Query: Honeypot Frameworks and Their Applications: A New Framework

Relevant passages:
Peer-to-Peer Botnets: Overview and Case Study <=SEP=> Botnets have recently been identified as one of the most important threats to the security of the Internet. Traditionally, botnets organize themselves in an hierarchical manner with a central command and control location. This location can be statically defined in the bot, or it can be dynamically defined based on a directory server. Presently, the centralized characteristic of botnets is us eful to security professionals because it offers a central point of failure for the botnet. In the near future, we believe attackers will move to more resilient architectures. In particular, one class of botnet structure that has entered initial stages of development is peer-to-peer based architectures. In this paper, we present an overview of peer-to-peer botnets. We also present a case study of a Kademlia-based Trojan.Peacomm bot.

Gatekeeper: Monitoring Auto-Start Extensibility Points (ASEPs) for Spyware Management <=SEP=> Spyware is a rapidly spreading problem for PC users causing significant impact on system stability and privacy concerns. It attaches to extensibility points in the system to ensure the spyware will be instantiated when the system starts. Users may willingly install free versions of software containing spyware as an alternative to paying for it. Traditional anti-virus techniques are less effective in this scenario because they lack the context to decide if the spyware should be removed. In this paper, we introduce Auto-Start Extensibility Points (ASEPs) as the key concept for modeling the spyware problem. By monitoring and grouping ‘‘hooking’’ operations made to the ASEPs, our Gatekeeper solution complements the traditional signature-based approach and provides a comprehensive framework for spyware management. We present ASEP hooking statistics for 120 real-world spyware programs. We also describe several techniques for discovering new ASEPs to further enhance the effectiveness of our solution.

Detecting stealth software with Strider GhostBuster <=SEP=> Stealth malware programs that silently infect enterprise and consumer machines are becoming a major threat to the future of the Internet. Resource hiding is a powerful stealth technique commonly used by malware to evade detection by computer users and anti-malware scanners. In this paper, we focus on a subclass of malware, termed "ghostware", which hide files, configuration settings, processes, and loaded modules from the operating system's query and enumeration application programming interfaces (APIs). Instead of targeting individual stealth implementations, we describe a systematic framework for detecting multiple types of hidden resources by leveraging the hiding behavior as a detection mechanism. Specifically, we adopt a cross-view diff-based approach to ghostware detection by comparing a high-level infected scan with a low-level clean scan and alternatively comparing an inside-the-box infected scan with an outside-the-box clean scan. We describe the design and implementation of the Strider GhostBuster tool and demonstrate its efficiency and effectiveness in detecting resources hidden by real-world malware such as rootkits, Trojans, and key-loggers.

A multifaceted approach to understanding the botnet phenomenon <=SEP=> The academic community has long acknowledged the existence of malicious botnets, however to date, very little is known about the behavior of these distributed computing platforms. To the best of our knowledge, botnet behavior has never been methodically studied, botnet prevalence on the Internet is mostly a mystery, and the botnet life cycle has yet to be modeled. Uncertainty abounds. In this paper, we attempt to clear the fog surrounding botnets by constructing a multifaceted and distributed measurement infrastructure. Throughout a period of more than three months, we used this infrastructure to track 192 unique IRC botnets of size ranging from a few hundred to several thousand infected end-hosts. Our results show that botnets represent a major contributor to unwanted Internet traffic - 27% of all malicious connection attempts observed from our distributed darknet can be directly attributed to botnet-related spreading activity. Furthermore, we discovered evidence of botnet infections in 11% of the 800,000 DNS domains we examined, indicating a high diversity among botnet victims. Taken as a whole, these results not only highlight the prominence of botnets, but also provide deep insights that may facilitate further research to curtail this phenomenon.

Modeling Botnet Propagation Using Time Zones <=SEP=> Time zones play an important and unexplored role in malware epidemics. To understand how time and location affect malware spread dynamics, we studied botnets, or large coordinated collections of victim machines (zombies) controlled by attackers. Over a six month period we observed dozens of botnets representing millions of victims. We noted diurnal properties in botnet activity, which we suspect occurs because victims turn their computers off at night. Through binary analysis, we also confirmed that some botnets demonstrated a bias in infecting regional populations. Clearly, computers that are offline are not infectious, and any regional bias in infections will affect the overall growth of the botnet. We therefore created a diurnal propagation model. The model uses diurnal shaping functions to capture regional variations in online vulnerable populations. The diurnal model also lets one compare propagation rates for different botnets, and prioritize response. Because of variations in release times and diurnal shaping functions particular to an infection, botnets released later in time may actually surpass other botnets that have an advanced start. Since response times for malware outbreaks is now measured in hours, being able to predict short-term propagation dynamics lets us allocate resources more intelligently. We used empirical data from botnets to evaluate the analytical model.

