Miracle-dz/UniFAR-FTUs huggingface dataset:
Software measure specification

This paper introduces the model-order-mapping (MOM) approach for specifying software/document measures. A MOM specification requires that the important attributes of the document be identified, a model that captures the attributes be chosen, and a mapping from the document to the model be specified. A partial ordering on the model must be developed as well as an order-preserving mapping from the model to an answer set. The relationship of the approach to measurement theory is shown. Validation of the MOM specification is presented.Properties of software measures that are guaranteed by a validated MOM specification and those that can be proved from a validated specification are described.
An SLA Evaluator for Multimedia Content Adaptation Services

Content adaptation is used to adapt multimedia content to a version required by users. In the service-oriented scheme, adaptation functions are provided as services by third-party service providers. Clients pay for the consumed services and thus demand service quality. Providers advertise their services; each with varied quality-of-services (QoS). Some of these QoS however, may not be deliverable accordingly during the actual service execution due to heavy load. Thus, the provider should able to determine a current deliverable QoS before the service level agreement (SLA) is settled with the requesters. In this paper, we propose a strategy for service providers to evaluate incoming requests and capable of offering the new QoS to the requests potentially being initially rejected. The proposed strategy takes into account the current server load and requests' priority. We analysed the performance of the proposed strategy in terms of SLA settlement under various conditions. The results indicate that the proposed strategy performs well.
Adaptive and distributed homology computation with application to large scale sensor networks

The homology groups provide useful information about a space. In several applications, including sensor networks, a combinatorial space is built to reflect the data and their relations about a specific topic to be analyzed. Hence the computation of the homology groups is of prime interest. However, the combinatorial space may vary and the computation of its homology groups becomes more difficult. This paper proposes an adaptive algorithm which updates incrementally the homology groups, and because it uses mostly small local computations, it is inherently well adapted to large-scale network. In the second part of the paper, the algorithm is developed and applied to the sensing coverage problem in a sensor networks. Because of its structure, the algorithm is inherently distributed.
Biomechanical analysis of facet joint slippage of lumbosacral joints under static loadings

In this study, three-dimensional laser scanning technology was employed to measure geometrical data of the human spine vertebrae. Based on the measured point-cloud data of the vertebra figuration, a detailed three-dimensional nonlinear finite element model of the lumbosacral joint L5-S1 of the spine was created and used to investigate the biomechanical properties of the lumbosacral joint. The finite element model was finely developed and validated according to available experimental results. The results show that facet articulations are important to stability of the lumbosacral joint. 1000N compressive force or 100N anterior force may yield the facet joint slippage for around 1mm and the facet contact surfaces may slip for around 2.8mm under both of 10Nm extension moment and 1000N compressive force. The finite element model might provide a detailed and accurate computational model for biomechanical analyses of the lumbosacral joint and studies of relative instrument implant and individual design of instruments.
Progress and Challenges in VLSI Placement Research

Given the significance of placement in integrated circuit (IC) physical design, extensive research studies performed over the last 50 years addressed numerous aspects of global and detailed placement. The objectives and the constraints dominant in placement have been revised many times over, and continue to evolve. Additionally, the increasing scale of placement instances affects the algorithms of choice for high-performance tools. We survey the history of placement research, the progress leading up to the state of the art, and outstanding challenges.
Clustering-based transduction for learning a ranking model with limited human labels

Transductive learning is a semi-supervised learning paradigm that can leverage unlabeled data by creating pseudo labels for learning a ranking model, when there is only limited or no training examples available. However, the effectiveness of transductive learning in information retrieval (IR) can be hindered by the low quality pseudo labels. To this end, we propose to incorporate a two-step k-means clustering algorithm to select the high quality training queries for generating the pseudo labels. In particular, the first step selects the high-quality queries for which the relevant documents are highly coherent as indicated by the clustering results. The second step then selects the initial training examples for the transductive learning that iteratively aggregating the pseudo examples. Finally, the learning to rank (LTR) algorithms are applied to learn the ranking model using the pseudo training examples created by the transductive learning process. Our proposed approach is particularly suitable for applications where there is only little or no human labels available as it does not necessarily involve the use of relevance assessments information or human efforts. Experimental results on the standard TREC Tweets11 collection show that our proposed approach outperforms strong baselines, namely the conventional applications of learning to rank algorithms using human labels for the training and transductive learning using all the queries available.
Network processing performability evaluation on heterogeneous reliability multicore processors using SRN model

