Miracle-dz/UniFAR-FTUs huggingface dataset:
SOTERIA: Exploiting Process Variations to Enhance Hardware Security with Photonic NoC Architectures

Photonic networks-on-chip (PNoCs) enable high bandwidth on-chip data transfers by using photonic waveguides capable of dense-wavelength-division-multiplexing (DWDM) for signal traversal and microring resonators (MRs) for signal modulation. A Hardware Trojan in a PNoC can manipulate the electrical driving circuit of its MRs to cause the MRs to snoop data from the neighboring wavelength channels in a shared photonic waveguide. This introduces a serious security threat. This paper presents a novel framework called SOTERIA† that utilizes process variation based authentication signatures along with architecture-level enhancements to protect data in PNoC architectures from snooping attacks. Evaluation results indicate that our approach can significantly enhance the hardware security in DWDM-based PNoCs with minimal overheads of up to 10.6% in average latency and of up to 13.3% in energy-delay-product (EDP).
Poster: Obfuscating Program Control Flow with Intel SGX

Control flow obfuscation is a direct approach in protecting the confidentiality of program logic. However, existing works in this direction either failed to offer high confidentiality guarantees or incurred high performance overheads. In this paper, we propose CFHider, a high security and high performance control flow obfuscation technique. By leveraging program transformation and Intel Software Guard Extension (SGX) technology, CFHider hides control flow information to an opaque yet trusted execution environment, i.e., the SGX enclave. Our evaluation showed that, CFHider extensively raises the bar for reverse-engineering attacks targeting on the control flow confidentiality, and incurs a moderate performance overhead.
Poster: Exploring Uncertainty in GitHub OSS Projects: When and How Do Developers Face Uncertainty?

Recently, many developers begin to notice that uncertainty is a crucial problem in software development. Unfortunately, no one knows how often uncertainty appears or what kinds of uncertainty exist in actual projects, because there are no empirical studies on uncertainty. To deal with this problem, we conduct a large-scale empirical study analyzing commit messages and revision histories of 1,444 OSS projects selected from the GitHub repositories.
Poster: Identifying TraIn: A Neglected Form of Socio-Technical Incongruence

Socio-Technical Congruence (STC) indicates that social interactions among developers should be congruent with technical dependencies among their tasks. Prior research discovered that the lack of the "should-happen" communication will lead to integration errors and productivity decrease. However, the opposite scenario, excessive communication not matched by any technical dependencies, has been largely neglected. This paper terms such scenario as Transgressive Incongruence (TraIn). To automatically pin-point source files involved in TraIn, this paper defines a new form of coupling between files, called communication coupling. It measures the communication traffic among developers working on two files. Evaluation on 6 Apache open source projects reveals: 1) the communication coupling between files with structural dependencies is 3 to 10 times higher than that between files independent from each other; and 2) source files involved in TraIn are usually very bug-prone. This implies that TraIn may have negative impact on the quality of software systems, and thus should merit due attention.
Are All Experts Equally Good? A Study of Analyst Earnings Estimates

We investigate whether experts possess differential expertise when making predictions. We note that this would make it possible to aggregate multiple predictions into a result that is more accurate than their consensus average, and that the improvement prospects grow with the amount of differentiation. Turning this argument on its head, we show how differentiation can be measured by how much weighted aggregation improves on simple averaging. Taking stock-market analysts as experts in their domain, we do a retrospective study using historical quarterly earnings forecasts and actual results for large publicly traded companies. We use it to shed new light on the Sinha et al. (1997) result, showing that analysts indeed possess individual expertise, but that their differentiation is modest. On the other hand, they have significant individual bias. Together, these enable a 20%-30% accuracy improvement over consensus average.
Demystifying Cyber-Physical Malware

The traditional notion of malware is too narrow, and the prevalent characterizations (virus, worm, trojan horse, spyware etc.) are neither precise nor comprehensive enough to characterize cyber-physical malware (CPM). Detecting sophisticated CPM is like searching for a needle in the haystack without knowing what the needle looks like. This technical briefing congregates interdisciplinary knowledge to describe the fundamentals of CPM, the mathematical foundation for analyzing and verifying CPM, the current state-of-the-art, the challenges, and directions for future research. Employing real-world examples, we shall illustrate the challenges of analyzing and verifying CPM.
Dignity: The Ethos of Humanbecoming

The purpose of this paper is to elaborate the ethos of humanbecoming with the core knowings of living quality. This requires describing in more detail the tenets of dignity—reverence, awe, betrayal, and shame—and specifying the tenets further with the newknowings arising from the humanbecoming hermeneutic sciencing of Lives of Others. The author introduces the newly conceptualized paradoxes, revering-betraying and aweing-shaming.
HRM in Transition Economies: The Case of Serbia