A survey of automated material handling systems in 300-mm SemiconductorFabs <=SEP=> The fast-paced developments and technological breakthroughs in the semiconductor manufacturing industry elevates the importance of optimum utilization of resources. The newer 300-mm wafers fabs place a high level of emphasis on increasing yield and reducing cycle times. Automated material handling systems are importanttools that help us achieve these objectives. In addition, due to the increased weight and size of 300-mm wafers, an automated material handling system isa must for a 300-mm manufacturing facility. This paper discusses various approaches for automated materials handling in semiconductor manufacturing industries.

Structural description and classification of signature images <=SEP=> -This, paper introduces a new method for describing signature images. The description involves features of the signatures and relations among its parts organized in a hierarchical structure. The description is used to classify the signatures and globally analyse their structure. Description Segmentation Feature extraction Classification Signature analysis I. I N T R O D U C T I O N Although a lot of research on signatures has been reported in the past 20 years (t) they are mainly confined to verification in which a set of goal oriented features is used to give the decision about the authenticity of the claimed signature. However, it is interesting to be able to access a signature database using a compact and meaningful description derived from its pictorial content. Constructing such a signature database, requires an automatic description of signature images. Researches on signature description are very limited and appeared implicitly in verification researches. In on-line systems, Lamarche and Plamondon (z) reconsidered the theoretical model of the handwriting process introduced by Verdenberg and Koster <3) to describe the pen tip speed and orientation and used this description for feature extraction. In off-line systems, Nagel and Rosenfeld (̀ ~ modified the model introduced by Eden (~) for describing upright handwriting by adding the slant parameter and used the parameters of the modified model as a basis for choosing their features for verification, and Brocklehurst (6) used data reduction techniques to encode the signatures into a list of 7 features (called encoded description) and used them for verification. In all cases, neither a structural description of the signature as a 2-D image nor a conceptualization of the features was proposed. In this paper, we introduce a method for signature description and a reliable approach that can describe digitized signature images by this method. The description uses a hierarchical approach, i.e. the signature is at the top level and each lower level gives more detail about the higher one. Since the range of the natural variation of signature writing will change with time as found by Kapoor <~ and Evett, (s) and the ratios of the writing parameters for different samples of the same individual's writing remain essentially constant over a wide range of the writing surface and space available, ('~ features and relations of o u r description are extracted in a relative way (e.g. the length is measured by its ratio to the width, and so on) to attempt to make it insensitive to the natural variation in the genuine signatures. The signature is described using a global description suitable for purposes like classifying the signature data and studying its nature, and a local description convenient for applications which require more detailed information about the signature like signature analysis or similarity oriented retrieval. The global description is represented by a character string, and the local description is represented by a tree structure. In Section 2, the general approach for describing signature images is introduced, and Section 3 introduces the practical method of the description. Section 4 presents the application of the global description to classifying and analysing the signature data, and finally, Section 5 contains the closing remarks. 2. SIGNATURE DESCRIPTION Signatures are a special case of handwriting in which special characters and flourishes are available, and the ratio between the middle zone width and the letter heights is sometimes abnormal. In many cases, the signature is not readable even by a human. Therefore, we deal with the signature as an image that has the principal zones (upper, middle and lower zones) of the handwriting, not as strokes, letters and words. As indicated by Rosenfeld, (9) description of a picture involves properties of the picture or its parts and relationships among them. Our description involves features like slant, and relations among signature properties like the comparison between the widths of the zones. The description is not reversible, that is, the signature cannot be reconstructed from its description. However, the description involves sufficient information to characterize the signature and its parts. Features and relations are extracted quantitatively, and then mapped into a conceptual

Analysis of the wrench-closure workspace of planar parallel cable-driven mechanisms <=SEP=> The mobile platform of a parallel cable-driven mechanism is connected in parallel to a base by lightweight links, such as cables. Since the cables can only work in tension, the set of poses of the mobile platform for which the cables can balance any external wrench, i.e., for which the platform of the mechanism is fully constrained, is often limited or even nonexistent. Thus, the study and determination of this set of poses, called the wrench-closure workspace (WCW), is an important issue for parallel cable-driven mechanisms. In this paper, the case of planar parallel cable-driven mechanisms is addressed. Theorems that characterize the poses of the WCW are proposed. Then, these theorems are used to disclose the parts of the reachable workspace which belong to the WCW. Finally, an efficient algorithm that determines the constant-orientation cross-sections of these parts is introduced.

