nils-herrmann/clean_scirepeval huggingface dataset:
AMCloud: Toward a Secure Autonomic Mobile Ad Hoc Cloud Computing System

Cloud computing is a revolutionary paradigm to deliver computing resources, ranging from data storage/processing to software, as a service over the network, with the benefits of efficient resource utilization and improved manageability. The current popular cloud computing models encompass a cluster of expensive and dedicated machines to provide cloud computing services, incurring significant investment in capital outlay and ongoing costs. A more cost effective solution would be to exploit the capabilities of an ad hoc cloud which consists of a cloud of distributed and dynamically untapped local resources. The ad hoc cloud can be further classified into static and mobile clouds: an ad hoc static cloud harnesses the underutilized computing resources of general purpose machines, whereas an ad hoc mobile cloud harnesses the idle computing resources of mobile devices. However, the dynamic and distributed characteristics of ad hoc cloud introduce challenges in system management. In this article, we propose a generic em autonomic mobile cloud (AMCloud) management framework for automatic and efficient service/resource management of ad hoc cloud in both static and mobile modes. We then discuss in detail the possible security and privacy issues in ad hoc cloud computing. A general security architecture is developed to facilitate the study of prevention and defense approaches toward a secure autonomic cloud system. This article is expected to be useful for exploring future research activities to achieve an autonomic and secure ad hoc cloud computing system.
Ultrasound anatomy of the nerves supplying the cervical zygapophyseal joints: an exploratory study.

Nerve blocks and radiofrequency neurotomy of the nerves supplying the cervical zygapophyseal joints are validated tools for diagnosis and treatment of chronic neck pain, respectively. Unlike fluoroscopy, ultrasound may allow visualization of the target nerves, thereby potentially improving diagnostic accuracy and therapeutic efficacy of the procedures. The aims of this exploratory study were to determine the ultrasound visibility of the target nerves in chronic neck pain patients and to describe the variability of their course in relation to the fluoroscopically used bony landmarks.



Fifty patients with chronic neck pain were studied. Sonographic visibility of the nerves and the bony target of fluoroscopically guided blocks were determined. The craniocaudal distance between the nerves and their corresponding fluoroscopic targets was measured.



Successful visualization of the nerves varied from 96% for the third occipital nerve to 84% for the medial branch of C6. The great exception was the medial branch of C7, which was visualized in 32%. The bony targets could be identified in all patients, with exception of C7, which was identified in 92%. The craniocaudal distance of each nerve to the corresponding bony target varied, the upper limit of the range being 2.2 mm at C4, the lower limit 1.0 mm at C7.



The medial branches and their relation to the fluoroscopically used bony targets were mostly visualized by ultrasound, with the exception of the medial branch of C7 and, to a lesser extent, the bony target of C7. The nerve location may be distant from the fluoroscope's target. These findings justify further studies to investigate the validity of ultrasound guided blocks for invasive diagnosis/treatment of cervical zygapophyseal joint pain.
Artificial Immune Systems : A Novel Paradigm to Pattern Recognition

This chapter introduces a new computational intelligence paradigm to perform pattern recognition, named Artificial Immune Systems (AIS). AIS take inspiration from the immune system in order to build novel computational tools to solve problems in a vast range of domain areas. The basic immune theories used to explain how the immune system perform pattern recognition are described and their corresponding computational models are presented. This is followed with a survey from the literature of AIS applied to pattern recognition. The chapter is concluded with a trade-off between AIS and artificial neural networks as pattern recognition paradigms.
Older Drivers and New In-Vehicle Technologies: Adaptation and Long-Term Effects

