bluuebunny/crossref_metadata_2025 huggingface dataset:
Foundations of Modern Query Languages for Graph Databases
Authors: Angles Renzo , Arenas Marcelo , Barceló Pablo , Hogan Aidan , Reutter Juan , Vrgoč Domagoj
Published: September 2017

We survey foundational features underlying modern graph query languages. We first discuss two popular graph data models:
edge-labelled graphs
, where nodes are connected by directed, labelled edges, and
property graphs
, where nodes and edges can further have attributes. Next we discuss the two most fundamental graph querying functionalities:
graph patterns
and
navigational expressions
. We start with graph patterns, in which a graph-structured query is matched against the data. Thereafter, we discuss navigational expressions, in which patterns can be matched recursively against the graph to navigate paths of arbitrary length; we give an overview of what kinds of expressions have been proposed and how they can be combined with graph patterns. We also discuss several semantics under which queries using the previous features can be evaluated, what effects the selection of features and semantics has on complexity, and offer examples of such features in three modern languages that are used to query graphs: SPARQL, Cypher, and Gremlin. We conclude by discussing the importance of formalisation for graph query languages; a summary of what is known about SPARQL, Cypher, and Gremlin in terms of expressivity and complexity; and an outline of possible future directions for the area.
Inferring Clothing Insulation Levels Using Mechanisms of Heat Transfer
Authors: Shaabana Ala , Zheng Rong , Xu Zhipeng
Published: September 2017

To maintain productivity and alertness, individuals must be thermally comfortable in the space they occupy (whether it is a cubicle, a room, a car, etc.). However, it is often difficult to non-intrusively assess an occupant’s “thermal comfort,” and hence most HVAC engineers adopt fixed temperature settings to “err on the safe side.” These set temperatures can be too hot or too cold for individuals wearing different clothing, and as a result lead to feelings of discomfort as well as wastage of energy. Since humans dress to target a comfortable thermal sensation, it is reasonable to assume that clothing is an important measure of current thermal sensation. To this end, we develop SiCILIA, a platform that extracts physical and personal variables of an occupant’s thermal environment to infer the amount of clothing insulation without human intervention. The proposed inference algorithm builds upon theories of body heat transfer and is corroborated by empirical data. SiCILIA was tested in a vehicle with a passenger-controlled HVAC system. Experimental results show that the algorithm is capable of accurately predicting an occupant’s thermal insulation with a mean prediction error of 0.07clo.
A Survey of Dynamic Analysis and Test Generation for JavaScript
Authors: Andreasen Esben , Gong Liang , Møller Anders , Pradel Michael , Selakovic Marija , Sen Koushik , Staicu Cristian-Alexandru
Published: September 2017

JavaScript has become one of the most prevalent programming languages. Unfortunately, some of the unique properties that contribute to this popularity also make JavaScript programs prone to errors and difficult for program analyses to reason about. These properties include the highly dynamic nature of the language, a set of unusual language features, a lack of encapsulation mechanisms, and the “no crash” philosophy. This article surveys dynamic program analysis and test generation techniques for JavaScript targeted at improving the correctness, reliability, performance, security, and privacy of JavaScript-based software.
A Functional Taxonomy of Music Generation Systems
Authors: Herremans Dorien , Chuan Ching-Hua , Chew Elaine
Published: September 2017

Digital advances have transformed the face of automatic music generation since its beginnings at the dawn of computing. Despite the many breakthroughs, issues such as the musical tasks targeted by different machines and the degree to which they succeed remain open questions. We present a functional taxonomy for music generation systems with reference to existing systems. The taxonomy organizes systems according to the purposes for which they were designed. It also reveals the inter-relatedness amongst the systems. This design-centered approach contrasts with predominant methods-based surveys and facilitates the identification of grand challenges to set the stage for new breakthroughs.
A Tutorial for Olfaction-Based Multisensorial Media Application Design and Evaluation
Authors: Murray Niall , Ademoye Oluwakemi A. , Ghinea Gheorghita , Muntean Gabriel-Miro
Published: September 2017

Recently, multimedia researchers have added several so-called new media to the traditional multimedia components (e.g., olfaction, haptic, and gustation). Evaluating multimedia user-perceived Quality of Experience (QoE) is already non-trivial and the addition of multisensorial media components increases this challenge. No standardized methodology exists to conduct subjective quality assessments of multisensorial media applications. To date, researchers have employed different aspects of audiovisual standards to assess user QoE of multisensorial media applications and thus, a fragmented approach exists. In this article, the authors highlight issues researchers face from numerous perspectives including applicability (or lack of) existing audiovisual standards to evaluate user QoE and lack of result comparability due to varying approaches, specific requirements of olfactory-based multisensorial media applications, and novelty associated with these applications. Finally, based on the diverse approaches in the literature and the collective experience of authors, this article provides a tutorial and recommendations on the key steps to conduct olfactory-based multisensorial media QoE evaluation.
A Review on Quantification Learning
Authors: González Pablo , Castaño Alberto , Chawla Nitesh V. , Coz Juan José Del
Published: September 2017

