small parameter δ such that δ → 0. As usual, the displacement field is denoted by u. We will show that each sequence of minimizers (ui, mi) contains a subsequence that converges to a couple of fields (u0, m0). By means of a Γ-limit procedure we will show that this couple (u0, m0) is a minimizer of the new functional E0. This new functional E0 describes the magnetic-elastic properties of the body with microstructure.
Table-Based Identification Protocol of Compuatational RFID Tags

Computation RFID (CRFID) expands the limit of traditional RFID by granting computational capability to RFID tags. RFID tags are powered by Radio-Frequency (RF) energy harvesting. However, CRFID tags need extra energy and processing time than traditional RFID tags to sense the environment and generate sensing data. Therefore, Dynamic Framed Slotted ALOHA (DFSA) protocol for traditional RFID is no longer a best solution for CRFID systems. In this paper, we propose a table-based CRFID tag identification protocol considering CRFID operation. An RFID reader sends the message with the frame index. Using the frame index, CRFID tags calculate the energy requirement and processing time information to the reader along with data transmission. The RFID reader records the received information of tags into a table. After table recording is completed, the optimal frame size and proper time interval is provided based on the table. The proposed CRFID tag identification protocol is shown to enhance the identification rate and the delay via simulations.
Shared Memory Paraellization of Data Mining Algorithms: Techniques, Programming Interface, and Performance.

With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In This work, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of popular data mining algorithms. In addition, we propose a reduction-object-based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the techniques we have developed starting from a common specification of the algorithm. We have carried out a detailed evaluation of the parallelization techniques and the programming interface. We have experimented with apriori and fp-tree-based association mining, k-means clustering, k-nearest neighbor classifier, and decision tree construction. The main results from our experiments are as follows: 1) Among full replication, optimized full locking, and cache-sensitive locking, there is no clear winner. Each of these three techniques can outperform others depending upon machine and dataset parameters. These three techniques perform significantly better than the other two techniques. 2) Good parallel efficiency is achieved for each of the four algorithms we experimented with, using our techniques and runtime system. 3) The overhead of the interface is within 10 percent in almost all cases. 4) In the case of decision tree construction, combining different techniques turned out to be crucial for achieving high performance.
Covariate measurement error in generalized linear models for longitudinal data : a latent Markov approach

One common approach to handle covariate measurement error in Generalized Linear Models (GLM) is classical error modeling. In the past 20 years, classical error modeling has been brought to (Non-Parametric) Maximum Likelihood (NPML) estimation, by means of finite mixture modeling: the supposedly continuous true score is modeled as a discrete (multinomial) static latent variable, and is handled as a part of the model. Nonetheless, the true score is not allowed to vary over time: if the true score has own underlying dynamics, these are either unaccounted for or mistaken for measurement error, or possibly both. The aim of the present paper is to formulate a joint model for the outcome variable, the covariate observed with error (measurement model), and the true score model that accounts for the underlying dynamics in the true score. The true score and its dynamics are modeled non-parametrically as a first-order latent (hidden) Markov chain. Estimation is done extending the NPML approach, in a full maximum likelihood environment with a well-know modification of the EM algorithm (forward-backward algorithm). From an applied researcher perspective, our methodology can safely handle both the case where the latent underlying characteristic is stable over time, as well as providing a suitable framework even when changes across measurement occasions are substantial. Within a GLM framework, it is demonstrated, by means of extensive simulation studies, that this is crucial to get correct estimates of the regression coefficients, as well as good coverages. In the real-data application, the effect of heart rate on the occurrence of cardiovascular diseases in a sample of Chinese elderly patients is measured. Modeling the true (unobserved) heart rate and its dynamics which, in elderly patients, are likely to be non negligible will be showed to allow a correct assessment of risk factors of cardiovascular diseases occurrence. Key-Words: covariate measurement error, errors–in–variables, longitudinal data, generalized linear models, latent Markov models. ∗roberto.dimari@unict.it
ExpCog : Experiments in Commonsense Cognitive Robotics

ExpCog is a high-level cognitive robotics framework aimed at integrating logic-based and cognitively-driven agent-control approaches, qualitative models of space, and the ability to apply these in the form of planning, explanation and simulation in a wide-range of robot-control platforms and simulation environments. In addition to its primary experimental function, the framework also has a utility toward didactic purposes, e.g., as a teaching and experimental aid in courses on Artificial Intelligence, Knowledge Representation and Reasoning, and Robotics. We demonstrate the ExpCog framework in the backdrop of an online incremental planning and postdiction driven autonomous wheelchair robot control task. We propose that ExpCog, if pursued as a longterm initiative in an open-source format, promises to consolidate KR methods for robotics under a unifying platform, thereby offering researchers, students, and enthusiasts alike direct access to commonsense cognitive robotics.
Parametric and Non-Parametric Nodule Models : Design and Evaluation

Lung nodule modeling quality defines the success of lung nodule detection. This paper presents a novel method for generating lung nodules using variational level sets to obtain the shape properties of real nodules to form an average model template per nodule type. The texture information used for filling the nodules is based on a devised approach that uses the probability density of the radial distance of each nodule to obtain the maximum and minimum Hounsfield density (HU). There are two main categories that lung nodule models fall within; parametric and non-parametric. The performance of the new nodule templates will be evaluated during the detection step and compared with the use of parametric templates and another non-parametric Active Appearance model to explain the advantages and/or disadvantages of using parametric vs. non-parametric models as well as which variation of nonparametric template design, i.e., shape based or shape-texture based yields better results in the overall detection process.