The introduction of new technologies into vehicles has been imposing new forms of interaction, being a challenge to drivers but also to HMI research. The multiplicity of on-board systems in the market has been changing the driving task, being the consequences of such interaction a concern especially to older drivers. Several studies have been conducted to report the natural functional declines of older drivers and the way they cope with additional sources of information and additional tasks in specific moments. However, the evolution of these equipments, their frequent presence in the automotive market and also the increased acceptability and familiarization of older drivers with such technologies, compel researchers to consider other aspects of these interactions: from adaptation to the long term effects of using any in-vehicle technologies.
Design of the ultrafast LVDS I/O interface in 40 nm CMOS process

This paper presents the design and simulation results of the ultrafast LVDS I/O interface designed in 40 nm CMOS process. The LVDS transmitters and receivers were designed to support a data transfer of a multichannel Integrated Circuit dedicated for readout of hybrid pixel semiconductor detectors used for X-ray imaging applications. The transmitter is based on the current switching bridge architecture while the receiver is built of the inverting comparator with hysteresis. The LVDS I/O interface is supplied from 2.5 V and 0.9 V supply voltage. The transmitter and receiver occupy respectively 0.1 mm2 and 0.009 mm2 of chip area. The static/dynamic power consumption of the transmitter and receiver are respectively equal to 17.9/26.4 mW and 7.1/12.1 mW.
Miniaturized Broadband Ferrite T-DMB Antenna for Mobile-Phone Applications

Miniaturized 0.026 ¿ Co2Z hexaferrite and Ni-Mn-Co spinel ferrite T-DMB antennas were fabricated and characterized for antenna performance. The Co2Z hexaferrites were prepared with two different processes that are water quenching and air cooling. The water quenched Co2Z hexaferrite antenna shows -6.5 dB of 3-D average gain at 190 MHz and 37 MHz of bandwidth at -10 dB. A magnetic tangent loss of water-quenched Co2Z hexaferrite was lower than that of air-cooled Co2Z hexaferrite. Compared to the hexaferrite antennas, the Ni-Mn-Co ferrite antenna shows higher frequency performance. Its gain and bandwidth were measured to be -5.83 dB at 215 MHz and 41 MHz, respectively. Omnidirectional gain pattern was observed from all fabricated ferrite antennas.
XSS Vulnerability Detection Using Optimized Attack Vector Repertory

In order to detect the Cross-Site Script (XSS) vulnerabilities in the web applications, this paper proposes a method of XSS vulnerability detection using optimal attack vector repertory. This method generates an attack vector repertory automatically, optimizes the attack vector repertory using an optimization model, and detects XSS vulnerabilities in web applications dynamically. To optimize the attack vector repertory, an optimization model is built in this paper with a machine learning algorithm, reducing the size of the attack vector repertory and improving the efficiency of XSS vulnerability detection. Based on this method, an XSS vulnerability detector is implemented, which is tested on 50 real-world websites. The testing results show that the detector can detect a total of 848 XSS vulnerabilities effectively in 24 websites.
Playability Heuristics Evaluation (PHE) approach for Malaysian educational games

Heuristics evaluation is one of the common techniques being used for usability evaluation. The potential of HE has been explored in games design and development and later playability heuristics evaluation (PHE) is generated. PHE has been used in evaluating games. Issues in games usability covers forms of game usability, game interface, game mechanics, game narrative and game play. This general heuristics has the potential to be further explored in specific domain of games that is educational games. Combination of general heuristics of games (tailored based on specific domain) and education heuristics seems to be an excellent focus in order to evaluate the usability issues in educational games especially educational games produced in Malaysia.
A non-intrusive Short-Time Objective Intelligibility measure

We propose a non-intrusive intelligibility measure for noisy and non-linearly processed speech, i.e. a measure which can predict intelligibility from a degraded speech signal without requiring a clean reference signal. The proposed measure is based on the Short-Time Objective Intelligibility (STOI) measure. In particular, the non-intrusive STOI measure estimates clean signal amplitude envelopes from the degraded signal. Subsequently, the STOI measure is evaluated by use of the envelopes of the degraded signal and the estimated clean envelopes. The performance of the proposed measure is evaluated on a dataset including speech in different noise types, processed with binary masks. The measure is shown to predict intelligibility well in all tested conditions, with the exception of those including a single competing speaker. While the measure does not perform as well as the original (intrusive) STOI measure, it is shown to outperform existing non-intrusive measures.
Codebook-Based Hybrid Precoding for Millimeter Wave Multiuser Systems