The task of quantification consists in providing an aggregate estimation (e.g., the class distribution in a classification problem) for unseen test sets, applying a model that is trained using a training set with a different data distribution. Several real-world applications demand this kind of method that does not require predictions for individual examples and just focuses on obtaining accurate estimates at an aggregate level. During the past few years, several quantification methods have been proposed from different perspectives and with different goals. This article presents a unified review of the main approaches with the aim of serving as an introductory tutorial for newcomers in the field.
Modeling, Evaluation, and Scale on Artificial Pedestrians
Authors: Martinez-Gil Francisco , Lozano Miguel , García-Fernández Ignacio , Fernández Fernando
Published: September 2017

Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim of this article is to provide a bibliographic outlook so that the reader may have quick access to the most relevant works related to this problem. We have used three main axes to organize the article’s contents: pedestrian models, validation techniques, and multiscale approaches. The backbone of this work is the classification of existing pedestrian models; we have organized the works in the literature under five categories, according to the techniques used for implementing the operational level in each pedestrian model. Then the main existing validation methods, oriented to evaluate the behavioral quality of the simulation systems, are reviewed. Furthermore, we review the key issues that arise when facing multiscale pedestrian modeling, where we first focus on the behavioral scale (combinations of micro and macro pedestrian models) and second on the scale size (from individuals to crowds). The article begins by introducing the main characteristics of walking dynamics and its analysis tools and concludes with a discussion about the contributions that different knowledge fields can make in the near future to this exciting area.
Probabilistic Complex Event Recognition
Authors: Alevizos Elias , Skarlatidis Anastasios , Artikis Alexander , Paliouras Georgios
Published: September 2017

Complex event recognition (CER) applications exhibit various types of uncertainty, ranging from incomplete and erroneous data streams to imperfect complex event patterns. We review CER techniques that handle, to some extent, uncertainty. We examine techniques based on automata, probabilistic graphical models, and first-order logic, which are the most common ones, and approaches based on Petri nets and grammars, which are less frequently used. Several limitations are identified with respect to the employed languages, their probabilistic models, and their performance, as compared to the purely deterministic cases. Based on those limitations, we highlight promising directions for future work.
iSelf
Authors: Sun Boyuan , Ma Qiang , Zhang Shanfeng , Liu Kebin , Liu Yunhao
Published: September 2017

It has been a consensus that a certain relationship exists between personal emotions and usage pattern of the smartphone. Based on users’ emotions and personalities, more and more applications are developed to provide intelligent automation services on the smartphone, such as music recommendations or stranger introductions on social networking sites. Most existing work studies this relationship by learning large amounts of samples, which are manually labeled and collected from smartphone users. The manual labeling process, however, is very time-consuming and labor-intensive. To address this issue, we propose iSelf, a system that provides a general service of automatic detection of a user’s emotions in cold-start conditions with a smartphone. With the technology of transfer learning, iSelf achieves high accuracy given only a few labeled samples. We also embed a hybrid public/personal inference engine and validation system into iSelf, to make it maintain updates continuously. Through extensive experiments in real traces, the inferring accuracy is tested above 74% and can be improved increasingly through validation and updates. The application program interface has been open online for other developers.
Weakly Hard Schedulability Analysis for Fixed Priority Scheduling of Periodic Real-Time Tasks
Authors: Sun Youcheng , Natale Marco Di
Published: September 2017

The hard deadline model is very popular in real-time research, but is representative or applicable to a small number of systems. Many applications, including control systems, are capable of tolerating occasional deadline misses, but are seriously compromised by a repeating pattern of late terminations. The weakly hard real-time model tries to capture these requirements by analyzing the conditions that guarantee that a maximum number of deadlines can be possibly missed in any set of consecutive activations. We provide a new weakly hard schedulability analysis method that applies to constrained-deadline periodic real-time systems scheduled with fixed priority and without knowledge of the task activation offsets. The analysis is based on a Mixed Integer Linear Programming (MILP) problem formulation; it is very general and can be adapted to include the consideration of resource sharing and activation jitter. A set of experiments conducted on an automotive engine control application and randomly generated tasksets show the applicability and accuracy of the proposed technique.
BenchPrime
Authors: Liu Qingrui , Wu Xiaolong , Kittinger Larry , Levy Markus , Jung Changhee
Published: September 2017

This paper presents BenchPrime, an automated benchmark analysis toolset that is systematic and extensible to analyze the similarity and diversity of benchmark suites. BenchPrime takes multiple benchmark suites and their evaluation metrics as inputs and generates a hybrid benchmark suite comprising only essential applications. Unlike prior work, BenchPrime uses linear discriminant analysis rather than principal component analysis, as well as selects the best clustering algorithm and the optimized number of clusters in an automated and metric-tailored way, thereby achieving high accuracy. In addition, BenchPrime ranks the benchmark suites in terms of their application set diversity and estimates how unique each benchmark suite is compared to other suites.

