Containing the Nanometer "Pandora-Box": Cross-Layer Design Techniques for Variation Aware Low Power Systems

The demand for richer multimedia services, multifunctional portable devices and high data rates can only been visioned due to the improvement in semiconductor technology. Unfortunately, sub-90 nm process nodes uncover the nanometer Pandora-box exposing the barriers of technology scaling-parameter variations, that threaten the correct operation of circuits, and increased energy consumption, that limits the operational lifetime of today's systems. The contradictory design requirements for low-power and system robustness, is one of the most challenging design problems of today. The design efforts are further complicated due to the heterogeneous types of designs ( logic, memory, mixed-signal) that are included in today's complex systems and are characterized by different design requirements. This paper presents an overview of techniques at various levels of design abstraction that lead to low power and variation aware logic, memory and mixed-signal circuits and can potentially assist in meeting the strict power budgets and yield/quality requirements of future systems.

Logic and Memory Design Based on Unequal Error Protection for Voltage-scalable, Robust and Adaptive DSP Systems

In this paper, we propose a system level design approach considering voltage over-scaling (VOS) that achieves error resiliency using unequal error protection of different computation elements, while incurring minor quality degradation. Depending on user specifications and severity of process variations/channel noise, the degree of VOS in each block of the system is adaptively tuned to ensure minimum system power while providing "just-the-right" amount of quality and robustness. This is achieved, by taking into consideration block level interactions and ensuring that under any change of operating conditions, only the "less-crucial" computations, that contribute less to block/system output quality, are affected. The proposed approach applies unequal error protection to various blocks of a system-logic and memory-and spans multiple layers of design hierarchy-algorithm, architecture and circuit. The design methodology when applied to a multimedia subsystem shows large power benefits ( up to 69% improvement in power consumption) at reasonable image quality while tolerating errors introduced due to VOS, process variations, and channel noise.

An Event Driven Fusion Approach for Enjoyment Recognition in Real-time

Social signals and interpretation of carried information is of high importance in Human Computer Interaction. Often used for affect recognition, the cues within these signals are displayed in various modalities. Fusion of multi-modal signals is a natural and interesting way to improve automatic classification of emotions transported in social signals. Throughout most present studies, uni-modal affect recognition as well as multi-modal fusion, decisions are forced for fixed annotation segments across all modalities. In this paper, we investigate the less prevalent approach of event driven fusion, which indirectly accumulates asynchronous events in all modalities for final predictions. We present a fusion approach, handling short-timed events in a vector space, which is of special interest for real-time applications. We compare results of segmentation based uni-modal classification and fusion schemes to the event driven fusion approach. The evaluation is carried out via detection of enjoyment-episodes within the audiovisual Belfast Story-Telling Corpus.

Can(Plan)+: Extending the Operational Semantics of the BDI Architecture to deal with Uncertain Information

The BDI architecture, where agents are modelled based on their beliefs, desires and intentions, provides a practical approach to develop large scale systems. However, it is not well suited to model complex Supervisory Control And Data Acquisition (SCADA) systems pervaded by uncertainty. In this paper we address this issue by extending the operational semantics of Can(Plan) into Can(Plan)+. We start by modelling the beliefs of an agent as a set of epistemic states where each state, possibly using a different representation, models part of the agent's beliefs. These epistemic states are stratified to make them commensurable and to reason about the uncertain beliefs of the agent. The syntax and semantics of a BDI agent are extended accordingly and we identify fragments with computationally efficient semantics. Finally, we examine how primitive actions are affected by uncertainty and we define an appropriate form of lookahead planning.

Musicologist-driven writer identification in early music manuscripts

Recent renewed interest in computational writer identification has resulted in an increased number of publications. In relation to historical musicology its application has so far been limited. One of the obstacles seems to be that the clarity of the images from the scans available for computational analysis is often not sufficient. In this paper, the use of the Hinge feature is proposed to avoid segmentation and staff-line removal for effective feature extraction from low quality scans. The use of an auto encoder in Hinge feature space is suggested as an alternative to staff-line removal by image processing, and their performance is compared. The result of the experiment shows an accuracy of 87 % for the dataset containing 84 writers’ samples, and superiority of our segmentation and staff-line removal free approach. Practical analysis on Bach’s autograph manuscript of the Well-Tempered Clavier II (Additional MS. 35021 in the British Library, London) is also presented and the extensive applicability of our approach is demonstrated.

