Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of H∞ robust damping controllers of FACTs devices with considering time-delay of wide-area signals

This paper proposed the design of wide-area robust damping (WARD) controller for multiple Flexible AC Transmission Systems (FACTS) devices to enhance the stability of power system with considering time delay of wide-area signals. Firstly, as power systems interconnect more and more to exchange large amounts, wide-area measurement system (WAMS) is widely applied to monitor and control the interconnected power systems, which can enable the use of measured signals from remote locations for centralized control purpose. In this trend, the impact of time delays introduced by remote signal transmission and processing in WAMS has not been ignored. So this paper describes the wide-area multiple FACTS robust damping controller design problem of power system as time-delay feedback control problem. Then based on the time-delay power system model, wide-area multiple FACTS robust damping controller is design free-weighting matrices method and pole placement method in the linear matrix inequality (LMI). Finally, the case study on 2 areas 4 machines system will show the robustness and effectiveness of this proposed controller.
DyLDO: Towards a Dynamic Linked Data Observatory

We describe work-in-progress on the design and methodology of the Dynamic Linked Data Observatory : a framework to monitor Linked Data over an extended period of time. The core goal of our work is to collect frequent, continuous snapshots of a subset of the Web of Data that is interesting for further study and experimentation, with an aim to capture raw data about the dynamics of Linked Data. The resulting corpora will be made openly and continuously available to the Linked Data research community. Herein, we (1) motivate the importance of such a corpus; (2) outline some of the use-cases and requirements for the resulting snapshots; (3) discuss different “views” of the Web of Data that affect how we define a sample to monitor; (4) detail how we select the scope of the monitoring experiment through sampling, (5) discuss the final design of the monitoring framework that will gather regular snapshots of (subsets of) the Web of Data over the coming months and years.
Load-based covert channels between Xen virtual machines

Multiple virtual machines on a single virtual machine monitor are isolated from each other. A malicious user on one virtual machine usually cannot relay secret data to other virtual machines without using explicit communication media such as shared files or a network. However, this isolation is threatened by communication in which CPU load is used as a covert channel. Unfortunately, this threat has not been fully understood or evaluated. In this study, we quantitatively evaluate the threat of CPU-based covert channels between virtual machines on the Xen hypervisor. We have developed CCCV, a system that creates a covert channel and communicates data secretly using CPU loads. CCCV consists of two user processes, a sender and a receiver. The sender runs on one virtual machine, and the receiver runs on another virtual machine on the same hypervisor. We measured the bandwidth and communication accuracy of the covert channel. CCCV communicated 64-bit data with a 100% success rate in an ideal environment, and with a success rate of over 90% in an environment where Web servers are processing requests on other virtual machines.
Development of a Simulation Model to Investigate Tool Wear in Ti-6Al-4V Alloy Machining

Titanium alloys like Ti‑6Al‑4V have a low density, a very high strength and are highly resistant to corrosion. However, the positive qualities in combination with the low heat conductivity have disadvantageous effects on mechanical machining and on cutting in particular. Ti‑6Al‑4V forms segmented chips for the whole range of cutting velocities which influences tool wear. Thus, optimization of the manufacturing process is difficult. To obtain this goal the chip segmentation process and the tool wear are studied numerically in this article. Therefore, a FEM model was developed which calculates the wear rates depending on state variables from the cutting simulation, using an empirical tool wear model. The segmentation leads to mechanical and thermal load variations, which are taken into consideration during the tool wear simulations. In order to evaluate the simulation results, they are compared with experimentally obtained results for different process parameters.
Rapid changes in the distribution of GAP-43 correlate with the expression of neuronal polarity during normal development and under experimental conditions

Hippocampal neurons growing in culture initially extend several, short minor processes that have the potential to become either axons or dendrites. The first expression of polarity occurs when one of these minor processes begins to elongate rapidly, becoming the axon. Before axonal outgrowth, the growth-associated protein GAP-43 is distributed equally among the growth cones of the minor processes; it is preferentially concentrated in the axonal growth cone once polarity has been established (Goslin, K., D. Schreyer, J. Skene, and G. Banker. 1990. J. Neurosci. 10:588-602). To determine when the selective segregation of GAP-43 begins, we followed individual cells by video microscopy, fixed them as soon as the axon could be distinguished, and localized GAP-43 by immunofluorescence microscopy. Individual minor processes acquired axonal growth characteristics within a period of 30- 60 min, and GAP-43 became selectively concentrated to the growth cones of these processes with an equally rapid time course. We also examined changes in the distribution of GAP-43 after transection of the axon. After an axonal transection that is distant from the soma, neuronal polarity is maintained, and the original axon begins to regrow almost immediately. In such cases, GAP-43 became selectively concentrated in the new axonal growth cone within 12-30 min. In contrast, when the axon is transected close to the soma, polarity is lost; the original axon rarely regrows, and there is a significant delay before a new axon emerges. Under these circumstances, GAP-43 accumulated in the new growth cone much more slowly, suggesting that its ongoing selective routing to the axon had been disrupted by the transection. These results demonstrate that the selective segregation of GAP-43 to the growth cone of a single process is closely correlated with the acquisition of axonal growth characteristics and, hence, with the expression of polarity.
High refractive index nanoparticle-loaded encapsulants for light-emitting diodes