In millimeter-wave (mmWave) systems, antenna architecture limitations make it difficult to apply conventional fully digital precoding techniques but call for low-cost analog radio frequency (RF) and digital baseband hybrid precoding methods. This paper investigates joint RF-baseband hybrid precoding for the downlink of multiuser multiantenna mmWave systems with a limited number of RF chains. Two performance measures, maximizing the spectral efficiency and the energy efficiency of the system, are considered. We propose a codebook-based RF precoding design and obtain the channel state information via a beam sweep procedure. Via the codebook-based design, the original system is transformed into a virtual multiuser downlink system with the RF chain constraint. Consequently, we are able to simplify the complicated hybrid precoding optimization problems to joint codeword selection and precoder design (JWSPD) problems. Then, we propose efficient methods to address the JWSPD problems and jointly optimize the RF and baseband precoders under the two performance measures. Finally, extensive numerical results are provided to validate the effectiveness of the proposed hybrid precoders.
A Wide-Band Dual-Polarized Stacked Patch Antenna

A wideband dual-polarized slot-coupled stacked patch antenna operating in the UMTS (1920-2170 MHz), WLAN (2.4-2.484 GHz), and UMTS II (2500-2690 MHz) frequency bands is described. Measurements on a prototype of the proposed patch antenna confirm good performance in terms of both impedance matching and isolation
Autophagy and the Cell Cycle: A Complex Landscape

Autophagy is a self-degradation pathway, in which cytoplasmic material is sequestered in double-membrane vesicles and delivered to the lysosome for degradation. Under basal conditions, autophagy plays a homeostatic function. However, in response to various stresses, the pathway can be further induced to mediate cytoprotection. Defective autophagy has been linked to a number of human pathologies, including neoplastic transformation, even though autophagy can also sustain the growth of tumor cells in certain contexts. In recent years, a considerable correlation has emerged between autophagy induction and stress-related cell-cycle responses, as well as unexpected roles for autophagy factors and selective autophagic degradation in the process of cell division. These advances have obvious implications for our understanding of the intricate relationship between autophagy and cancer. In this review, we will discuss our current knowledge of the reciprocal regulation connecting the autophagy pathway and cell-cycle progression. Furthermore, key findings involving nonautophagic functions for autophagy-related factors in cell-cycle regulation will be addressed.
A Prolog Datamodel for State Chart XML

SCXML was proposed as one description language for dialog control in the W3C Multimodal Architecture but lacks the facilities required for grounding and reasoning. This prohibits the application of many dialog modeling techniques for multimodal applications following this W3C standard. By extending SCXML with a Prolog datamodel and scripting language, we enable those techniques to be employed again. Thereby bridging the gap between respective dialog modeling research and a standardized architecture to access and coordinate modalities.
Eye movements in Usability Research Why “ Rising from the Ashes ” rather than “ Taking off like Wildfire ? ”

This section considers the application of eye movements to user interfaces—both for analyzing interfaces, measuring usability, and gaining insight into human performance—and as an actual control medium within a human-computer dialogue. The two areas have generally been reported separately; but this book seeks to tie them together. For usability analysis, the user’s eye movements while using the system are recorded and later analyzed retrospectively, but the eye movements do not affect the interface in real time. As a direct control medium, the eye movements are obtained and used in real time as an input to the user-computer dialogue. They might be the sole input, typically for disabled users or hands-busy applications, or they might be used as one of several inputs, combining with mouse, keyboard, sensors, or other devices.
Bijections for Cayley trees, spanning trees, and their q-analogues