HRM in Transition Economies: The Case of Serbia While the convergence vs. divergence debate has gained broad recognition among both HRM scholars and practitioners, it seems that a closer insight into current HRM developments in the South Eastern European transition economies has yet to be achieved. This paper, therefore, aims to highlight current HRM practices in Serbia and address possibilities for implementing the North American HRM model in a highly incompatible cultural setting. Investigation of HRM practices in Serbia is based on the "CRANET survey on Strategic International HRM" (Brewster et al., 2004) and on interviews with the HR managers of 38 randomly selected companies operating in Serbia. The Serbian national culture has been included a priori in the initial research design as an explanatory variable. Research findings suggest that both the incompetence of HR managers and professionals, as well as a slow-moving transition, need to be carefully considered to explain the distinctiveness of HRM in transition economies. On the other hand, national culture seems to be a key obstacle to the achievement of full convergence of performance appraisal and performance-related pay.
The Association Between Gait Speed and Cognitive Status in Community-Dwelling Older People: A Systematic Review and Meta-analysis.

BACKGROUND Gait speed and cognitive performance tend to decline with age. A better understanding of the dynamics of the association between gait speed and cognitive status may identify preclinical markers and improve diagnostic assessments. The objective was to quantify the association between gait speed and cognitive status in later life. METHODS A systematic search was undertaken of relevant databases for original articles published prior to June 2017, measuring the association between gait speed and cognition cross-sectionally or longitudinally among the community-dwelling population. A meta-analysis pooled results of the mean difference between concurrent measures of gait speed in the normal cognition group compared to non-normal cognition groups. RESULTS Thirty-six studies were selected, providing data from 29,520 participants. The majority of studies reported a significant association between slower gait speed and worse cognitive function in older people. Results of the meta-analysis of 27 studies showed that, compared to normal controls, clinically meaningful reductions in gait speed ranged from 0.11 m/s in those with cognitive impairment, to 0.20 m/s in those with mild dementia, and to 0.41 m/s in those with moderate dementia. CONCLUSION The strength of evidence for an association between gait speed and cognition was demonstrated by the number and consistency of results, as well as quality of the studies. Identification of diagnostic markers of motor-cognitive risk has led to increasing interest in the effects of interventions for prevention of gait speed loss and cognitive decline in aging.
Abiotic variables accounting for presence of the exotic rainbow trout (Oncorhynchus mykiss) in Eastern Quebec Rivers

Key-words: invasion success, abiotic filter, geomorphological variables, climatic variables, logistic regression modelling Rainbow trout is an exotic fish species that has been introduced in Quebec (Canada) since 1893–1894. Despite spatially-restricted stocking for recreational fishing, the species has spread throughout the Saint Lawrence River. In this study, the relationship between rainbow trout occurrence (presence or absence) and abiotic variables (river geomorphology and climate) was examined for 91 coastal rivers throughout Eastern Quebec in order to determine which variables promote or impede the ongoing invasion process. Results revealed that rainbow trout presence in Eastern Quebec was primarily determined by geomorphological parameters. The invader’s presence was strongly related to the presence of tributaries (especially larger ones). To a lesser extent, the presence of rainbow trout was positively related to warm spring and summer temperatures and negatively related to the peak flood date occurring during the egg deposition period (May). This study proposes a parsimonious modelling approach to identify which environmental parameters favour the spreading of an invader, even when a limited dataset is available due to the incomplete invasion process.
Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling

Global environmental changes are rapidly affecting species’ distributions and habitat suitability worldwide, requiring a continuous update of biodiversity status to support effective decisions on conservation policy and management. In this regard, satellite-derived Ecosystem Functional Attributes (EFAs) offer a more integrative and quicker evaluation of ecosystem responses to environmental drivers and changes than climate and structural or compositional landscape attributes. Thus, EFAs may hold advantages as predictors in Species Distribution Models (SDMs) and for implementing multi-scale species monitoring programs. Here we describe a modelling framework to assess the predictive ability of EFAs as Essential Biodiversity Variables (EBVs) against traditional datasets (climate, land-cover) at several scales. We test the framework with a multi-scale assessment of habitat suitability for two plant species of conservation concern, both protected under the EU Habitats Directive, differing in terms of life history, range and distribution pattern (Iris boissieri and Taxus baccata). We fitted four sets of SDMs for the two test species, calibrated with: interpolated climate variables; landscape variables; EFAs; and a combination of climate and landscape variables. EFA-based models performed very well at the several scales (AUCmedian from 0.881±0.072 to 0.983±0.125), and similarly to traditional climate-based models, individually or in combination with land-cover predictors (AUCmedian from 0.882±0.059 to 0.995±0.083). Moreover, EFA-based models identified additional suitable areas and provided valuable information on functional features of habitat suitability for both test species (narrowly vs. widely distributed), for both coarse and fine scales. Our results suggest a relatively small scale-dependence of the predictive ability of satellite-derived EFAs, supporting their use as meaningful EBVs in SDMs from regional and broader scales to more local and finer scales. Since the evaluation of species’ conservation status and habitat quality should as far as possible be performed based on scalable indicators linking to meaningful processes, our framework may guide conservation managers in decision-making related to biodiversity monitoring and reporting schemes.
Structural Properties of multilayer Software Networks: a Case Study in Tomcat

