Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling And Verification Of Concurrent Programs Using UPPAAL

This paper describes the design and implementation of a library of reusable UPPAAL template processes which support reasoning and property checking of concurrent programs, e.g. to be realized in the Java programming language. The stimulus to the development of the library originated in the context of a systems programming undergraduate course. The library, though, can be of help to general practitioners of concurrent programming which nowadays are challenged to exploiting the potentials of modern multicore architectures. The paper describes the library and demonstrates its usage to modelling and exhaustive verification of mutual exclusion and common concurrent structures and synchronizers. UPPAAL was chosen because it is a popular and continually improved toolbox based on timed automata and model checking and it is provided of a user-friendly graphical interface which proves very important for debugging and property assessment of concurrent models. Java was considered as target implementation language because of its diffusion among application developers.
Evaluating prosody in synthetic speech with online (eye-tracking) and offline (rating) methods

This study examines the relationship between online processing effects observed in earlier eye-tracking experiments [1, 2] and offline quality ratings gathered for the synthetic and natural speech stimuli used in these experiments, along with their acoustic-prosodic properties. White et al. [2] reported that even high-quality synthetic speech failed to replicate the facilitative effect of contextually appropriate accent patterns found with human speech, while it produced a more robust intonational garden-path effect with contextually inappropriate patterns. They conjectured that both of these effects could be due to processing delays observed with the synthetic speech. In this paper, we present an acoustic analysis of the stimuli used in the eye-tracking experiments and an offline stimuli rating task, which was designed to investigate whether a context-independent measure of utterance quality could predict processing-based effects. The analysis reveals that for synthetic speech, longer adjectives—which provide more processing time—do facilitate anticipatory looks to the target. Larger values of F0 drop (difference between the F0 values of the adjective and following noun) also negatively influenced looks to the target and were negatively correlated with offline ratings, suggesting that this may be a specific acoustic factor that merits attention in future work on improving synthesis quality. Finally, the study shows that online measures of unconscious processing and offline measures of conscious judgments, taken together, can provide a more comprehensive evaluation of synthetic speech than either method alone.
Beyond Gene Delivery: Strategies to Engineer the Surfaces of Viral Vectors

Viral vectors have been extensively studied due to their great transduction efficiency compared to non-viral vectors. These vectors have been used extensively in gene therapy, enabling the comprehension of, not only the advantages of these vectors, but also the limitations, such as the activation of the immune system after vector administration. Moreover, the need to control the target of the vector has led to the development of chemical and non-chemical modifications of the vector surface, allowing researchers to modify the tropism and biodistribution profile of the vector, leading to the production of viral vectors able to target different tissues and organs. This review describes recent non-genetic modifications of the surfaces of viral vectors to decrease immune system activation and to control tissue targeting. The developments described herein provide opportunities for applications of gene therapy to treat acquired disorders and genetic diseases and to become useful tools in regenerative medicine.
Parallel Method for Discovering Frequent Itemsets Using Weighted Tree Approach

Every element of the transaction in a transaction database may contain the components such as item number, quantity, cost of the item bought and some other relevant information of the customer. Most of the association rules mining algorithms to discover frequent itemsets do not consider the components such as quantity, cost etc. In a large database it is possible that even if the itemset appears in a very few transactions, it may be purchased in a large quantity. Further, this may lead to very high profit. Therefore these components are the most important information and without which it may cause the lose of information. This motivated us to propose a parallel algorithm to discover all frequent itemsets based on the quantity of the item bought in a single scan of the database. This method achieves its efficiency by applying two new ideas. Firstly, transaction database is converted into an abstraction called Weighted Tree that prevents multiple scanning of the database during the mining phase. This data structure is replicated among the parallel nodes. Secondly, for each frequent item assigned to a parallel node, an item tree is constructed and frequent itemsets are mined from this tree based on weighted minimum support.
Meta-Heuristic Algorithm based on Ant Colony Optimization Algorithm, Tabu Search and Project Scheduling Problem (PSP) for the Traveling Salesman Problem

Traveling Salesman Problem (TSP) is focused to construct the path with the lowest distance between different places (nodes), visiting every one once. This paper proposed an algorithm to solve TSP adding three aspects: time, cost and effort, where the effort is calculated multiplying time, distance and cost factors and dividing by the sum of them; the aim of this estimation is optimizing the best way to visit the cities graph.
Distributed frank-wolfe under pipelined stale synchronous parallelism