The SEMAINE corpus of emotionally coloured character interactions

We have recorded a new corpus of emotionally coloured conversations. Users were recorded while holding conversations with an operator who adopts in sequence four roles designed to evoke emotional reactions. The operator and the user are seated in separate rooms; they see each other through teleprompter screens, and hear each other through speakers. To allow high quality recording, they are recorded by five high-resolution, high framerate cameras, and by four microphones. All sensor information is recorded synchronously, with an accuracy of 25 μs. In total, we have recorded 20 participants, for a total of 100 character conversational and 50 non-conversational recordings of approximately 5 minutes each. All recorded conversations have been fully transcribed and annotated for five affective dimensions and partially annotated for 27 other dimensions. The corpus has been made available to the scientific community through a web-accessible database.

'The Blazing Torch': New Light on English Balladry as a Multi-Media Matrix

This paper investigates the inter-twining histories of two highly successful broadside ballads during the seventeenth century. Neither has been systematically studied before. A set of cultural relationships is opened for consideration by these songs: first, between the two ballads, which are different in several ways but set to the same tune; second, between the selected songs and other ballads on comparable themes; and third, between different editions of the two featured songs. In discussing each of these relationships, attention is paid not only to the texts but to the pictures and the tunes that helped to bring balladry to life for early-modern consumers. It is argued that balladry should be studied as an interconnected web and that individual publications drew significance from the manner in which they associated themselves – through shared pictures, tunes and narratives – with other examples of the genre.

Vision and deaf awareness training is it app.ropriate?

Title
Visual and deaf awareness training is it app.ropriate
Purpose
Some of our most vulnerable patients have a sensory deficit. An app which focused on patients with a vision and/or hearing loss was developed for healthcare students. The intent was to embed the core values necessary for students to provide appropriate care for patients with a sensory deficit.
Setting
Queen’s University Belfast, School of Nursing and Midwifery.
Methods
Stage 1
A review of current sensory awareness training in the United Kingdom
Stage 2
Application for funding
Stage 3
Development of a teaching tool template with the essential aspects required for sensory awareness training
Stage 4
Collaboration with others: Royal National Institute for the Blind, Action on Hearing Loss, Computer technician.
Stage 5
Production and transfer of multimedia outputs onto a software application system.
Stage 6
App Piloted with a sample of lecturers (n=5), undergraduate nursing students (n=20), service users (n=5)
Stage 7
Editing
Stage 8
App made available to all undergraduate nursing students
Stage 9
App evaluation (n=300)



Results
Overall nursing students positively evaluated the app, 100% of students rated the app between good and excellent. Qualitative evidence from service users and practice partnerships was extremely positive:
"At last I feel listened too in respect to my hearing loss and empowered. I don't feel like I am complaining I am actually helping to create something which should benefit staff and all of us with a hearing or vision loss". Patient
“Very insightful into the lives of those with a disability will be so useful in practice as an aid to jog my memory". 1st year nursing student
Conclusion
It is hoped that further evaluation and implementation of the app will show an improved quality to the care delivered to those with a sensory deficit. We believe that by working in partnership with service users we have helped to create an innovative tool that benefits both staff and patients.
Financial disclosure Yes
Funding of £2700 was awarded in 2014 through the Martha McMenamin Memorial Northern Ireland Scholarship.

Partial Palmprint Matching Using Invariant Local Minutiae Descriptors

In forensic investigations, it is common for forensic investigators to obtain a photograph of evidence left at the scene of crimes to aid them catch the culprit(s). Although, fingerprints are the most popular evidence that can be used, scene of crime officers claim that more than 30% of the evidence recovered from crime scenes originate from palms. Usually, palmprints evidence left at crime scenes are partial since very rarely full palmprints are obtained. In particular, partial palmprints do not exhibit a structured shape and often do not contain a reference point that can be used for their alignment to achieve efficient matching. This makes conventional matching methods based on alignment and minutiae pairing, as used in fingerprint recognition, to fail in partial palmprint recognition problems. In this paper a new partial-to-full palmprint recognition based on invariant minutiae descriptors is proposed where the partial palmprint’s minutiae are extracted and considered as the distinctive and discriminating features for each palmprint image. This is achieved by assigning to each minutiae a feature descriptor formed using the values of all the orientation histograms of the minutiae at hand. This allows for the descriptors to be rotation invariant and as such do not require any image alignment at the matching stage. The results obtained show that the proposed technique yields a recognition rate of 99.2%. The solution does give a high confidence to the judicial jury in their deliberations and decision.