TiO2 nanoparticle-loaded epoxy for light-emitting diode (LED) encapsulation is demonstrated to have a refractive index of n = 1.68, higher than that of pure epoxy (n = 1.53). The dispersion of surfactant-coated TiO2 nanoparticles into epoxy is shown to reduce the number and size of TiO2 agglomerates compared to uncoated TiO2 nanoparticle-loaded epoxy. The scattering of nanoparticle-loaded media is highly dependent on nanoparticle size and loading factor. A multilayer graded refractive index structure for LED encapsulants with layer thicknesses less than the calculated mean optical scattering length is therefore proposed. The graded-index structure shows increasing optical transmittance as the number of layers increases.
Screening Examination of Premature Infants for Retinopathy of Prematurity

This statement revises a previous statement on screening of preterm infants for retinopathy of prematurity (ROP) that was published in 2006. ROP is a pathologic process that occurs only in immature retinal tissue and can progress to a tractional retinal detachment, which can result in functional or complete blindness. Use of peripheral retinal ablative therapy by using laser photocoagulation for nearly 2 decades has resulted in a high probability of markedly decreasing the incidence of this poor visual outcome, but the sequential nature of ROP creates a requirement that at-risk preterm infants be examined at proper times and intervals to detect the changes of ROP before they become permanently destructive. This statement presents the attributes on which an effective program for detecting and treating ROP could be based, including the timing of initial examination and subsequent reexamination intervals.
Translating a Reinforcement Learning Task into a Computational Psychiatry Assay: Challenges and Strategies

Computational psychiatry applies advances from computational neuroscience to psychiatric disorders. A core aim is to develop tasks and modeling approaches that can advance clinical science. Special interest has centered on reinforcement learning (RL) tasks and models. However, laboratory tasks in general often have psychometric weaknesses and RL tasks pose special challenges. These challenges must be addressed if computational psychiatry is to capitalize on its promise of developing sensitive, replicable assays of cognitive function. Few resources identify these challenges and discuss strategies to mitigate them. Here, we first overview general psychometric challenges associated with laboratory tasks, as these may be unfamiliar to cognitive scientists. Next, we illustrate how these challenges interact with issues specific to RL tasks, in the context of presenting a case example of preparing an RL task for computational psychiatry. Throughout, we highlight how considering measurement issues prior to a clinical science study can inform study design.
Load-Balancing in Distributed Selective Search

Simulation and analysis have shown that selective search can reduce the cost of large-scale distributed information retrieval. By partitioning the collection into small topical shards, and then using a resource ranking algorithm to choose a subset of shards to search for each query, fewer postings are evaluated. Here we extend the study of selective search using a fine-grained simulation investigating: selective search efficiency in a parallel query processing environment; the difference in efficiency when term-based and sample-based resource selection algorithms are used; and the effect of two policies for assigning index shards to machines. Results obtained for two large datasets and four large query logs confirm that selective search is significantly more efficient than conventional distributed search. In particular, we show that selective search is capable of both higher throughput and lower latency in a parallel environment than is exhaustive search.
Maintaining Location Privacy and Anonymity for Vehicle’s Drivers in VANET

— Vehicular Ad-hoc Network (VANET) is an emerging technology that aims at providing both safety and comfort for drivers. One of the most important evolving VANET applications is Location-Based Services (LBS). These applications require providing continuous user location updates to untrusted Location-Based Service Providers (SPs), in order to provide real-time services. However, this leads to tracking and identification of users, and thus breaching privacy of vehicle drivers. In this paper, we propose a solution that maintains location privacy of a user and anonymity when using real-time applications, while taking into consideration constraints posed by VANET. Our scheme uses group navigation combined with the use of mobility prediction and prospective path confusion, in order to mitigate tracking of vehicles and provide real-time anonymization for drivers. Besides that, we propose an “n-1 key forwarding mechanism” that is used for secure and private renewal of vehicle's key pairs. In addition, we provide a “Blind LBS Provider” in our approach that has zero-information about a vehicle and blindly provides a service to a vehicle. In our solution, we also provide a variety of techniques to enhance security and privacy of vehicle’s driver that include: timestamps, Reqmask, message signing and encryption. Moreover, our scheme offers additional benefits to vehicles, and provides a variety of security services while avoids well-known attacks in VANET. Our approach provides protection against both internal and external adversaries. Finally in this paper, we analytically evaluated our work using different location privacy metrics and simulated our scheme. Results showed that our solution is applicable and capable of providing real-time location privacy for vehicle drivers without loss of availability or accuracy of LBS applications. Thus, breaking the zero-sum game between privacy and Quality-of-Service (QoS)
Lorentz-violating massive gravity in curved space

