Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Construction of Trusted Resource Pool in Clouds

IaaS cloud converts physical resources into resource pools. The pool oriented resource management model requires transparency of the underlying physical resources, as well as the on-demand consumption of IT services and the trust verification of the resources from cloud users. A viable way is by creating trusted clusters that consist of trusted physical machines, with strict membership management of these trusted clusters, confining IT services to be hosted within trusted clusters. This paper proposes a trusted cluster scheme which is based on a dynamic group signature scheme. The scheme fits into the pool oriented trust management for cloud computing.
Cascade Artificial Neural Network Models for Predicting Shelf Life of Processed Cheese

The purpose of this study is to develop artificial neural network (ANN) models for predicting shelf life of processed cheese stored at 7-8oC. Body & texture, aroma & flavour, moisture and free fatty acids were taken as input parameters, and sensory score as output parameter for developing the models. The developed Cascade single layer ANN models were compared with each other. Bayesian regularization was used for training ANN models. Network was trained with 100 epochs, and neurons in each hidden layer(s) varied from 3 to 20. Cascade ANN models very well predicted the shelf life of processed cheese.
An impulse-based approach under penetration between bodies for tactile feedback display

In the CG community, many kinds of physical-based (impulse-based) approaches such as Mirtich's and Baraff's have been proposed for showing dynamic animation. However, because they generate and calibrate only an impulsive force, i.e., an area of force distribution, the impulsive forces are not always precisely calibrated. Moreover, since they do not deal with any exact impulse (force distribution), they cannot be applicable for dynamic animation with simultaneous contacts between bodies and for tactile feedback display between them. In order to overcome such drawbacks, we proposed a new approach to generate an arbitrary impulse (force distribution) artificially based on practical time, and tried for dynamic animation with single contact between plastic puck and wall in an air hockey game. In this paper, we extend our proposed approach for a human to strike a puck by a mallet and to feel their impulse by a haptic device such as PHANToM. Moreover, we investigate impulse precision by changing penetration depth between puck and mallet.
Virtualization Security: Virtual Machine Monitoring and Introspection

Virtualization sprawl has rapidly grown over the last few years. Servers and desktops are being constantly virtualized in the name of, amongst others, resource consolidation and cost reduction. Traditional monitoring technologies can offer neither adequate protection nor efficient use of a system’s resources; intercommunication between virtual machines are not trivial to inspect, as well as the internal state of each virtual machine. Tampering with virtual machines could easily go unnoticed and rootkits, viruses and similar threats could infect a virtual machine and act covertly due to a lack of visibility. New solutions to thwart or mitigate those risks have made their way into the industry. Virtual machine introspection enables external monitoring of a virtual machine’s internals using a privileged security-oriented virtual machine. The aim of this thesis is to discuss the virtualization-related security issues and examine traditional and modern monitoring techniques, their limitations and the level of protection and assurance they offer. Finally we propose and discuss a defensive concept of a mechanism that aims to distract and confuse a potential adversary by presenting him misleading information about the system.
International Accessibility of Open Source Software

Though open source sofware has achieved tremendous success in recent years, no existing literature examines issues of accessibility for international users. In this paper we present an international accessibility model which involves adoption of open source software and participation in the development community of software by international users. Based on that model, we first classify open source software roughly into three categories based on its target user groups, i.e., system administrators, developers and end-users, and discuss a list of desired accessibility properties from the viewpoints of international users. Our investigation of some high-profile open source projects shows that technologically difficult problems are solved rather elegantly in some projects while seemingly easy problems such as translation of manuals are ignored or poorly addressed. We explain possible factors that can lead to the differences among these projects and conclude that most existing open source software still lacks desired accessibility properties for international users, and various contributing factors such as cultivation of online user communities, support from commercial companies, educational and propagandistic roles of press, localization of documentation, highly modular design and building of integrated Web environments for global developers and users need to work together to improve the status quo.
Optimal Competition and Allocation of Space in Shopping Centers

This article explains why a profit-maximizing developer may include multiple, competing outlets in a shopping center. While competing outlets presumably dissipate potential profits, thereby lowering aggregate rents that the developer can extract, the presence of shopping externalities causes the developer to be interested not just in individual store profits, but also in the traffic they generate throughout the center. And since competition among identical stores increases traffic, it can create an offsetting advantage that favors multiple outlets. The article provides a theoretical analysis of this problem and illustrates its implications for tenant mix by applying the theory to the problem of filling a vacant store. The paper concludes by explicitly relating the analysis to Brueckner's (1993) model of the optimal allocation of space in shopping centers.
Predicting real growth and inflation with the yield spread