As a case study, this work for the first time compares the DenBench with the MediaBench and MiBench using four different metrics to provide a multi-dimensional understanding of the benchmark suites. For each metric, BenchPrime measures to what degree DenBench applications are irreplaceable with those in MediaBench and MiBench. This provides means for identifying an essential subset from the three benchmark suites without compromising the application balance of the full set. The experimental results show that the necessity of including DenBench applications varies across the target metrics and that significant redundancy exists among the three benchmark suites.
Timestamp Temporal Logic (TTL) for Testing the Timing of Cyber-Physical Systems
Authors: Mehrabian Mohammadreza , Khayatian Mohammad , Shrivastava Aviral , Eidson John C. , Derler Patricia , Andrade Hugo A. , Li-Baboud Ya-Shian , Griffor Edward , Weiss Marc , Stanton Kevin
Published: September 2017

In order to test the performance and verify the correctness of Cyber-Physical Systems (CPS), the timing constraints on the system behavior must be met. Signal Temporal Logic (STL) can efficiently and succinctly capture the timing constraints of a given system model. However, many timing constraints on CPS are more naturally expressed in terms of events on signals. While it is possible to specify event-based timing constraints in STL, such statements can quickly become long and arcane in even simple systems. Timing constraints for CPS, which can be large and complex systems, are often associated with tolerances, the expression of which can make the timing constraints even more cumbersome using STL. This paper proposes a new logic, Timestamp Temporal Logic (TTL), to provide a definitional extension of STL that more intuitively expresses the timing constraints of distributed CPS. TTL also allows for a more natural expression of timing tolerances. Additionally, this paper outlines a methodology to automatically generate logic code and programs to monitor the expressed timing constraints. Since our TTL monitoring logic evaluates the timing constraints using only the timestamps of the required events on the signal, the TTL monitoring logic has significantly less memory footprint when compared to traditional STL monitoring logic, which stores the signal value at the required sampling frequency. The key contribution of this paper is a scalable approach for online monitoring of the timing constraints. We demonstrate the capabilities of TTL and our methodology for online monitoring of TTL constraints on two case studies: 1) Synchronization and phase control of two generators and, 2) Simultaneous image capture using distributed cameras for 3D image reconstruction.
On The Design and Application of Thermal Isolation Servers
Authors: Ahmed Rehan , Huang Pengcheng , Millen Max , Thiele Lothar
Published: September 2017

Recently, there has been an increasing trend towards executing real-time applications on multi-core platforms. However, this complicates the design problem, as applications running on different cores can interfere due to shared resources and mediums. In this paper, we focus on thermal interference, where a given task (τ
1
) heats the processor, resulting in reduced service (due to Dynamic Thermal Management (DTM)) to another task (τ
2
). In real-time domain, where tasks have deadline constraints, thermal interference is a substantial problem as it directly impacts the Worst Case Execution Time (WCET) of the effected application (τ
2
). The problem exacerbates as we move to mixed-criticality systems, where the criticality of τ
2
may be greater than the criticality of τ
1
, complicating the certification process.

In this paper, we propose a server based strategy (Thermal Isolation Server (TI Server)) which can be used to avoid thermal interference of applications. We also present a heuristic to design TI Servers to meet the timing constraints of all tasks and the thermal constraints of the system. TI Servers are time/space composable, and can be applied to a variety of task models. We also evaluate TI Servers on a hardware test-bed for validation purposes.
Antlab
Authors: Gavran Ivan , Majumdar Rupak , Saha Indranil
Published: September 2017

We present Antlab, an end-to-end system that takes streams of user task requests and executes them using collections of robots. In Antlab, each request is specified declaratively in linear temporal logic extended with quantifiers over robots. The user does not program robots individually, nor know how many robots are available at any time or the precise state of the robots. The Antlab runtime system manages the set of robots, schedules robots to perform tasks, automatically synthesizes robot motion plans from the task specification, and manages the co-ordinated execution of the plan.

We provide a constraint-based formulation for simultaneous task assignment and plan generation for multiple robots working together to satisfy a task specification. In order to scalably handle multiple concurrent tasks, we take a separation of concerns view to plan generation. First, we solve each planning problem in isolation, with an “ideal world” hypothesis that says there are no unspecified dynamic obstacles or adversarial environment actions. Second, to deal with imprecisions of the real world, we implement the plans in receding horizon fashion on top of a standard robot navigation stack. The motion planner dynamically detects environment actions or dynamic obstacles from the environment or from other robots and locally corrects the ideal planned path. It triggers a re-planning step dynamically if the current path deviates from the planned path or if planner assumptions are violated.