Statistical properties of software networks have been extensively studied. However, in the previous works, software networks are usually considered as a single-layer network, which cannot capture the authentic characteristics of software since software in its nature should be multilayer. In this paper, we explore the structural properties of the multilayer software network at the class level by progressively merging layers together, where each coupling type such as inheritance, implements, and method call defines a specific layer. A case study in software Tomcat is conducted using a set of 10 measures widely used in complex network literatures. The results show that some structural properties that are widely observed in software network researches can only emerge when several layers are merged together, such as high clustering coefficient, small value of average shortest path length, and high global efficiency. Our study highlights the importance of taking into consideration the multilayer nature of software systems. The results we found can provide valuable insights to our understanding and modeling of the dynamical processes taking place in the design and development of software systems.
Approximate Submodular Functions and Performance Guarantees

We consider the problem of maximizing non-negative non-decreasing set functions. Although most of the recent work focus on exploiting submodularity, it turns out that several objectives we encounter in practice are not submodular. Nonetheless, often we leverage the greedy algorithms used in submodular functions to determine a solution to the non-submodular functions. Hereafter, we propose to address the original problem by \emph{approximating} the non-submodular function and analyze the incurred error, as well as the performance trade-offs. To quantify the approximation error, we introduce a novel concept of $\delta$-approximation of a function, which we used to define the space of submodular functions that lie within an approximation error. We provide necessary conditions on the existence of such $\delta$-approximation functions, which might not be unique. Consequently, we characterize this subspace which we refer to as \emph{region of submodularity}. Furthermore, submodular functions are known to lead to different sub-optimality guarantees, so we generalize those dependencies upon a $\delta$-approximation into the notion of \emph{greedy curvature}. Finally, we used this latter notion to simplify some of the existing results and efficiently (i.e., linear complexity) determine tightened bounds on the sub-optimality guarantees using objective functions commonly used in practical setups and validate them using real data.
Echocardiographic Strain Analysis for the Early Detection of Left Ventricular Systolic/Diastolic Dysfunction and Dyssynchrony in a Mouse Model of Physiological Aging

Abstract Heart disease is the leading cause of hospitalization and death worldwide, severely affecting health care costs. Aging is a significant risk factor for heart disease, and the senescent heart is characterized by structural and functional changes including diastolic and systolic dysfunction as well as left ventricular (LV) dyssynchrony. Speckle tracking–based strain echocardiography (STE) has been shown as a noninvasive, reproducible, and highly sensitive methodology to evaluate LV function in both animal models and humans. Herein, we describe the efficiency of this technique as a comprehensive and sensitive method for the detection of age-related cardiac dysfunction in mice. Compared with conventional echocardiographic measurements, radial and longitudinal strain, and reverse longitudinal strain were able to detect subtle changes in systolic and diastolic cardiac function in mice at an earlier time point during aging. Additionally, the data show a gradual and consistent decrease with age in regional contractility throughout the entire LV, in both radial and longitudinal axes. Furthermore, we observed that LV segmental dyssynchrony in longitudinal axis reliably differentiated between aged and young mice. Therefore, we propose the use of echocardiographic strain as a highly sensitive and accurate technology enabling and evaluating the effect of new treatments to fight age-induced cardiac disease.
Molecular Epidemiology of Human Adenovirus–Associated Febrile Respiratory Illness in Soldiers, South Korea1

During January 2013–April 2014, we subjected nasopharyngeal specimens collected from patients with acute febrile respiratory illness in a military hospital to PCR testing to detect 12 respiratory viruses and sequence a partial hexon gene for human adenovirus (HAdV) molecular typing. We analyzed the epidemiologic characteristics of HAdV infections and compared clinical characteristics of HAdV types. Among the 305 patients with acute febrile respiratory illness, we detected respiratory viruses in 139 (45.6%) patients; HAdV was the most prevalent virus (69 cases). Of the 40 adenoviruses identified based on type, HAdV-55 (29 cases) was the most prevalent, followed by HAdV-4 (9 cases). HAdV-55 was common in patients with pneumonia (odds ratio 2.17; 95% CI 0.48–9.86) and hospitalized patients (odds ratio 5.21; 95% CI 1.06–25.50). In soldiers with HAdV infection in Korea, HAdV-55 was the most prevalent type and might be associated with severe clinical outcomes.
The Cost of Distorted Financial Advice: Evidence from the Mortgage Market