Additive lattice kirigami <=SEP=> Kirigami uses bending, folding, cutting, and pasting to create complex three-dimensional (3D) structures from a flat sheet. In the case of lattice kirigami, this cutting and rejoining introduces defects into an underlying 2D lattice in the form of points of nonzero Gaussian curvature. A set of simple rules was previously used to generate a wide variety of stepped structures; we now pare back these rules to their minimum. This allows us to describe a set of techniques that unify a wide variety of cut-and-paste actions under the rubric of lattice kirigami, including adding new material and rejoining material across arbitrary cuts in the sheet. We also explore the use of more complex lattices and the different structures that consequently arise. Regardless of the choice of lattice, creating complex structures may require multiple overlapping kirigami cuts, where subsequent cuts are not performed on a locally flat lattice. Our additive kirigami method describes such cuts, providing a simple methodology and a set of techniques to build a huge variety of complex 3D shapes.

Confidence intervals in within-subject designs: A simpler solution to Loftus and Masson's method <=SEP=> Within-subject ANOVAs are a powerful tool to analyze data because the variance associated to differences between the participants is removed from the analysis. Hence, small differences, when present for most of the participants, can be significant even when the participants are very different from one another. Yet, graphs showing standard error or confidence interval bars are misleading since these bars include the between-subject variability. Loftus and Masson (1994) noticed this fact and proposed an alternate method to compute the error bars. However, i) their approach requires that the ANOVA be performed first, which is paradoxical since a graph is an aid to decide whether to perform analyses or not; ii) their method provides a single error bar for all the conditions, masking information such as the heterogeneity of variances across conditions; iii) the method proposed is difficult to implement in commonly-used graphing software. Here we propose a simple alternative and sow how it can be implemented in SPSS.

Decision Support Systems (DSS) in Construction Tendering Processes <=SEP=> The successful execution of a construction project is heavily impacted by making the right decision during tendering processes. Managing tender procedures is very complex and uncertain involving coordination of many tasks and individuals with different priorities and objectives. Bias and inconsistent decision are inevitable if the decision-making process is totally depends on intuition, subjective judgement or emotion. In making transparent decision and healthy competition tendering, there exists a need for flexible guidance tool for decision support. Aim of this paper is to give a review on current practices of Decision Support Systems (DSS) technology in construction tendering processes. Current practices of general tendering processes as applied to the most countries in different regions such as United States, Europe, Middle East and Asia are comprehensively discussed. Applications of Web-based tendering processes is also summarised in terms of its properties. Besides that, a summary of Decision Support System (DSS) components is included in the next section. Furthermore, prior researches on implementation of DSS approaches in tendering processes are discussed in details. Current issues arise from both of paper-based and Web-based tendering processes are outlined. Finally, conclusion is included at the end of this paper.

An empirical resource for discovering cognitive principles of discourse organisation: the ANNODIS corpus <=SEP=> This paper describes the ANNODIS resource, a discourse-level annotated corpus for French. The corpus combines two perspectives on discourse: a bottom-up approach and a top-down approach. The bottom-up view incrementally builds a structure from elementary discourse units, while the top-down view focuses on the selective annotation of multi-level discourse structures. The corpus is composed of texts that are diversified with respect to genre, length and type of discursive organisation. The methodology followed here involves an iterative design of annotation guidelines in order to reach satisfactory inter-annotator agreement levels. This allows us to raise a few issues relevant for the comparison of such complex objects as discourse structures. The corpus also serves as a source of empirical evidence for discourse theories. We present here two first analyses taking advantage of this new annotated corpus, one that tested hypotheses on constraints governing discourse structure, and another that studied the variations in composition and signalling of multi-level discourse structures.

The slot-coupled hemispherical dielectric resonator antenna with a parasitic patch: applications to the circularly polarized antenna and wide-band antenna <=SEP=> The aperture-coupled hemispherical dielectric resonator antenna (DRA) with a parasitic patch is studied rigorously. Using the Green's function approach, integral equations for the unknown patch and slot currents are formulated and solved using the method of moments. The theory is utilized to design a circularly polarized (CP) DRA and a wide-band linearly polarized (LP) DRA. In the former, the CP frequency and axial ratio (AR) can easily be controlled by the patch location and patch size, respectively, with the impedance matched by varying the slot length and microstrip stub length. It is important that the AR will not be affected when the input impedance is tuned, and the CP design is therefore greatly facilitated. For the wide-band LP antenna, a maximum bandwidth of 22% can be obtained, which is much wider than the previous bandwidth of 7.5% with no parasitic patches. Finally, the frequency-tuning characteristics of the proposed antenna are discussed. Since the parasitic patch can be applied to any DRAs, the method will find applications in practical DRA designs.