We have implemented Antlab as a C++ and Python library on top of robots running on ROS, using SMT-based and AI planning-based implementations for task and path planning. We evaluated Antlab both in simulation as well as on a set of TurtleBot robots. We demonstrate that it can provide a scalable and robust infrastructure for declarative multi-robot programming.
A Structured Methodology for Pattern based Adaptive Scheduling in Embedded Control
Authors: Ghosh Sumana , Dutta Souradeep , Dey Soumyajit , Dasgupta Pallab
Published: September 2017

Software implementation of multiple embedded control loops often share compute resources. The control performance of such implementations have been shown to improve if the sharing of bandwidth between control loops can be dynamically regulated in response to input disturbances. In the absence of a structured methodology for planning such measures, the scheduler may spend too much time in deciding the optimal scheduling pattern. Our work leverages well known results in the domain of network control systems and applies them in the context of bandwidth sharing among controllers. We provide techniques that may be used a priori for computing co-schedulable execution patterns for a given set of control loops such that stability is guaranteed under all possible disturbance scenarios. Additionally, the design of the control loops optimize the average case control performance by adaptive sharing of bandwidth under time varying input disturbances.
Compositional Relational Abstraction for Nonlinear Hybrid Systems
Authors: Chen Xin , Mover Sergio , Sankaranarayanan Sriram
Published: September 2017

We propose techniques to construct abstractions for nonlinear dynamics in terms of relations expressed in linear arithmetic. Such relations are useful for translating the closed loop verification problem of control software with continuous-time, nonlinear plant models into discrete and linear models that can be handled by efficient software verification approaches for discrete-time systems. We construct relations using Taylor model based flowpipe construction and the systematic composition of relational abstractions for smaller components. We focus on developing efficient schemes for the special case of composing abstractions for linear and nonlinear components. We implement our ideas using a relational abstraction system, using the resulting abstraction inside the verification tool NuXMV, which implements numerous SAT/SMT solver-based verification techniques for discrete systems. Finally, we evaluate the application of relational abstractions for verifying properties of time triggered controllers, comparing with the Flow* tool. We conclude that relational abstractions are a promising approach towards nonlinear hybrid system verification, capable of proving properties that are beyond the reach of tools such as Flow*. At the same time, we highlight the need for improvements to existing linear arithmetic SAT/SMT solvers to better support reasoning with large relational abstractions.
An Out-of-Order Load-Store Queue for Spatial Computing
Authors: Josipovic Lana , Brisk Philip , Ienne Paolo
Published: September 2017

The efficiency of spatial computing depends on the ability to achieve maximal parallelism. This necessitates memory interfaces that can correctly handle memory accesses that arrive in arbitrary order while still respecting data dependencies and ensuring appropriate ordering for semantic correctness. However, a typical memory interface for out-of-order processors (i.e., a load-store queue) cannot immediately meet these requirements: a different allocation policy is needed to achieve out-of-order execution in spatial systems that naturally omit the notion of sequential program order, a fundamental piece of information for correct execution. We show a novel and practical way to organize the allocation for an out-of-order load-store queue for spatial computing. The main idea is to dynamically allocate groups of memory accesses (depending on the dynamic behavior of the application), where the access order within the group is statically predetermined (for instance by a high-level synthesis tool). We detail the construction of our load-store queue and demonstrate on a few practical cases its advantages over standard accelerator-memory interfaces.
FlowPaP and FlowReR
Authors: Yan Hao , Jiang Lei , Duan Lide , Lin Wei-Ming , John Eugene
Published: September 2017

Handheld devices, such as smartphones and tablets, currently dominate the semiconductor market. The memory access patterns of CPU and IP cores are dramatically different in a handheld device, making the main memory a critical bottleneck of the entire system. As a result, non-volatile memories, such as spin transfer torque magnetoresistive random-access memory (STT-MRAM), are emerging as a replacement for the existing DRAM-based main memory, achieving a wide variety of advantages. However, replacing DRAM with STT-MRAM also results in new design challenges including read disturbance. A simple read-and-restore scheme preserves data integrity under read disturbance, but incurs significant performance and energy overheads. Consequently, by utilizing unique characteristics of mobile applications, we propose FlowPaP, a flow pattern prediction scheme to dynamically predict the write-to-last-read distances for data frames running on a handheld device. FlowPaP identifies and removes unnecessary memory restores originally required for preventing read disturbance, significantly improving energy efficiency and performance for STT-MRAM-based handheld devices. In addition, we propose a flow-based data retention time reduction scheme named FlowReR to further lower energy consumption of STT-MRAM at the expense of reducing its data retention time. FlowReR imposes a second step that marginally trades off the already improved energy efficiency for performance improvements. Experimental results show that, compared to the original read-and-restore scheme, the application of FlowPaP and FlowReR together can simultaneously improve energy efficiency by 34% and performance by 17% for a set of commonly used Android applications.
Modular Compilation of Hybrid Systems for Emulation and Large Scale Simulation
Authors: Malik Avinash , Roop Partha S. , Andalam Sidharta , Trew Mark , Mendler Michael
Published: September 2017