Operators for Similarity Search: Semantics, Techniques and Usage Scenarios

This book provides a comprehensive tutorial on similarity operators. The authors systematically survey the set of similarity operators, primarily focusing on their semantics, while also touching upon mechanisms for processing them effectively.

The book starts off by providing introductory material on similarity search systems, highlighting the central role of similarity operators in such systems. This is followed by a systematic categorized overview of the variety of similarity operators that have been proposed in literature over the last two decades, including advanced operators such as RkNN, Reverse k-Ranks, Skyline k-Groups and K-N-Match. Since indexing is a core technology in the practical implementation of similarity operators, various indexing mechanisms are summarized. Finally, current research challenges are outlined, so as to enable interested readers to identify potential directions for future investigations.

In summary, this book offers a comprehensive overview of the field of similarity search operators, allowing readers to understand the area of similarity operators as it stands today, and in addition providing them with the background needed to understand recent novel approaches.

Semantics for possibilistic answer set programs: uncertain rules versus rules with uncertain conclusions

Although Answer Set Programming (ASP) is a powerful framework for declarative problem solving, it cannot in an intuitive way handle situations in which some rules are uncertain, or in which it is more important to satisfy some constraints than others. Possibilistic ASP (PASP) is a natural extension of ASP in which certainty weights are associated with each rule. In this paper we contrast two different views on interpreting the weights attached to rules. Under the first view, weights reflect the certainty with which we can conclude the head of a rule when its body is satisfied. Under the second view, weights reflect the certainty that a given rule restricts the considered epistemic states of an agent in a valid way, i.e. it is the certainty that the rule itself is correct. The first view gives rise to a set of weighted answer sets, whereas the second view gives rise to a weighted set of classical answer sets.

Characterizing and Extending Answer Set Semantics using Possibility Theory

Answer Set Programming (ASP) is a popular framework for modelling combinatorial problems. However, ASP cannot be used easily for reasoning about uncertain information. Possibilistic ASP (PASP) is an extension of ASP that combines possibilistic logic and ASP. In PASP a weight is associated with each rule, whereas this weight is interpreted as the certainty with which the conclusion can be established when the body is known to hold. As such, it allows us to model and reason about uncertain information in an intuitive way. In this paper we present new semantics for PASP in which rules are interpreted as constraints on possibility distributions. Special models of these constraints are then identified as possibilistic answer sets. In addition, since ASP is a special case of PASP in which all the rules are entirely certain, we obtain a new characterization of ASP in terms of constraints on possibility distributions. This allows us to uncover a new form of disjunction, called weak disjunction, that has not been previously considered in the literature. In addition to introducing and motivating the semantics of weak disjunction, we also pinpoint its computational complexity. In particular, while the complexity of most reasoning tasks coincides with standard disjunctive ASP, we find that brave reasoning for programs with weak disjunctions is easier.

Memory-centric VDF Graph Transformations for Practical FPGA Implementation

Realising memory intensive applications such as image and video processing on FPGA requires creation of complex, multi-level memory hierarchies to achieve real-time performance; however commerical High Level Synthesis tools are unable to automatically derive such structures and hence are unable to meet the demanding bandwidth and capacity constraints of these applications. Current approaches to solving this problem can only derive either single-level memory structures or very deep, highly inefficient hierarchies, leading in either case to one or more of high implementation cost and low performance. This paper presents an enhancement to an existing MC-HLS synthesis approach which solves this problem; it exploits and eliminates data duplication at multiple levels levels of the generated hierarchy, leading to a reduction in the number of levels and ultimately higher performance, lower cost implementations. When applied to synthesis of C-based Motion Estimation, Matrix Multiplication and Sobel Edge Detection applications, this enables reductions in Block RAM and Look Up Table (LUT) cost of up to 25%, whilst simultaneously increasing throughput.