Future network systems and embedded infrastructure devices in ubiquitous environments will need to consume low power and process large amounts of network packet traffic. In order to meet necessary high processing efficiency requirements, future processors will have many heterogeneous cores with reduced reliability due to low voltage, small transistor sizes, semiconductor wearout, and environmental factors such as noise and interference. It will be necessary for multi-core network infrastructure software to mitigate transient hardware faults to maintain acceptable system reliability. Applications such as packet processing can benefit from the reliability versus performance tradeoff. We propose a model based on Stochastic Reward Nets to evaluate the performance vs. reliability tradeoff of unreliable embedded multi-core network processors, and apply this model to a multi-core packet processing application.
Developments in Networks of Evolutionary Processors

Networks of evolutionary processors (NEPs) are distributed word rewriting systems typically viewed as language generators. Each node contains a set of words, a set of operations (typically insertion, deletion or rewriting of one symbol with another one), an input fllter and an output fllter. The purpose of this paper is to overview existing models of NEPs, their variants and developments. In particular, besides the basic model, hybrid networks of evolutionary processors (HNEPs) have been extensively studied. In HNEPs, operations application might be restricted to speciflc end of the string, but the fllters are random-context conditions (they were regular in the basic model). We will also cover the literature on the so-called obligatory HNEPs, i.e., ones where the operations are obligatory: the string that cannot be rewritten is not preserved. Some speciflc aspects that we pay attention to are: computational universality and completeness, the topology of the underlying graph, the number of nodes, the power of fllters.
Socio-Economic Impacts on Local Community through Tourism Development with Special Reference to Heritance Kandalama

Tourism is considered as one of the largest and fastest developing sectors of the world. Its high growth and development rates bring considerable volumes of foreign currency inflows, infrastructure development, employment generation, regional development, economic multiplier effects and introduction of new management and educational experience actively affect various sectors of economy, which will be positively affected to the social and economic development of the country. However the industry also generates a number of other negative socio- economic and cultural impacts on local communities. Therefore, the study considers the main social and economic impacts on local community trough tourism development in Kandalama area of Sri Lanka. Heritance Kandalama, a star class hotel, commenced its operations in 1994 beside the Kandalama Lake in a picturesque environment. During the construction stage there were many protests against the hotel and may parties claimed that the hotel will pollute the natural and the socio-cultural environment in the area. Finally, the company built an award winning environmental friendly hotel and introduced many programs to deliver benefits to the local community through their CSR activities. The study mainly target to identify the social and economic impacts on local community and their perception towards the tourism development in the neighborhood. The study is adapted the mixed methodology and the data is generated through structured questionnaire survey, personal interviews and discussions. The study identified that community has developed positive attitudes about the tourism development and the community is accepted tourism as a major income source through active and passive participations. The hotel also has taken numerous policy decisions and practices to ensure the delivery of benefits of tourism to the local community. As usually the industry has generated both positive and negative impacts in the area. However, the negative impacts are at a minimum level when compare with the positive impacts. It is suggested that to have more community awareness and education programs in order to obtain positive benefits and to minimize the negative impacts of tourism. Community empowerment and their capacity building is highly important in this context.
A parallel simulator for distributed and cooperative web caches

Abstract: The use of Web caches makes it possible to offer a service of better quality to Internet users. Due to the difficulty in obtaining a real network of caches to experience with, most research projects use Web caches simulators. This paper presents a Web cache simulator capable of executing simulations of distributed and cooperative Web caches servers. The simulator allows the measurement of the impact of configuration parameters in the cache performance, making possible to design better cooperative cache networks. To show an example of the simulator use, simulations based in the Brazilian National Research Network - RNP are presented.
Kobe University Repository : Kernel Tit le Calcium pyrophosphate dihydrate deposit ion in the transverse ligament of the at las : an unusual cause of cervical myelopathy

A 75-year-old male presented with progressive myelopathy due to retro-odontoid massive deposits of calcium pyrophosphate dehydrate (CPPD) crystals. Magnetic resonance imaging revealed a non-enhanced isointense extradural mass on T1-weighted image and heterogeneous intense mass on T2-weighted image. Computed tomography (CT) showed linear calcification within the mass. The mass was resected via a posterolateral approach resulting in marked improvement of the symptoms. Histological examination revealed birefringent rhomboid crystals consistent with CPPD. The preoperative differential diagnosis of periodontoid CPPD deposition disease in the elderly population should be considered, particularly if CT studies demonstrate small areas of calcification within the retroodontoid mass.
Proceedings of the Annual Meeting of the Cognitive Science Society