Hybrid systems combine discrete controllers with adjoining physical processes. While many approaches exist for simulating hybrid systems, there are few approaches for their emulation, especially when the actual physical plant is not available. This paper develops the first formal framework for emulation along with a new compiler that enables large-scale (1000+ components) simulation. We propose a formal model called Synchronous Emulation Automaton (SEA) specifically for modular compilation and parallel execution. SEA combines Linear Time Invariant (LTI) systems with discrete mode switches and has the following semantic differences with Hybrid Automata: ➀ the Ordinary Differential Equations are solved analytically and the solutions are sampled at the Worst-Case Reaction Time of the model and ➁ we develop a new composition semantics, which allows individual SEAs to execute in parallel with each other. The proposed semantics eliminates: ⓐ the need for dynamic numerical solvers, and ⓑ the Zeno-phenomenon by construction. Experimental results show that process models designed using our tool (Piha) give a 3.6 times execution speedup over Simulink®, and upto 26 times speedup on manycore architectures.
User-aware Frame Rate Management in Android Smartphones
Authors: Egilmez Begum , Schuchhardt Matthew , Memik Gokhan , Ayoub Raid , Soundararajan Niranjan , Kishinevsky Michael
Published: September 2017

Frame rate has a direct impact on the energy consumption of smartphones: the higher the frame rate, the higher the power consumption. Hence, reducing display refreshes will reduce the power consumption. However, it is risky to manipulate frame rate drastically as it can deteriorate user satisfaction with the device. In this work, we introduce a screen management system that controls the frame rate on smartphone displays based on a model that detects user dissatisfaction due to display refreshes. This approach is based on understanding when higher frame rates are necessary, and providing lower frame rates —thus, saving power— if the lower rate is predicted not to cause user dissatisfaction. According to the results of our first user survey with 20 participants, individuals show highly varying requirements: while some users require high frame rates for the highest satisfaction, others are equally satisfied with lower frame rates. Based on this observation, we develop a system that predicts user dissatisfaction on the runtime and either increases or decreases the maximum frame rate setting. For user dissatisfaction predictions, we have compared two different approaches: (1) static model, which uses dissatisfaction characteristics of a fixed group of people, and (2) user-specific model, which is learning only from the specific user. Our second set of experiments with 20 participants shows that users report 32% less dissatisfaction and 4% more dissatisfaction than the default Android system with user-specific and static systems, respectively. These experiments also show that, compared to the default scheme, our mechanisms reduce the power consumption of the phone by 7.2% and 1.8% on average with the user-specific and static models, respectively.
A Novel Emulation Model of the Cardiac Conduction System
Authors: Andalam Sidharta , Allen Nathan , Malik Avinash , Roop Partha S. , Trew Mark
Published: September 2017

Models of the cardiac conduction system are usually at two extremes: (1) high fidelity models with excellent precision but lacking a real-time response for emulation (hardware in the loop simulation); or (2) models amenable for emulation, but that do not exhibit appropriate dynamic response, which is necessary for arrhythmia susceptibility. We introduce two abstractions to remedy the situation. The first abstraction is a new cell model, which is a semi-linear hybrid automata. The proposed model is as computationally efficient as current state-of-the-art cell models amenable for emulation. Yet, unlike these models, it is also able to capture the dynamic response of the cardiac cell like the higher-fidelity models. The second abstraction is the use of smooth-tokens to develop a new path model, connecting cells, which is efficient in terms of memory consumption. Moreover, the memory requirements of the path model can be statically bounded and are invariant to the emulation step size. Results show that the proposed semi-linear abstraction for the cell reduces the execution time by up to 44%. Furthermore, the smooth-tokens based path model reduces the memory consumption by 40 times when compared to existing path models. This paves the way for the emulation of complex cardiac conduction systems, using hardware code-generators.
An Automated Security-Aware Approach for Design of Embedded Systems on MPSoC
Authors: Tan Benjamin , Biglari-Abhari Morteza , Salcic Zoran
Published: September 2017

MPSoC-based embedded systems design is becoming increasingly complex. Not only do we need to satisfy multiple design objectives, we increasingly need to address potential security risks. In this work, we propose a security-aware systematic design approach which explores the design space, given a system-level application description, by generating potential architecture configurations of execution platform nodes that are interconnected using a NoC. We then perform automated security analysis to check the generated configurations against designer-specified security constraints. Following the analysis, we use an automated architecture configuration refinement process to generate a list of security additions that are inserted into the initial configuration so that the security constraints are satisfied. By performing this refinement on several candidate configuration options, we can explore the trade-off between resource cost and security. In this paper, we illustrate the proposed approach using a Smart Home Control System application.
A High-Speed Accelerator for Homomorphic Encryption using the Karatsuba Algorithm
Authors: Migliore Vincent , Seguin Cédric , Real Maria Méndez , Lapotre Vianney , Tisserand Arnaud , Fontaine Caroline , Gogniat Guy , Tessier Russell
Published: September 2017