Iterative-convergent algorithms represent an important family of applications in big data analytics. These are typically run on distributed processing frameworks deployed on a cluster of machines. On the other hand, we are witnessing the move towards data center operating systems (OS), where resources are unified by a resource manager and processing frameworks coexist with each other. In this context, different processing framework job tasks can be scheduled on the same machine and slow down a worker (straggler problem). Existing work has shown that an iteration model with relaxed consistency such as the Stale Synchronous Parallel (SSP) model, while still guaranteeing convergence, is able to cope with stragglers. In this paper we propose a model for the integration of the SSP model on a pipelined distributed processing framework. We then apply SSP on a distributed version of the Frank-Wolfe algorithm. We theoretically show its sparsity bounds and convergence under SSP. Finally, we experimentally show that the Frank-Wolfe algorithm applied on LASSO regression under SSP is able to converge faster than its BSP counterpart, especially under load conditions similar to those encountered in a data center OS.
Strong Religion: The Rise of Fundamentalisms around the World

Since the September 11 terrorist attacks against the United States, religious fundamentalism has dominated public debate as never before. Policymakers, educators and the general public all want to know: Why do fundamentalist movements turn violent? Are fundamentalisms a global threat to human rights, security and democratic forms of government? What is the future of fundamentalism? To answer questions like these, "Strong Religion" draws on the results of the Fundamentalism Project, a decade-long interdisciplinary study of antimodernist, antisecular militant religious movements on five continents and within seven religious traditions. The authors of this study analyze the various social structures, cultural contexts and political environments in which fundamentalist movements have emerged around the world, from the Islamic Hamas and Hizbullah to the Catholic and Protestant paramilitaries of Northern Ireland, and from the Moral Majority and Christian Coalition of the United states to the Sikh radicals and Hindu nationalists of India. Offering a vividly detailed portrait of the cultures that nourish such movements, "Strong Religion" describes different modes of fundamentalism and identifies the kinds of historical events that can trigger them. For anyone who wants to understand why fundamentalist movements arise and what makes them turn violent, "Strong Religion" should be essential reading.
Dynamic data aggregation for energy optimization in multi-hop Wireless Sensor Networks

This paper proposes a model where the energy usage of sensor nodes in a multi-hop Wireless Sensor Network (WSN) is optimized by using data aggregation, a technique which discards “unnecessary” packets so as to save bandwidth. It does so in two steps; first of which uses an Exponential Weighted Moving Average (EWMA) data aggregation technique to compare the current data value with all the previous values before deciding whether to forward or drop the packet. The second step optimizes the network even further by considering readings from neighboring sensors into the equation. Some flexibility has been designed in the algorithm allowing the precision level to be adjusted based on the users requirements. Simulated results show how the scheme reduces the number of packets transmitted and the normalized energy consumed by the nodes.
PNFEA: A Proposal Approach for Proactive Network Forensics Evidence Analysis to Resolve Cyber Crimes

Nowadays, cyber crimes are increasing and have affected large organizations with highly sensitive information. Consequently, the affected organizations spent more resources analyzing the cyber crimes rather than detecting and preventing these crimes. Network forensics plays an important role in investigating cyber crimes; it helps organizations resolve cyber crimes as soon as possible without incurring a significant loss. This paper proposes a new approach to analyze cyber crime evidence. The proposed approach aims to use cyber crime evidence to reconstruct useful attack evidence. Moreover, it helps investigators to resolve cyber crime efficiently. The results of the comparison of the proposed approach prove that it is more efficient in terms of time and cost compared with the generic and the modern process approach for network forensics. Index Terms—Cyber crime, network forensics, proactive approach, evidence investigation component.
Geographic Box Plots

Traditional box plots, described by Tukey in 1977, can be biased representations of geographic or spatial variables, since they do not take into account the areas associated with the elements of geographic variables. To help solve this problem, we propose and evaluate a spatially (areally) weighted box plot, a "geographic box plot," that can be used to describe a wide variety of geographic variables. Much of our discussion of box plots also applies to "traditional" and "geographic" histograms and percentile plots. Traditional and geographic box plots of one hypothetical and two real-world geographic variables are constructed and compared to illustrate our points, as well as to illustrate the often marked differences between traditional and geographic box plots of the same geographic variables. The real-world geographic variables considered here are human population density (in the year 2000) within the contiguous 48 United States and five-year-average (January 2001-December 2005) air temperature over the Arctic land surface. Our traditional box plot of population density over represented the small, high-density states, whereas our corresponding geographic box plot correctly depicted the geographic distribution of population density. A geographic box plot correctly accounted for the reduction in spherical grid-node areas with latitude over the Arctic land surface, whereas a traditional box plot of the spherical grid-node values did not. Our hope is that geographers and other scientists will make refinements to and find many more applications for our geographic box plots.
Detecting food intake acoustic events in noisy recordings using template matching