Many households lack the sophistication required to make complex financial decisions and risk being exploited when seeking advice from intermediaries. We build a model of financial advice, in which banks attain their optimal mortgage portfolio by setting rates and providing advice to their clientele. “Sophisticated” households know which mortgage type is best for them; “naive” are susceptible to the bank’s advice. Using data on the universe of Italian mortgages, we estimate the model and quantify the welfare implications of distorted financial advice.The average cost of the distortion is equivalent to an increase in the annual mortgage payment by 11%. However, since even distorted advice conveys information, banning advice altogether results in a loss of 998 euros per year on average. A financial literacy campaign is beneficial for naive households, but hurts sophisticated ones.
Towards an efficient deep learning model for musical onset detection

In this paper, we propose an efficient and reproducible deep learning model for musical onset detection (MOD). We first review the state-of-the-art deep learning models for MOD, and identify their shortcomings and challenges: (i) the lack of hyper-parameter tuning details, (ii) the non-availability of code for training models on other datasets, and (iii) ignoring the network capability when comparing different architectures. Taking the above issues into account, we experiment with seven deep learning architectures. The most efficient one achieves equivalent performance to our implementation of the state-of-the-art architecture. However, it has only 28.3% of the total number of trainable parameters compared to the state-of-the-art. Our experiments are conducted using two different datasets: one mainly consists of instrumental music excerpts, and another developed by ourselves includes only solo singing voice excerpts. Further, inter-dataset transfer learning experiments are conducted. The results show that the model pre-trained on one dataset fails to detect onsets on another dataset, which denotes the importance of providing the implementation code to enable re-training the model for a different dataset. Datasets, code and a Jupyter notebook running on Google Colab are publicly available to make this research understandable and easy to reproduce.
Data Mining definition services in Cloud Computing with Linked Data

In recent years Cloud Computing service providers have been adding Data Mining (DM) services to their catalog. Several syntactic and semantic proposals have been presented to address the problem of the definition and description of services in Cloud Computing in a comprehensive way. Considering that each provider defines its own service logic for DM, we find that using semantic languages and following the linked data proposal it is possible to design a specification for the exchange of data mining services, achieving a high degree of interoperability. In this paper we propose a schema for the complete definition of DM Cloud Computing services, considering key aspects such as pricing, interfaces, experimentation work-flow, among others. Our proposal leverages the power of Linked Data for validating its usefulness with the definition of various DM services to define a complete Cloud Computing service.
Recommending Multimedia Information in a Virtual Han Chang’an City Roaming System

Abstract This article presents a roaming system of Han Chang’an City, with both virtual reality (VR) technology and information recommendation technology. Nowadays, some new research issues in the cultural heritage domain can be achieved with the rapid development of VR technology. The ancient site of Han Chang’an City, as one of the most valuable and significant cultural heritages in China, attracts more and more attention around the world. To let more people understand Han Chang’an City and reproduce its beauty, in this article, we propose a virtual roaming system combined with information recommendation technology. First, Unity3D is selected as the three-dimensional platform to design the scenario model of Han Chang’ an City, and the virtual scene is reconstructed with VR technology, according to real historical data; then, the dynamic information recommendation module is designed to recommend hot topic information and personalized information. The former is obtained through web crawlers, including the latest released news related to Han Chang’an City for users. The latter is generated by the proposed hybrid recommendation algorithm, which combines explicit and implicit feedback. The performance of the proposed algorithm is validated on two datasets. Finally, we show some results of our system test. Our proposed system is released online now, and users can wander in the scene any time.
Poster: A Multi-year Analysis of Students' Build Errors in Agile Software Development Educational Projects

Team exercises for software development project-based learning (SDPBL) adopting an agile development model have become popular for training and education worldwide. In the agile development model, an essential part is the build process. In this study, we investigated students' build errors in agile SDPBL projects by monitoring and collecting logs of the build process from 2013 to 2016. From 2013 to 2015, we categorized the build errors and then discussed the resolutions for each types of build errors. In 2016, the instructors modified the SDPBL project the build error types and corresponding cause and resolution. As the result, in 2016, the number of build errors and the time required to solve the build errors decreased compared to previous years.