Measuring Urban Social Diversity Using Interconnected Geo-Social Networks <=SEP=> Large metropolitan cities bring together diverse individuals, creating opportunities for cultural and intellectual exchanges, which can ultimately lead to social and economic enrichment. In this work, we present a novel network perspective on the interconnected nature of people and places, allowing us to capture the social diversity of urban locations through the social network and mobility patterns of their visitors. We use a dataset of approximately 37K users and 42K venues in London to build a network of Foursquare places and the parallel Twitter social network of visitors through check-ins. We define four metrics of the social diversity of places which relate to their social brokerage role, their entropy, the homogeneity of their visitors and the amount of serendipitous encounters they are able to induce. This allows us to distinguish between places that bring together strangers versus those which tend to bring together friends, as well as places that attract diverse individuals as opposed to those which attract regulars. We correlate these properties with wellbeing indicators for London neighbourhoods and discover signals of gentrification in deprived areas with high entropy and brokerage, where an influx of more affluent and diverse visitors points to an overall improvement of their rank according to the UK Index of Multiple Deprivation for the area over the five-year census period. Our analysis sheds light on the relationship between the prosperity of people and places, distinguishing between different categories and urban geographies of consequence to the development of urban policy and the next generation of socially-aware location-based applications.

SLING: A framework for frame semantic parsing <=SEP=> We describe SLING, a framework for parsing natural language into semantic frames. SLING supports general transition-based, neural-network parsing with bidirectional LSTM input encoding and a Transition Based Recurrent Unit (TBRU) for output decoding. The parsing model is trained end-to-end using only the text tokens as input. The transition system has been designed to output frame graphs directly without any intervening symbolic representation. The SLING framework includes an efficient and scalable frame store implementation as well as a neural network JIT compiler for fast inference during parsing. SLING is implemented in C++ and it is available for download on GitHub.

Modeling the statistical time and angle of arrival characteristics of an indoor multipath channel <=SEP=> Most previously proposed statistical models for the indoor multipath channel include only time of arrival characteristics. However, in order to use statistical models in simulating or analyzing the performance of systems employing spatial diversity combining, information about angle of arrival statistics is also required. Ideally, it would be desirable to characterize the full spare-time nature of the channel. In this paper, a system is described that was used to collect simultaneous time and angle of arrival data at 7 GHz. Data processing methods are outlined, and results obtained from data taken in two different buildings are presented. Based on the results, a model is proposed that employs the clustered "double Poisson" time-of-arrival model proposed by Saleh and Valenzuela (1987). The observed angular distribution is also clustered with uniformly distributed clusters and arrivals within clusters that have a Laplacian distribution.

Context-Sensitive Flow Graph and Projective Single Assignment Form for Resolving Context-Dependency of Binary Code <=SEP=> Program analysis on binary code is considered as difficult because one has to resolve destinations of indirect jumps. However, there is another difficulty of context-dependency that matters when one processes binary programs that are not compiler generated. In this paper, we propose a novel approach for tackling these difficulties and describe a way to reconstruct a control flow from a binary program with no extra assumptions than the operational meaning of machine instructions.

Human-in-the-Loop Challenges for Entity Matching: A Midterm Report <=SEP=> Entity matching (EM) has been a long-standing challenge in data management. In the past few years we have started two major projects on EM (Magellan and Corleone/Falcon). These projects have raised many human-in-the-loop (HIL) challenges. In this paper we discuss these challenges. In particular, we show how these challenges forced us to revise our solution architecture, from a typical RDBMS-style architecture to a very human-centric one, in which human users are first-class objects driving the EM process, using tools at pain-point places. We discuss how such solution architectures can be viewed as combining "tools in the loop" with "human in the loop". Finally, we discuss lessons learned which can potentially be applied to other problem settings. We also hope that more researchers will investigate EM, as it can be a rich "playground" for HIL research.

ReticularSpaces: activity-based computing support for physically distributed and collaborative smart spaces <=SEP=> Smart spaces research focuses on technology for multiple displays and devices for collocated participants. In most approaches, however, users have to cope with heterogeneous interfaces and information organization, as well as a lack of support for collaboration with mobile and remote users outside the smart space. In this paper, we present ReticularSpaces; a multi-display smart space system built on the principles of activity-based computing. The focus of ReticularSpaces is to support: (i) unified interaction with applications and documents through ReticularUI, a novel distributed user interfaces design; (ii) management of the complexity of tasks between users and displays; (iii) mobile users in a local, remote or 'nomadic' settings; and (iv) collaboration among local and remote users. We describe the motivation, design, and architecture of ReticularSpaces, and report from a preliminary feasibility study. The study shows that participants found ReticularSpaces useful and effective, but at the same time reveals new areas for research on smart environments.