In models of modified gravity, extra degrees of freedom usually appear. They must be removed from the spectrum because they may indicate the presence of instabilities and because otherwise the model might not agree with observation. In the present letter, we will discuss a model that modifies General Relativity through the addition of a Lorentz-violating potential-like term for the metric. No additional propagating modes and no classical instabilities are present. The model departs from GR only in the extreme infrared region, and the cosmological evolution contains a bounce when the size of the Universe is of the same order of the added deformation.
An object storage model for the truffle language implementation framework

Truffle is a Java-based framework for developing high-performance language runtimes. Language implementers aiming at developing new runtimes have to design all the runtime mechanisms for managing dynamically typed objects from scratch. This not only leads to potential code duplication, but also impacts the actual time needed to develop a fully-fledged runtime. In this paper we address this issue by introducing a common object storage model (OSM) for Truffle that can be used by language implementers to develop new runtimes. The OSM is generic, language-agnostic, and portable, as it can be used to implement a great variety of dynamic languages. It is extensible, featuring built-in support for custom extension mechanisms. It is also high-performance, as it is designed to benefit from the optimizing compiler in the Truffle framework. Our initial evaluation indicates that the Truffle OSM can be used to implement high-performance language runtimes, with no performance overhead when compared to language-specific solutions.
Probable Bioweapon: Influenza Type A Virus - A Short Case Report.

Influenza type A virus (Influenza virus A), an old foe of mankind, is presently the most significant pathogen causing both pandemics and epizootics, worldwide. The proliferative husbandry of poultry and pigs, primarily, constitutes a key factor in ongoing generation of pandemic and pre-pandemic strains, which is fueled by remarkable wild aquatic bird permissiveness of the virus. Those attributes are here thoroughly inquired into, so as to profile and rate threat and usability. Also, various human interventions and misuses, including human experimental infections, undesirable vaccinations, as well as unauthorized and unskillful operations, led to bad corollaries and may rather be reassessed and modified or disallowed. Diversified interfaces between influenza and human manners are thereby brought out and elucidated, along with their lessons.
Robust data sharing with key-value stores

A key-value store (KVS) offers functions for storing and retrieving values associated with unique keys. KVSs have become the most popular way to access Internet-scale “cloud” storage systems. We present an efficient wait-free algorithm that emulates multi-reader multi-writer storage from a set of potentially faulty KVS replicas in an asynchronous environment. Our implementation serves an unbounded number of clients that use the storage concurrently. It tolerates crashes of a minority of the KVSs and crashes of any number of clients. Our algorithm minimizes the space overhead at the KVSs and comes in two variants providing regular and atomic semantics, respectively. Compared with prior solutions, it is inherently scalable and allows clients to write concurrently. Because of the limited interface of a KVS, textbook-style solutions for reliable storage either do not work or incur a prohibitively large storage overhead. Our algorithm maintains two copies of the stored value per KVS in the common case, and we show that this is indeed necessary. If there are concurrent write operations, the maximum space complexity of the algorithm grows in proportion to the point contention. A series of simulations explore the behavior of the algorithm, and benchmarks obtained with KVS cloud-storage providers demonstrate its practicality.
Targeting Specific Distributions of Trajectories in MDPs

We define TTD-MDPs, a novel class of Markov decision processes where the traditional goal of an agent is changed from finding an optimal trajectory through a state space to realizing a specified distribution of trajectories through the space. After motivating this formulation, we show how to convert a traditional MDP into a TTD-MDP. We derive an algorithm for finding non-deterministic policies by constructing a trajectory tree that allows us to compute locally-consistent policies. We specify the necessary conditions for solving the problem exactly and present a heuristic algorithm for constructing policies when an exact answer is impossible or impractical. We present empirical results for our algorithm in two domains: a synthetic grid world and stories in an interactive drama or game.
Enhancing annotation visibility for software inspection