The Interactive Strategy Trainer for Active Reading and Thinking (iSTART) is an intelligent tutoring system that provides students with automated training on reading strategies. In particular, iSTART trains students to self-explain target sentences so as to integrate encoded information into a coherent mental representation. The goal of this study was to investigate the relation between text structures and the generation of bridging and elaborative inferences during self-explanation. We developed a computational model in which textual cohesion was interpreted as matrices of textbase cohesion values, such as argument overlap or semantic similarity, but also as matrices of situation model cohesion values such as causality. The model successfully predicted the different types of self-explanations as a function of the textual cohesion. We also found that students’ prior knowledge interacts with the textual cohesion effect when cohesion was based on situation model indices.
The personal security system: a framework for reforming Social Security

The U.S. Social Security System is in urgent need of reform. It has a massive long-term deficit that cannot be covered without major payroll tax hikes or significant benefit cuts. For example, paying for Social Security benefits on an ongoing basis requires an immediate and permanent 4.7 percentage-point increase in the payroll tax rate. Since the current tax rate is 12.4 percent, this represents a 40 percent tax hike. This is more than twice the requisite tax hike reported by the Social Security Trustees. Their half-truth about Social Security finances reflects the use of a truncated planning horizon. In addition to being effectively insolvent, the Social Security System is also inefficient, inequitable, uninformative, and outmoded. Our plan, the Personal Security System (PSS), would redress these problems by replacing the Old-Age Insurance (OAI) portion of Social Security with a system of individual accounts and by establishing a dedicated stream of revenues to pay off the current system’s unfunded liability. Simulations of this approach to Social Security reform show substantial long-run improvements in U.S. living standards. These gains reflect a partial alleviation of the enormous fiscal burden that future generations will face as a result of current entitlement programs. Because precise analysis of any Social Security reform requires the use of the Social Security Administration’s extensive databases, we strongly urge Congress to instruct the Social Security Administration to undertake a detailed analysis of this proposal.
Race, poverty, and social justice : multidisciplinary perspectives through service learning

This volume explores multiple examples of how to connect classrooms to communities through service learning and participatory research to teach issues of social justice. The various chapters provide examples of how collaborations between students, faculty, and community partners are creating models of democratic spaces (on campus and off campus) where the students are teachers and the teachers are students. The purpose of this volume is to provide examples of how service learning can be integrated into courses addressing social justice issues. At the same time, it is about demonstrating the power of service learning in advancing a course content that is community-based and socially engaged.To stimulate the adaptation of the approaches described in these books, each volume includes an Activity / Methodology table that summarizes key elements of each example, such as class size, pedagogy, and other disciplinary applications. Click here for the table to this title.
Green mining: energy consumption of advertisement blocking methods

Extending battery life on mobile devices has become an important topic recently due to the increasing frequency of smartphone adoption. A primary component of smart phone energy consumption is the apps that run on these devices. Many apps have embedded advertising and web browser apps will show ads that are embedded on webpages. Other researchers have found that advertising libraries and advertisements tend to increase power usage. But is the converse true? If we use advertisement blocking software will we consume less energy, or will the overhead of ad-blocking consume more energy? This study seeks to determine the effects of advertisements on energy consumption, and the effects of attempts to block the advertisements. We compared different methods of blocking advertisements on an Android mobile phone platform and compared the power efficiency of these methods. We found many cases where ad-blocking software or methods resulted in increased power use.
'Critically' reinvigorating teacher education: Issues and dilemmas

Introduction The intention of the workshop was to provide a space to investigate ways of reclaiming teacher education programs as sites for transformative learning. In the tradition of critical-democratic education, the intent was to create a new ‘social imagination’ (Greene, 1995) with its emphasis on social justice, respect for others, critical inquiry, equality, freedom, civic courage and concern for the collective good (Giroux, 1992). These are the principles and values that guide our individual and collective efforts to reinvigorate an undergraduate teacher education program. In this workshop, we attempted to address two key questions: what kinds of teachers do we require in these conservative times and how do we go about educating them?
Inverse Light Design for High-occlusion Environments

Lighting design is a demanding but very important task in computer cinematography, games and architectural design. Computer-assisted lighting design aims at providing the designers with tools to describe the desired outcome and derive a suitable lighting configuration to match their goal. In this paper, we present an automatic approach to the inverse light source emittance and positioning problem, based on a layered linear / non-linear optimization strategy and the introduction of a special light source indexing according to the compatibility of each individual luminary position with the desired illumination. Our approach is independent of a particular light transport model and can quickly converge to an appropriate and plausible light configuration that approximates the desired illumination and can handle environments with high occlusion.
Distributed Storage Coding for Flexible and Efficient Data Dissemination and Retrieval in Wireless Sensor Networks