Somewhat Homomorphic Encryption (SHE) schemes can be used to carry out operations on ciphered data. In a cloud computing scenario, personal information can be processed secretly, inferring a high level of confidentiality. The principle limitation of SHE is the size of ciphertext compared to the size of the message. This issue can be addressed by using a batching technique that “packs” several messages into one ciphertext. However, this method leads to important drawbacks in standard implementations. This paper presents a fast hardware/software co-design implementation of an encryption procedure using the Karatsuba algorithm. Our hardware accelerator is 1.5 times faster than the state of the art for 1 encryption and 4 times faster for 4 encryptions.
Using Efficient Path Profiling to Optimize Memory Consumption of On-Chip Debugging for High-Level Synthesis
Authors: Fezzardi Pietro , Lattuada Marco , Ferrandi Fabrizio
Published: September 2017

High-Level Synthesis (HLS) for FPGAs is attracting popularity and is increasingly used to handle complex systems with multiple integrated components. To increase performance and efficiency, HLS flows now adopt several advanced optimization techniques. Aggressive optimizations and system level integration can cause the introduction of bugs that are only observable on-chip. Debugging support for circuits generated with HLS is receiving a considerable attention. Among the data that can be collected on chip for debugging, one of the most important is the state of the Finite State Machines (FSM) controlling the components of the circuit. However, this usually requires a large amount of memory to trace the behavior during the execution. This work proposes an approach that takes advantage of the HLS information and of the structure of the FSM to compress control flow traces and to integrate optimized components for on-chip debugging. The generated checkers analyze the FSM execution on-fly, automatically notifying when a bug is detected, localizing it and providing data about its cause. The traces are compressed using a software profiling technique, called Efficient Path Profiling (EPP), adapted for the debugging of hardware accelerators generated with HLS. With this technique, the size of the memory used to store control flow traces can be reduced up to 2 orders of magnitude, compared to state-of-the-art.
An Inexact Ultra-low Power Bio-signal Processing Architecture With Lightweight Error Recovery
Authors: Basu Soumya , Duch Loris , Braojos RubÉn , Ansaloni Giovanni , Pozzi Laura , Atienza David
Published: September 2017

The energy efficiency of digital architectures is tightly linked to the voltage level (Vdd) at which they operate. Aggressive voltage scaling is therefore mandatory when ultra-low power processing is required. Nonetheless, the lowest admissible Vdd is often bounded by reliability concerns, especially since static and dynamic non-idealities are exacerbated in the near-threshold region, imposing costly guard-bands to guarantee correctness under worst-case conditions. A striking alternative, explored in this paper, waives the requirement for unconditional correctness, undergoing more relaxed constraints. First, after a run-time failure, processing correctly resumes at a later point in time. Second, failures induce a limited Quality-of-Service (QoS) degradation. We focus our investigation on the practical scenario of embedded bio-signal analysis, a domain in which energy efficiency is key, while applications are inherently error-tolerant to a certain degree. Targeting a domain-specific multi-core platform, we present a study of the impact of inexactness on application-visible errors. Then, we introduce a novel methodology to manage them, which requires minimal hardware resources and a negligible energy overhead. Experimental evidence show that, by tolerating 900 errors/hour, the resulting inexact platform can achieve an efficiency increase of up to 24%, with a QoS degradation of less than 3%.
A large-scale study of programming languages and code quality in GitHub
Authors: Ray Baishakhi , Posnett Daryl , Devanbu Premkumar , Filkov Vladimir
Published: September 2017

What is the effect of programming languages on software quality? This question has been a topic of much debate for a very long time. In this study, we gather a very large data set from GitHub (728 projects, 63 million SLOC, 29,000 authors, 1.5 million commits, in 17 languages) in an attempt to shed some empirical light on this question. This reasonably large sample size allows us to use a mixed-methods approach, combining multiple regression modeling with visualization and text analytics, to study the effect of language features such as static versus dynamic typing and allowing versus disallowing type confusion on software quality. By triangulating findings from different methods, and controlling for confounding effects such as team size, project size, and project history, we report that language design does have a significant, but modest effect on software quality. Most notably, it does appear that disallowing type confusion is modestly better than allowing it, and among functional languages, static typing is also somewhat better than dynamic typing. We also find that functional languages are somewhat better than procedural languages. It is worth noting that these modest effects arising from language design are overwhelmingly dominated by the process factors such as project size, team size, and commit size. However, we caution the reader that even these modest effects might quite possibly be due to other, intangible process factors, for example, the preference of certain personality types for functional, static languages that disallow type confusion.
Manipulating word representations, and preparing students for coding jobs?
Authors: Hill Robin K. , Guzdial Mark
Published: September 2017

The
Communications
Web site, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of
Communications
, we'll publish selected posts or excerpts.