Analysts often use financial variables to help predict real activity and inflation. One of the most popular of these variables is the spread between yields on long-term and short-term government instruments, also known as the yield spread. Researchers have shown the spread is a good predictor of real activity. For instance, in a recent issue of the Economic Review, Bonser-Neal and Morley found that the spread helps predict real activity over the next year, the next two years, and the next three years. > Kozicki examines the predictive power of the yield spread for real growth and inflation in a collection of industrialized countries. She extends the analysis of Bonser-Neal and Morley by examining in greater detail the horizons at which the yield spread helps predict real growth and by investigating whether information on the level of yields contains additional predictive power beyond that summarized by the spread. She also adds to the existing literature by examining a broader collection of countries than has previously been analyzed and a wider array of forecast horizons. In addition, restrictions imposed in earlier studies are relaxed. > For real activity, Kozicki finds that the predictive power of the yield spread largely derives from its usefulness over horizons of a year or so and generally dominates the predictive power associated with the level of yields. For inflation, although the yield spread helps predict inflation at moderate horizons of a few years, the level of yields is a more useful predictor of inflation.
Deriving Production Rules for Incremental View Maintenance S t

It is widely recognized that production rules in database systems can be used to automatically maintain derived data such as views. However, writing a correct set of rules for efficiently maintaining a given view can be a difficult and ad-hoc process. We provide a facility whereby a user delines a view as an SQL select expression, from which the system automatically derives set-oriented production rules that maintain a materialization of that view. The maintenance rules are triggered by operations on the view’s base tables. Generally, the rules perform incremental maintenance: the materialized view is modified according to the sets of changes made to the base tables, which are accessible through logical tables provided by the rule language. However, for some operations substantial recomputation may be required. We give algorithms that, based on key information, perform syntactic analysis on a view definit,ion to determine when efficient maintenance is possible.
Biocompatibility of resin-modified filling materials.

Increasing numbers of resin-based dental restorations have been placed over the past decade. During this same period, the public interest in the local and especially systemic adverse effects caused by dental materials has increased significantly. It has been found that each resin-based material releases several components into the oral environment. In particular, the comonomer, triethyleneglycol di-methacrylate (TEGDMA), and the 'hydrophilic' monomer, 2-hydroxy-ethyl-methacrylate (HEMA), are leached out from various composite resins and 'adhesive' materials (e.g., resin-modified glass-ionomer cements [GICs] and dentin adhesives) in considerable amounts during the first 24 hours after polymerization. Numerous unbound resin components may leach into saliva during the initial phase after polymerization, and later, due to degradation or erosion of the resinous restoration. Those substances may be systemically distributed and could potentially cause adverse systemic effects in patients. In addition, absorption of organic substances from unpolymerized material, through unprotected skin, due to manual contact may pose a special risk for dental personnel. This is borne out by the increasing numbers of dental nurses, technicians, and dentists who present with allergic reactions to one or more resin components, like HEMA, glutaraldehyde, ethyleneglycol di-methacrylate (EGDMA), and dibenzoyl peroxide (DPO). However, it must be emphasized that, except for conventional composite resins, data reported on the release of substances from resin-based materials are scarce. There is very little reliable information with respect to the biological interactions between resin components and various tissues. Those interactions may be either protective, like absorption to dentin, or detrimental, e.g., inflammatory reactions of soft tissues. Microbial effects have also been observed which may contribute indirectly to caries and irritation of the pulp. Therefore, it is critical, both for our patients and for the profession, that the biological effects of resin-based filling materials be clarified in the near future.
Intelligent Placement of Datacenters for Internet Services

Popular Internet services are hosted by multiple geographically distributed data centers. The location of the data centers has a direct impact on the services' response times, capital and operational costs, and (indirect) carbon dioxide emissions. Selecting a location involves many important considerations, including its proximity to population centers, power plants, and network backbones, the source of the electricity in the region, the electricity, land, and water prices at the location, and the average temperatures at the location. As there can be many potential locations and many issues to consider for each of them, the selection process can be extremely involved and time-consuming. In this paper, we focus on the selection process and its automation. Specifically, we propose a framework that formalizes the process as a non-linear cost optimization problem, and approaches for solving the problem. Based on the framework, we characterize areas across the United States as potential locations for data centers, and delve deeper into seven interesting locations. Using the framework and our solution approaches, we illustrate the selection trade offs by quantifying the minimum cost of (1) achieving different response times, availability levels, and consistency times, and (2) restricting services to green energy and chiller-less data centers. Among other interesting results, we demonstrate that the intelligent placement of data centers can save millions of dollars under a variety of conditions. We also demonstrate that the selection process is most efficient and accurate when it uses a novel combination of linear programming and simulated annealing.
Quotients of Incidence Algebras and the Euler Characteristic