We construct a family of extremely simple bijections that yield Cayley’s famous formula for counting trees. The weight preserving properties of these bijections furnish a number of multivariate generating functions for weighted Cayley trees. Essentially the same idea is used to derive bijective proofs and q-analogues for the number of spanning trees of other graphs, including the complete bipartite and complete tripartite graphs. These bijections also allow the calculation of explicit formulas for the expected number of various statistics on Cayley trees.
Comparative Study on DFD to UML Diagrams Transformations

Most of legacy systems use nowadays were modeled and documented using structured approach. Expansion of these systems in terms of functionality and maintainability requires shift towards object-oriented documentation and design, which has been widely accepted by the industry. In this paper, we present a survey of the existing Data Flow Diagram (DFD) to Unified Modeling language (UML) transformation techniques. We analyze transformation techniques using a set of parameters, identified in the survey. Based on identified parameters, we present an analysis matrix, which describes the strengths and weaknesses of transformation techniques. It is observed that most of the transformation approaches are rule based, which are incomplete and defined at abstract level that does not cover in depth transformation and automation issues. Transformation approaches are data centric, which focuses on datastore for class diagram generation. Very few of the transformation techniques have been applied on case study as a proof of concept, which are not comprehensive and majority of them are partially automated. Unified Modeling Language (UML); Data Flow Diagram (DFD); Class Diagram; Model Transformation.
Using Taguchi Method to Optimize Welding Pool of Dissimilar Laser Welded Components

In the present work CO2 continuous laser welding process was successfully applied and optimized for joining a dissimilar AISI 316 stainless steel and AISI 1009 low carbon steel plates. Laser power, welding speed, and defocusing distance combinations were carefully selected with the objective of producing welded joint with complete penetration, minimum fusion zone size and acceptable welding profile. Fusion zone area and shape of dissimilar austenitic stainless steel with ferritic low carbon steel were evaluated as a function of the selected laser welding parameters. Taguchi approach was used as statistical design of experiment (DOE) technique for optimizing the selected welding parameters in terms of minimizing the fusion zone. Mathematical models were developed to describe the influence of the selected parameters on the fusion zone area and shape, to predict its value within the limits of the variables being studied. The result indicates that the developed models can predict the responses satisfactorily.
Domain Specific Modeling Language for Cyber Physical Systems

The benefits of Domain Specific Modeling Languages (DSML), for modeling and design of cyber physical systems, have been acknowledged in previous years. In contrast to general purpose modeling languages, such as Unified Modeling Language, DSML facilitates the modeling of domain specific concepts. The objective of this work is to develop a simple graphical DSML for cyber physical systems, which allow the unified modeling of the structural and behavioral aspects of a system in a single model, and provide model transformation and design verification support in future. The proposed DSML was defined in terms of its abstract and concrete syntax. The applicability of the proposed DSML was demonstrated by its application in two case studies: Traffic Signal and Arbiter case studies. The results showed that the proposed DSML produce simple and unified models with possible model transformation and verification support.
Building and Employing Cross-Reality

Considers present and future practical applications of cross-reality. From tools to build new 3D virtual worlds to the products of those tools, cross-reality is becoming a staple of our everyday reality. Practical applications of cross-reality include the ability to virtually visit a factory to manage and maintain resources from the comfort of your laptop or desktop PC as well as sentient visors that augment reality with additional information so that users can make more informed choices. Tools and projects considered are:Project Wonderland for multiuser mixed reality;ClearWorlds: mixed- reality presence through virtual clearboards; VICI (Visualization of Immersive and Contextual Information) for ubiquitous augmented reality based on a tangible user interface; Mirror World Chocolate Factory; and sentient visors for browsing the world.
Deadlock Avoidance Controller Design for Timed Petri Nets Using Stretching