Automatic food intake monitoring using wearable systems is a promising research direction in the fight against obesity and eating disorders. Previous work has indicated progress towards automatic food intake monitoring using acoustic sensors for detecting periods of food intake, swallowing and chewing detection, and discriminating between solid and liquid food intake. However, little effort has been put towards acoustic detection in noisy recordings. In this paper, we explore detecting food intake events (particularly chew events) in the presence of restaurant background noise. Three templates were extracted from a clean signal to represent the beginning, middle and end phase of a chewing sequence. Then, each template was used with sliding window correlation to detect chew events in a noisy recording. The noisy signal was formed by instantaneous addition of a clean throat microphone recording during eating and restaurant noise recorded with the same throat microphone. Results show that the template created from the end phase of a chewing sequence outperformed templates from the beginning and middle phases for detecting chew events in a continuous clean and noisy test signal. An F1 score of 71.4% was achieved for detecting chews in very low signal-to-noise ratio of -10 dB.
Clinical Reasoning Automata for Simulated Patients

In this paper we introduce clinical reasoning automata to model states and transitions about different cognitive processes that occur during a clinical reasoning activity. A state of the automaton represents a particular process in a complex patient diagnosis using influence diagrams encoding clinical knowledge about the case. Transitions model switch between diagnosis cognitive processes, such as collecting evidences, formulating hypothesis or explicitly asking for assistance at a given point during the reasoning process. That way, we can efficiently model tutoring feedback hints for clinical reasoning learning that are based not only on the clinical knowledge, but also on the sequencing of the tutoring processes.
QoS aware power allocation in multi-hop multi-relay network

Considering the quality-of-service (QoS), power allocation is a critical importance issue in realizing multi-hop relay systems. In this paper considering the QoS Constraints in term of BER or instantaneous SNR, an optimal power allocation scheme that minimized the total power consumption in an amplify-and-forward (AF) multi-hop multi-branch transmission system is proposed. Considering an asymptotic expression for the target SNR as the QoS Constraint, we formulate our optimization problem as two standard convex optimization problems. Solving these problems we present an optimum power allocation algorithm which at first performs a branch selection phase holding the QoS Constraint, and then, drive a minimum total consumption value and also an optimal power allocation coefficient for their corresponding source and relay nodes. Optimized power allocation demonstrates a significant power saving performance over the uniform power allocation while guarantees the target SNR.
Integrated Flexible Electronic Devices Based on Passive Alignment for Physiological Measurement

This study proposes a simple method of fabricating flexible electronic devices using a metal template for passive alignment between chip components and an interconnect layer, which enabled efficient alignment with high accuracy. An electrocardiogram (ECG) sensor was fabricated using 20 µm thick polyimide (PI) film as a flexible substrate to demonstrate the feasibility of the proposed method. The interconnect layer was fabricated by a two-step photolithography process and evaporation. After applying solder paste, the metal template was placed on top of the interconnect layer. The metal template had rectangular holes at the same position as the chip components on the interconnect layer. Rectangular hole sizes were designed to account for alignment tolerance of the chips. Passive alignment was performed by simply inserting the components in the holes of the template, which resulted in accurate alignment with positional tolerance of less than 10 µm based on the structural design, suggesting that our method can efficiently perform chip mounting with precision. Furthermore, a fabricated flexible ECG sensor was easily attachable to the curved skin surface and able to measure ECG signals from a human subject. These results suggest that the proposed method can be used to fabricate epidermal sensors, which are mounted on the skin to measure various physiological signals.
A Top-Down and Bottom-Up Visual Attention Model for Humanoid Object Approaching and Obstacle Avoidance

Most of the research on humanoid walk tasks has considered a global representation of the scene that frequently relies on external sensors. This is detrimental to the autonomy and the reactivity of the agent under unknown or changing scenarios. Ego-centric localization has been less explored, and the works considering on-board acquisitions have mostly dealt with tasks under controlled scenarios where the path to the object is cleared from obstacles. In this work a behavior-based control scheme is proposed, so the robot Nao can approach and position in relation to a given face of an object, while avoiding obstacles. For this, the solution relies on top-down (color-based) and bottom-up (optic-flow-based) visual features, and proprioceptive information registered on-board. The model is decentralized and exploits the emergent aspect of behavior from the independent contribution of a walk and a look-at task. An embodied visual encoding approach is proposed to support the arbitration between competing behavioral modes.
MpiJava: A Java Interface to MPI