In this note, we show that, if A ≅ kQ A /I A is a schurian strongly simply connected algebra given by its normed presentation, and Σ is the unique poset whose Hasse quiver coincides with Q A , then A ≅ kΣ if and only if I A has a generating set consisting of exactly χ(Q A ) elements, where χ(Q A ) is the Euler characteristic of Q A . We also prove that a quotient of an incidence algebra A = kΣ/J is strongly simply connected if and only if A is simply connected and kΣ is strongly simply connected.
Locally Testing Direct Products in the High Error Range

Given a function f : X → Σ, its `-wise direct product is the function F = f ` : X` → Σ` defined by F (x1, . . . , x`) = (f(x1), . , f(x`)). In this paper we study the local testability of the direct product encoding (mapping f 7→ f `). Namely, given an arbitrary function F : X` → Σ`, we wish to determine how close it is to f ` for some f : X → Σ, by making the smallest possible number of random queries into F (namely, two). This question has first been studied by Goldreich and Safra and later the following simple two-query test has been studied by Dinur and Reingold: Choose a random pair x,x′ ∈ X` that have m coordinates in common. Accept iff F (x) and F (x′) agree on the common coordinates. Dinur and Reingold showed that if the test accepts with sufficiently high probability (close to 1) then F is close to f ` for some f . In this work we analyze the case of low acceptance probability of the test. We show that even if the test passes with small probability, ε > 0, already F must have a non-trivial structure and in particular must agree with some f ` on nearly ε of the domain. Moreover, we give a structural characterization of all functions F on which the test passes with probability ε. We find a list of functions f1, . , ft such that essentially the only way T ′ will accept on a pair x,x′, is if both F (x) and F (x′) agree with fi. This is related to approximate local-decoding of this code, as studied by Impagliazzo et. al. Our result means that both the testing and the approximate local decoding can be done in “one shot” with the minimal possible number (only two) of queries. Our results hold for values of ε as small as `−Ω(1), and we show that below 1/` no characterization is possible. ∗Weizmann Institute. Research supported by ISF and BSF grants. irit.dinur@weizmann.ac.il †Hebrew University. elazargo@cs.huji. ac.il
FMOL: Toward User-Friendly, Sophisticated New Musical Instruments

The design of new instruments and controllers for performing live computer music is an exciting ﬁeld of research that can lead to truly new music-making paradigms. The ever-increasing availability of sensing technologies that enable virtually any kind of physical gesture to be detected and tracked has indeed sprouted a wealth of experimental instruments and controllers with which to explore new creative possibilities. However, the design of these new controllers is often approached from an essentially technical point of view in which the novelty of the sensing technologies deployed over-shadows the attainable musical results. Although new instruments are not constrained to the physical restrictions of traditional ones, an integrated approach in which the instrument is designed as a whole and not as a combination of arbitrary input and output devices can lead to the creation of more rewarding and more musical instruments. This article describes an attempt at an integrated conception, called F@ust Music On-Line (FMOL), which is a simple mouse-controlled instrument that has been used on the Internet by hundreds of musicians during the past four years. FMOL has been created with the complementary goals of introducing the practice of experimental electronic music to newcomers while trying to remain attractive to more advanced electronic musicians. It has been used by musicians of diverse skills for the collective composition of the music of two important shows, including one opera of the Catalan theatre group La Fura dels Baus. It is also being played in live concerts.
Noisy Speech Recognition Based on Integration/Selection of Multiple Noise Suppression Methods Using Noise GMMs

To achieve high recognition performance for a wide variety of noise and for a wide range of signal-to-noise ratio, this paper presents methods for integration of four noise reduction algorithms: spectral subtraction with smoothing of time direction, temporal domain SVD-based speech enhancement, GMM-based speech estimation and KLT-based comb-filtering. In this paper, we proposed two types of combination methods of noise suppression algorithms: selection of front-end processor and combination of results from multiple recognition processes. Recognition results on the CENSREC-1 task showed the effectiveness of our proposed methods.
The importance of immune evasion in the pathogenesis of rabies virus