The recently introduced method, which was called ldquostretching,rdquo is extended to timed Petri nets which may have both controllable and uncontrollable transitions. Using this method, a new Petri net, called ldquostretched Petri net,rdquo which has only unit firing durations, is obtained to represent a timed-transition Petri net. Using this net, the state of the original timed Petri net can be represented easily. This representation also makes it easy to design a supervisory controller for a timed Petri net for any purpose. In this paper, supervisory controller design to avoid deadlock is considered in particular. Using this method, a controller is first designed for the stretched Petri net. Then, using this controller, a controller for the original timed Petri net is obtained. Algorithms to construct the reachability sets of the stretched and original timed Petri nets, as well as algorithms to obtain the controller for the original timed Petri net are presented. These algorithms are implemented using Matlab. Examples are also presented to illustrate the introduced approach.
A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis

We measure the knowledge flows between countries by analysing publication and citation data, arguing that not all citations are equally important. Therefore, in contrast to existing techniques that utilize absolute citation counts to quantify knowledge flows between different entities, our model employs a citation context analysis technique, using a machine-learning approach to distinguish between important and non-important citations. We use 14 novel features (including context-based, cue words-based and text-based) to train a Support Vector Machine (SVM) and Random Forest classifier on an annotated dataset of 20,527 publications downloaded from the Association for Computational Linguistics anthology (http://allenai.org/data.html). Our machine-learning models outperform existing state-of-the-art citation context approaches, with the SVM model reaching up to 61% and the Random Forest model up to a very encouraging 90% Precision–Recall Area Under the Curve, with 10-fold cross-validation. Finally, we present a case study to explain our deployed method for datasets of PLoS ONE full-text publications in the field of Computer and Information Sciences. Our results show that a significant volume of knowledge flows from the United States, based on important citations, are consumed by the international scientific community. Of the total knowledge flow from China, we find a relatively smaller proportion (only 4.11%) falling into the category of knowledge flow based on important citations, while The Netherlands and Germany show the highest proportions of knowledge flows based on important citations, at 9.06 and 7.35% respectively. Among the institutions, interestingly, the findings show that at the University of Malaya more than 10% of the knowledge produced falls into the category of important. We believe that such analyses are helpful to understand the dynamics of the relevant knowledge flows across nations and institutions.
Application of Ontologies in Cloud Computing: The State-Of-The-Art

This paper presents a systematic survey on existing literatures and seminal works relevant to the application of ontologies in different aspects of Cloud computing. Our hypothesis is that ontologies along with their reasoning capabilities can have significant impact on improving various aspects of the Cloud computing phenomena. Ontologies can promote intelligent decision support mechanisms for various Cloud based services. They can also provide effective interoperability among the Cloud based systems and resources. This survey can promote a comprehensive understanding on the roles and significance of ontologies within the overall domain of Cloud Computing. Also, this project can potentially form the basis of new research area and possibilities for both ontology and Cloud computing communities.
Consensus in Sparse, Mobile Ad Hoc Networks

Consensus is central to several applications including collaborative ones which a wireless ad hoc network can facilitate for mobile users in terrains with no infrastructure support for communication. We solve the consensus problem in a sparse network in which a node can at times have no other node in its wireless range and useful end-to-end connectivity between nodes can just be a temporary feature that emerges at arbitrary intervals of time for any given node pair. Efficient one-to-many dissemination, essential for consensus, now becomes a challenge; enough number of destinations cannot deliver a multicast unless nodes retain the multicast message for exercising opportunistic forwarding. Seeking to keep storage and bandwidth costs low, we propose two protocols. An eventually relinquishing (◇ RC) protocol that does not store messages for long is used for attempting at consensus, and an eventually quiescent (◇ QC) one that stops forwarding messages after a while is used for concluding consensus. Use of the ◇ RC protocol poses additional challenges for consensus, when the fraction, f/n, of nodes that can crash is 1/4 ≤ f/n <; 1/2. Consensus latency and packet overhead are measured through simulations and both decrease considerably even for a modest increase in network density.