Annotation of software artifacts is common in software development, and vital for software inspection. People viewing annotated artifacts encounter delocalization: they must understand various parts of an artifact (and their annotations) to understand the part they are viewing. We taxonomize delocalization within software systems into lateral delocalization (different items of the artifact within the same development phase), longitudinal delocalization (related items in different phases), and historical delocalization (successive versions of the same item). We report on a pilot study of code inspection with AnnoSpec, an inspection tool supporting visibility of laterally-delocalized annotations. Our results suggest that addressing delocalization may help people perform inspections more effectively.
Coverage-Based Clustering and Scheduling Approach for Test Case Prioritization

SUMMARY Regression testing is essential for assuring the quality of a software product. Because rerunning all test cases in regression testing may be impractical under limited resources, test case prioritization is a feasible solution to optimize regression testing by reordering test cases for the current testing version. In this paper, we propose a novel test case prioritization approach that combines the clustering algorithm and the scheduling algorithm for improving the e ﬀ ectiveness of regression testing. By using the clustering algorithm, test cases with same or similar properties are merged into a cluster, and the scheduling algorithm helps allocate an execution priority for each test case by incorporating fault detection rates with the waiting time of test cases in candidate set. We have conducted several experiments on 12 C programs to validate the e ﬀ ectiveness of our proposed approach. Experimental results show that our approach is more e ﬀ ective than some well studied test case prioritization techniques in terms of average percentage of fault detected (APFD) values.
Patent Application of Vitit Kantabutra for TITLE : INTENTIONALLY-LINKED ENTITIES : A GENERAL-PURPOSE DATABASE SYSTEM CROSS-REFERENCE TO RELATED APPLICATIONS

In accordance with one embodiment the subject of the patent is a method for storing a database comprising entity objects or data structures representing the data entities, and relationship objects or data structures representing the relationships amongst the entities. Each relationship object or data structure possesses links to the entity objects or data structures that play the various roles in the relationship. Where there is a link from a relationship to an entity, there is also a link from the entity to the relationship, facilitating queries and updates to the database system. It is possible and often desirable for an embodiment to permit not merely one, but possibly many (or zero) entities to play each role in a relationship. The database is value-oriented in the sense that the address of an entity is not part of the key, thus permitting value-comparison-based searches.
Heterogeneity of Messenger RNA That Encodes the Rat Insulin Receptor Is Limited to the Domain of Exon 11: Analysis by RNA Heteroduplex Mapping, Amplification of cDNA, and In Vitro Translation

Structural isoforms of the insulin receptor that occur in various tissues have been postulated to be involved in certain actions of insulin in target cells. To determine whether these insulin-receptor subtypes are caused by alterations in the receptor primary structure, we used RNA heteroduplex mapping and amplification of cDNA to detect variation in the coding region of insulin-receptor mRNA from 5 rat tissues. A complete series of overlapping antisense [32P]RNA probes was prepared from plasmids containing segments of a full-length rat insulin-receptor cDNA, and probes were hybridized individually in solution with polyadenylated RNA from rat brain, kidney, liver, skeletal muscle, and spleen. After ribonuclease digestion, probe fragments were analyzed by denaturing gel electrophoresis. Tissue-specific cleavage of the mRNA:RNA probe heteroduplex, attributable to sequence mismatch, was detected only for a single probe covering the distal α-subunit, as expected for the known alternative splicing of rat insulin-receptor mRNA in this region. No evidence for additional heterogeneity of the receptor mRNA coding region was observed in the 5 tissues studied either by RNA heteroduplex mapping or, in some areas, by regional amplification of insulin-receptor cDNA. Cell-free translation of size-fractionated polyadenylated RNA was used to further demonstrate that each of the major insulin-receptor mRNA size classes in rat liver contained both forms of the alternatively spliced mRNA transcripts and produced two insulin-proreceptor polypeptides. These results suggest that heterogeneity of the insulin-receptor mRNA coding region affecting the receptor primary structure is limited to the distal α-subunit near the subunit cleavage site. Many of the reported structural isoforms of the mature insulin receptor are therefore likely to occur by specific posttranslational processing events that may influence the transmission of the insulin signal in various tissues.
Energy Loss Allocation in Radial Distribution Systems: A Comparison of Practical Algorithms

This paper presents allocation of energy losses to consumers connected to radial distribution networks in a deregulated environment. A detailed comparison of the proposed ldquoExact Methodrdquo with three alternative algorithms, namely, pro rata, quadratic allocation and proportional allocation are presented. Pro rata procedure is based on the load demand of each consumer, quadratic and proportional allocations are based on identifying the real and reactive parts of current in each branch and the losses are allocated to each consumer, and the proposed ldquoExact Methodrdquo is based on the actual contribution of real power loss by each consumer. A case study based on a 30-node distribution system is provided.