Rabies is a zoonotic disease caused by the Lyssavirus rabies virus (RABV) that can infect most mammals, including humans, where it has a case-fatality rate of almost 100%. Although preventable by vaccination, rabies causes c. 59,000 human fatalities every year worldwide. Thus, there exists an urgent need to establish an effective therapy and/or improve dissemination of vaccines for humans and animals. These outcomes require greater understanding of the mechanisms of RABV pathogenesis to identify new molecular targets for the development of therapeutics and/or live vaccines with high levels of safety. Importantly, a number of studies in recent years have indicated that RABV specifically suppresses host immunity through diverse mechanisms and that this is a key process in pathogenicity. Here, we review current understanding of immune modulation by RABV, with an emphasis on its significance to pathogenicity and the potential exploitation of this knowledge to develop new vaccines and antivirals.
Modelling language development and evolution with the benefit of hindsight

A description is given of a ‘back-tracking’ approach that could be used to model neural language development and language evolution. This approach aims to develop a neural model of human language capacity that incorporates important constraints on language structure, language comprehension and performance, and brain structure. The model is then to be used as a target for development or evolution. To this end, the target model would have to be simplified, so that the target model can be derived from the simplified version and learning algorithms (or structural changes). The benefit of this approach is that the development of important constraints such as the combinatorial productivity of human language is ensured. The paper illustrates the importance of including this constraint in models of language development and evolution. It then describes a neural model in which this constraint is satisfied. Finally, the paper describes how such a model could be used to investigate language development and/or evolution.
Evaluating the robustness of the DGT approach for smartphone-based vehicular networks

To cope with millions users becoming increasingly connected to Internet on the move, location-based services may be better supported by decentralized infrastructures enabling improved scalability, access rate and resiliency. In this context, our previous work introduced the Distributed Geographical Table (DGT), an overlay scheme that builds and maintains virtual neighborhood relationships between peers with heterogeneous connections. In this paper we illustrate a smartphone-based vehicular network that uses the DGT, and we show its robustness against disconnections caused by the unavailability of connectivity/coverage (mostly occurring in rural areas), as well as overlay reconnections due to vertical handovers (mostly occurring in highly serviced urban areas). The simulative analysis of sample scenarios based on experimental measurements of coverage and connection throughput, carried out across/around Parma urban area, gives us valuable insights for defining an integrated model that will combine the DGT, user/vehicle mobility and connectivity/coverage types.
ANTIHYPERGLYCEMIC AND ANTIHYPERLIPIDEMIC EFFECTS OF DIFFERENT FRACTIONS OF STEVIA REBAUDIANA LEAVES IN ALLOXAN INDUCED DIABETIC RATS

The present study carried out to investigate the antihyperglycemic, oral glucose tolerance test (OGTT) and antihyperlipidemic (Total cholesterol and triglycerides) effects of the different fractions (Petroleum ether, ethyl acetate and chloroform) of ethanolic extract of Stevia rebaudiana leaves. The different fractions of the extract were administered orally as a single dose of 150 mg/kg body weight to alloxan induced hyperglycemic rats and found to reduce blood glucose level significantly (p<0.05). The different fractions resulted in the significant reduction of lipid content which was increased in hyperglycemic rats. The plant fractions also improve the glucose tolerance in the glucose induced rats. The effects of plant fractions were compared with standard drug metformin. The phytochemical screening tests indicated that the different constituents such as saponins, tannins, triterpines, alkaloids, flavonoids and glycosides etc. were present in the plant which has antidiabetic and hypolipidemic properties. Thus, this investigation paves the way for plant based antihyperglycemic and antihyperlipidemic treatment and indicates that various fractions (Petroleum ether, ethyl acetate and chloroform) of the ethanolic extract of Stevia rebaudiana leaves have favorable effect in bringing down the severity of hyperglycemia, enhancing antihyperlipidemic activity and also improving glucose tolerance activity.
Towards Benchmarking Graph-Processing Platforms

Graph-processing platforms are increasingly used in a variety of domains. Although both industry and academia are developing and tuning graph-processing algorithms and platforms, the performance of graph-processing platforms has never been explored or compared in-depth. Thus, users face the daunting challenge of selecting an appropriate platform for their specific application. To alleviate this challenge, we propose an empirical method for benchmarking graph-processing platforms. We implement a benchmarking suite, which includes a comprehensive process and a selection of representative metrics, datasets, and algorithmic classes. In our process, we focus on evaluating basic performance, resource utilization, scalability, and overhead. Our selection includes 5 classes of algorithms and 7 graphs. We use our suite on 6 platforms and, besides valuable insights gained for each platform, we also present the first comprehensive comparison of graph-processing platforms.