The overall aim of this paper is to introduce mpiJava|a Java interface to the widely used Message Passing Interface (MPI). In the rst part of the paper we discuss the design of the mpiJava API and issues associated with its development. In the second part of the paper we brieey describe an implementation of mpiJava on NT using the WMPI environment. We then discuss some measurements made of communications performance to compare mpiJava with C and Fortran bindings of MPI. In the nal part of the paper we summarize our ndings and brieey mention work we plan to undertake in the near future.
HOW TO REFUTE AN ARGUMENT USING ARTIFICIAL INTELLIGENCE

There is a family of terms in argumentation that are closely related to each other and that all refer to some way in which a given argument is attacked, rebutted, refuted, undercut, critically questioned or objected to, thereby defeating it or casting it into doubt. Proper understanding of this family of terms is fundamental to argumentation theory and to building argumentation technologies in artificial intelligence. This paper refines, clarifies and classifies them, using the Carneades Argumentation System. It begins with a simple example that illustrates two main ways of refuting an argument, and concludes with a seven-step procedure for seeking a refutation or objection.
Bacterial Diversity and Bioprospecting for Cold-Active Hydrolytic Enzymes from Culturable Bacteria Associated with Sediment from Nella Fjord, Eastern Antarctica

The diversity and cold-active hydrolytic enzymes of culturable bacteria associated with sandy sediment from Nella Fjord, Eastern Antarctica (69°22′6″ S, 76°21′45″ E) was investigated. A total of 33 aerobic heterotrophic bacterial strains were isolated at 4 °C. These bacterial isolates could be sorted into 18 phylotypes based on the 16S rRNA gene sequence belonging to four phyla, namely Alphaproteobacteria, Gammaproteobacteria, Bacteroidetes and Actinobacteria. Only seven isolates were psychrophilic, 15 isolates were moderately psychrophilic, and 11 isolates were psychrotolerant. More than 72% of the isolates required sodium chloride to grow. Esterase, β-glucosidase and proteases activities at 4 °C were detected in more than 45% of the strains while approximately 21%, 15% and 12% of the strains possessed lipase, amylase and chitinase, respectively. These results indicate that a relatively high culturable bacterial diversity is present within marine sediment of Nella Fjord and it could serve as an ideal candidate region for bioprospecting.
Who likes it more?: mining worth-recommending items from long tails by modeling relative preference

Recommender systems are useful tools that help people to filter and explore massive information. While the accuracy of recommender systems is important, many recent research indicated that focusing merely on accuracy not only is insufficient to meet user needs, but also may be harmful. Other characteristics such as novelty, unexpectedness and diversity should also be taken into consideration. Previous work has shown that more the sales of long-tail items could be more beneficial to both customers and some business models. However, the majority of collaborative filtering approaches tends to recommend popular selling items. In this work, we focus on long-tail item promotion and aggregate diversity enhancement, and propose a novel approach which diversifies the results of recommender systems by considering ``recommendations" as resources to be allocated to the items. Our approach increases the quantity and quality of long-tail item recommendations by adding more variation into the recommendation and maintains a certain level of accuracy simultaneously. The experimental results show that this approach can discover more worth-recommending items from Long Tails and improves user experience.
Educating the Reflective Practitioner for Catholic Secondary Schools.

This paper reports on the conceptualization and first year of implementation of a model of preservice teacher education and training established at the University of Notre Dame Australia to meet the specific needs of the Catholic education system. In setting up an appropriate model, the notion of the graduate teacher as one who is critically self-aware and sensitive to students' needs within a faith community assumed central importance. The nature of the Catholic school is outlined, with its emphasis on a holistic approach to education and its view of school as community. An essential component of the Diploma in Education program is students' involvement in a regular, well-planned, professionally supervised experience in schools. A curriculum sequence based on developmental and sequential stages was designed to facilitate the development of competence in planning, implementing, and evaluating teaching-learning processes and contexts across different subject areas. Data analysis that used a modified version of the Developmental Research Sequence provided evidence that the first year of the course has helped neophyte teachers move towards an ideal of reflective practice through building self-efficacy. (Contains 16 references.) (JDD) *********************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * *********************************************************************** EDUCATING THE REFLECIIVE PRALMIONER FOR CATHOLIC SECONDARY SCHOOLS