The technique of distributed storage coding has been widely used in wireless sensor networks for increasing the robustness of data storage and efficiency of data retrieval. Existing works mainly focus on scenarios in which each storage node stores a linear combination of a subset of K data packets generated by different source nodes. By solving the linear equations, a collector can recover all the K data packets with high probability. This paper explores the problem of flexible and efficient data dissemination and retrieval in wireless sensor networks. Our scheme exploits the broadcast nature of wireless transmission and improves the traditional random walk algorithm for efficient data dissemination. Furthermore, through the use of Fountain codes in data encoding, it enables a mobile collector to recover up-to-date data generated by any subset of source nodes. Specifically, by querying any t(1 + &#949;) storage nodes at the t-th time slot, the target data can be retrieved without having to decode all the source packets. Simulation results validate our analysis and show that the proposed schemes are flexible and efficient.
Novel strategies to target the ubiquitin proteasome system in multiple myeloma

Multiple myeloma (MM) is a hematological malignancy characterized by the accumulation of plasma cells in the bone marrow (BM). The success of the proteasome inhibitor bortezomib in the treatment of MM highlights the importance of the ubiquitin proteasome system (UPS) in this particular cancer. Despite the prolonged survival of MM patients, a significant amount of patients relapse or become resistant to therapy. This underlines the importance of the development and investigation of novel targets to improve MM therapy. The UPS plays an important role in different cellular processes by targeted destruction of proteins. The ubiquitination process consists of enzymes that transfer ubiquitin to proteins targeting them for proteasomal degradation. An emerging and promising approach is to target more disease specific components of the UPS to reduce side effects and overcome resistance. In this review, we will focus on different components of the UPS such as the ubiquitin activating enzyme E1, the ubiquitin conjugating enzyme E2, the E3 ubiquitin ligases, the deubiquitinating enzymes (DUBs) and the proteasome. We will discuss their role in MM and the implications in drug discovery for the treatment of MM.
FRT: Fast and reliable transport protocol for underwater wireless sensor networks

Underwater wireless sensor networks (UWSNs) are prone to message loss due to their poor link condition with high bit error rate (BER). Retransmission-based mechanisms such as ARQ can be used for the reliability, however, they are not suitable for UWSNs due to the inherent long propagation delay of UWSNs. Therefore, a forward error correction (FEC) mechanism might be an alternative in order to guarantee the reliable message delivery. In this paper, we therefore propose a fast and reliable transport (called FRT) protocol for UWSNs. The FRT protocol takes advantage of the FEC mechanism and utilizes link quality toward neighbors so as to provide reliable and fast delivery of packets. Using ns-2 simulator, we verify that our FRT protocol achieves less latency than an existing protocol without an increase of transmission overhead.
Acquisition of 1,000 eubacterial genes physiologically transformed a methanogen at the origin of Haloarchaea

Archaebacterial halophiles (Haloarchaea) are oxygen-respiring heterotrophs that derive from methanogens—strictly anaerobic, hydrogen-dependent autotrophs. Haloarchaeal genomes are known to have acquired, via lateral gene transfer (LGT), several genes from eubacteria, but it is yet unknown how many genes the Haloarchaea acquired in total and, more importantly, whether independent haloarchaeal lineages acquired their genes in parallel, or as a single acquisition at the origin of the group. Here we have studied 10 haloarchaeal and 1,143 reference genomes and have identified 1,089 haloarchaeal gene families that were acquired by a methanogenic recipient from eubacteria. The data suggest that these genes were acquired in the haloarchaeal common ancestor, not in parallel in independent haloarchaeal lineages, nor in the common ancestor of haloarchaeans and methanosarcinales. The 1,089 acquisitions include genes for catabolic carbon metabolism, membrane transporters, menaquinone biosynthesis, and complexes I–IV of the eubacterial respiratory chain that functions in the haloarchaeal membrane consisting of diphytanyl isoprene ether lipids. LGT on a massive scale transformed a strictly anaerobic, chemolithoautotrophic methanogen into the heterotrophic, oxygen-respiring, and bacteriorhodopsin-photosynthetic haloarchaeal common ancestor.
A robust adaptive nonlinear control approach to ship straight-path tracking design

This article focuses on the straight-path tracking problem for underactuated ships with parametric uncertainties and completely unknown control gain coefficient under bounded exogenous disturbances. Combined Nussbaum gain technique with backstepping approach, an adaptive robust controller is developed such that all signals and states are globally uniformly ultimately bounded (GUUB). Consequently, an underactuated ship can be stabilized on a prescribed straight path in a GUUB manner under external disturbances induced by wave and wind. Numerical simulation results on an ocean-going training ship 'YULONG', belonging to Dalian Maritime University, are presented to validate the effectiveness of the proposed algorithm.