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http://cacm.acm.org/blogs/blog-cacm

Robin K. Hill mulls an aspect of natural language processing research, while Mark Guzdial ponders why coding is taught in public schools.
3D-printing human body parts
Authors: Kirkpatrick Keith
Published: September 2017

Bioprinting has generated bones, cartilage, and some muscles; hearts and livers are still years away.
Digital hearing
Authors: Monroe Don
Published: September 2017

Advances in audio processing help separate the conversation from background noise.
Welcome
Authors: Carter Karla
Published: September 2017

Hello! I'm Karla Carter, formerly Vice Chair of SIGCAS, and now, as of July 1, 2017, Chair! Thank you for entrusting three more years of executive committee duties to me. We are lucky to have Mikey Goldweber, from Xavier, remaining on the executive committee as Past Chair, Dee Weikle, from James Madison, continuing as our Editor-in-Chief for the newsletter, and we're welcoming two new executive committee members, Sam Rebelsky, from Grinnell, as the new Vice Chair, and Bob Beck, from Villanova, as Member-at-large. Dee has asked us all to tell a bit about ourselves. Here is my tale.
From a science fiction to reality
Authors: Murata Kiyoshi , Adams Andrew A. , Fukuta Yasunori , Orito Yohko , Arias-Oliva Mario , Pelegrin-Borondo Jorge
Published: September 2017

This study deals with young people's attitudes towards and social acceptance of "cyborg technology" including wearables and insideables (or implantable devices) to enhance human ability in Japan as part of the international research project on cyborg ethics, taking Japanese socio-cultural characteristics surrounding cyborg technology into consideration. Those subjects were investigated through questionnaire surveys of Japanese university students, which were conducted in November and December 2016. The survey results demonstrated respondents' relatively low resistance to using wearables and insideables to improve human physical ability and intellectual power. On the other hand, the morality of insideables was questioned by respondents. In various aspects, statistically significant differences in attitudes towards the technologies between genders were detected.
The false prometheus
Authors: Lahtiranta Janne , Hyrynsalmi Sami , Koskinen Jani
Published: September 2017

In the information society of today, privacy is a premium service and user-related information a commodity. This development has gone unnoticed for many, but for some it contradicts with their common sense and perception of right and wrong. If we look into user agreements, and the effect Fair Information Practice Principles (FIPPs) seem to have, this development is particularly evident. One-on-one agreements such as End User License Agreements (EULAs) between the providers and users have become ubiquitous to most users who simply scroll through the agreement and click 'I agree' without actually understanding or caring what they have accepted.

There are various reasons for this kind of behavior ranging from complete indifference, to inadequate internet and technology literacy, and even to peer pressure as certain applications have become a 'must have' amongst a group of users. This problem is particularly current as personal mobile devices have become important, for some even inseparable, part of our daily lives. These devices, such as smart phones and tablets, have also become
user-centered aggregation points
of information that contain personal, even sensitive information about us, and those around us. At the same time, the number of different applications that have practically unrestrained access to the Internet, is on the rise.

When combined with ignorance and negligence, the risk of placing personal information into wrong hands is a very real one. In the following, we focus on this well-explored challenge from a novel perspective---informed consent---and argue that one way to address this problem is to develop solutions that not only promote personal choice and awareness, but are also context-dependent. In order to provide a practical insight into our primarily conceptual work, we use one of the most popular applications, the Pokémon GO by Niantic Inc., in highlighting some of the encountered privacy-related issues.
Segmenting two-sided markets
Authors: Banerjee Siddhartha , Gollapudi Sreenivas , Kollias Kostas , Munagala Kamesh
Published: September 2017

Recent years have witnessed the rise of many successful e-commerce marketplace platforms like the Amazon marketplace, AirBnB, Uber/Lyft, and Upwork, where a central platform mediates economic transactions between buyers and sellers. A common feature of many of these two-sided marketplaces is that the platform has full control over search and discovery, but prices are determined by the buyers and sellers. We summarize our results from [Banerjee et al. 2017] where, motivated by this application domain, we study the algorithmic aspects of market segmentation via directed discovery in two-sided markets with endogenous prices. We consider a model where an online platform knows each buyer/seller's characteristics, and associated demand/supply elasticities. Moreover, the platform can use discovery mechanisms (search, recommendation, etc.) to control which buyers/sellers are visible to each other. We develop efficient algorithms for throughput (i.e. volume of trade) and welfare maximization with provable guarantees under a variety of assumptions on the demand and supply functions.
Intro to informational substitutes
Authors: Chen Yiling , Waggoner Bo
Published: September 2017

We propose definitions for when signals are "substitutes" and "complements". These give a characterization of equilibria of prediction markets and are relevant to the complexity of information acquisition under constraints.
Improving an Anonymous and Provably Secure Authentication Protocol for a Mobile User
Authors: Moon Jongho , Lee Youngsook , Kim Jiye , Won Dongho
Published: September 2017

Recently many authentication protocols using an extended chaotic map were suggested for a mobile user. Many researchers demonstrated that authentication protocol needs to provide key agreement, mutual authentication, and user anonymity between mobile user and server and resilience to many possible attacks. In this paper, we cautiously analyzed chaotic-map-based authentication scheme and proved that it is still insecure to off-line identity guessing, user and server impersonation, and on-line identity guessing attacks. To address these vulnerabilities, we proposed an improved protocol based on an extended chaotic map and a fuzzy extractor. We proved the security of the proposed protocol using a random oracle and AVISPA (Automated Validation of Internet Security Protocols and Applications) tool. Furthermore, we present an informal security analysis to make sure that the improved protocol is invulnerable to possible attacks. The proposed protocol is also computationally efficient when compared to other previous protocols.
Effect of Salinity Intrusion on Food Crops, Livestock, and Fish Species at Kalapara Coastal Belt in Bangladesh
Authors: Alam Mohammad Zahangeer , Carpenter-Boggs Lynne , Mitra Shishir , Haque Md. Manjurul , Halsey Joan , Rokonuzzaman M. , Saha Badhan , Moniruzzaman M.
Published: September 2017

Salinity has caused significant negative effects on agricultural production. This research is focused on the vulnerabilities of soil and water salinities on crop, fish, and livestock production across the Kalapara coastal belt of Bangladesh. Several parameters were measured as indicators of salinity. The electrical conductivity of water was found to be significant with TDS, F−, Cl−,SO42-, Na+, K+, Ca2+, Mg2+,NO2-, andPO43-. Chloride was found to be identical withSO42-, Na+, K+, Ca2+, Mg2+, Br−, andPO43-. Electrical conductivity, F−, Cl−,SO42-, Na+, K+, and Mg2+were all found to be higher than the recommended values. Similarly, soil conductivity was found significant with TDS, Cl−,SO42-, Na+, F−,NO2-,NO3-, andPO43-. Chloride in soil samples was found statistically identical withSO42-, Na+,NO3-, andPO43-. About 200 ha fodder crops areas are affected each year due to salinity. Ninety-two percent of the areas were found to be salinity affected in the 36 current cropping patterns. Twelve percent of marine fish and 25 percent of shrimp species have disappeared as a result of salinity. The negative impact of soil and water salinity on crops, fish, and livestock has been increasing in this coastal belt.
Relation between Quaternion Fourier Transform and Quaternion Wigner-Ville Distribution Associated with Linear Canonical Transform
Authors: Bahri Mawardi , Saleh Arif Fatimah Muh.
Published: September 2017

The quaternion Wigner-Ville distribution associated with linear canonical transform (QWVD-LCT) is a nontrivial generalization of the quaternion Wigner-Ville distribution to the linear canonical transform (LCT) domain. In the present paper, we establish a fundamental relationship between the QWVD-LCT and the quaternion Fourier transform (QFT). Based on this fact, we provide alternative proof of the well-known properties of the QWVD-LCT such as inversion formula and Moyal formula. We also discuss in detail the relationship among the QWVD-LCT and other generalized transforms. Finally, based on the basic relation between the quaternion ambiguity function associated with the linear canonical transform (QAF-LCT) and the QFT, we present some important properties of the QAF-LCT.
A Novel System for the Quantification of the ADCC Activity of Therapeutic Antibodies
Authors: Lallemand Christophe , Liang Feifei , Staub Flore , Simansour Maud , Vallette Benoit , Huang Lue , Ferrando-Miguel Rosa , Tovey Michael G.
Published: September 2017

Novel ADCC effector cells expressing the V-variant or F-variant of FcγRIIIa (CD16a) and firefly luciferase under the control of a chimeric promoter incorporating recognition sequences for the principal transcription factors involved in FcγRIIIa signal transduction, together with novel target cells overexpressing a constant high level of the specific antigen recognized by rituximab, trastuzumab, cetuximab, infliximab, adalimumab, or etanercept, confer improved sensitivity, specificity, and dynamic range in an ADCC assay relative to effector cells expressing a NFAT-regulated reporter gene and wild-type target cells. The effector cells also contain a normalization gene rendering ADCC assays independent of cell number or serum matrix effects. The novel effector and target cells in a frozen thaw-and-use format exhibit low vial-to-vial and lot-to-lot variation in their performance characteristics reflected by CVs of 10% or less. Homologous control target cells in which the specific target gene has been invalidated by genome editing providing an ideal control and a means of correcting for nonspecific effects were observed with certain samples of human serum. The novel effector cells and target cells expressing noncleavable membrane-bound TNFαhave been used to quantify ADCC activity in serum from patients with Crohn’s disease treated with infliximab and to relate ADCC activity to drug levels.