Advanced control strategies for balancing LED usage of AC LED driver <=SEP=> This paper presents two enhanced methods to balance LEDs energy usage in the AC LED Driver. While conventional AC LED driver has energy consumption imbalance, the proposed control methods provide equally distributed energy usage. First method is to apply the appropriate firing voltage that is the threshold voltage for equalizing energy consumption of LEDs. This method improves balancing energy consumption within a rectified line cycle. The other method is to change the order of LEDs turning on sequence by every two rectified line cycle. These two approaches are compared with mathematical analysis in terms of the energy consumption of each LED. A prototype driver with three 12 W-LED strings is built. The proposed method 1 and method 2 achieve 0.0030 J and 0.0033 J standard deviation of energy consumption, respectively, compared to the 0.0070 J deviation for the conventional approach.

Deep convolutional neural network based large-scale oil palm tree detection for high-resolution remote sensing images <=SEP=> This paper proposed a deep convolutional neural network (DCNN) based framework for large-scale oil palm tree detection using high-resolution remote sensing images in Malaysia. Different from the previous palm tree or tree crown detection studies, the palm trees in our study area are very crowded and their crowns often overlap. Moreover, there are various land cover types in our study area, e.g. impervious, bare land, and other vegetation, etc. The main steps of our proposed method include large-scale and multi-class sample collection, AlexNet-based DCNN training and optimization, sliding window-based label prediction, and post-processing. Compared with the manually interpreted ground truth, our proposed method achieves detection accuracies of 92%–97% in our study area, which are greatly higher than the accuracies obtained from another two detection methods used in this paper.

Magnet design based on transient behavior of an IPMSM in event of malfunction <=SEP=> This paper deals with the approach of analyzing the magnet design based on transient behavior of an IPMSM during switching processes in the event of malfunction for automotive applications. Depending on the maximal current increase during the transient process the needed percentage of Dysprosium for the magnet design is conducted. Switching off strategy is introduced for both Voltage-Source- and Current-Source-Inverter for automotive application. Both inverters are compared concerning the transient current increase and respectively the Dy-content for the magnet design.

Multiple asynchronous stimulus- and task-dependent hierarchies (STDH) within the visual brain's parallel processing systems. <=SEP=> Results from a variety of sources, some many years old, lead ineluctably to a re-appraisal of the twin strategies of hierarchical and parallel processing used by the brain to construct an image of the visual world. Contrary to common supposition, there are at least three 'feed-forward' anatomical hierarchies that reach the primary visual cortex (V1) and the specialized visual areas outside it, in parallel. These anatomical hierarchies do not conform to the temporal order with which visual signals reach the specialized visual areas through V1. Furthermore, neither the anatomical hierarchies nor the temporal order of activation through V1 predict the perceptual hierarchies. The latter shows that we see (and become aware of) different visual attributes at different times, with colour leading form (orientation) and directional visual motion, even though signals from fast-moving, high-contrast stimuli are among the earliest to reach the visual cortex (of area V5). Parallel processing, on the other hand, is much more ubiquitous than commonly supposed but is subject to a barely noticed but fundamental aspect of brain operations, namely that different parallel systems operate asynchronously with respect to each other and reach perceptual endpoints at different times. This re-assessment leads to the conclusion that the visual brain is constituted of multiple, parallel and asynchronously operating task- and stimulus-dependent hierarchies (STDH); which of these parallel anatomical hierarchies have temporal and perceptual precedence at any given moment is stimulus and task related, and dependent on the visual brain's ability to undertake multiple operations asynchronously.

From Theory to Experimental Evaluation: Resource Management in Software-Defined Vehicular Networks <=SEP=> Managing resources in dynamic vehicular environments is a tough task, which is becoming more challenging with the increased number of access technologies today available in connected cars (e.g., IEEE 802.11, LTE), in the variety of applications provided on the road (e.g., safety, traffic efficiency, and infotainment), in the amount of driving awareness/coordination required (e.g., local, context, and cooperative awareness), and in the level of automation toward zero-accident driving (e.g., platooning and autonomous driving). The open programmability and logically centralized control features of the software–defined networking (SDN) paradigm offer an attractive means to manage communication and networking resources in the vehicular environment and promise improved performance. In this paper, we enumerate the potentials of software-defined vehicular networks, analyze the need to rethink the traditional SDN approach from theoretical and practical standpoints when applied in this application context, and present an emulation approach based on the proposed node car architecture in Mininet-WiFi to showcase the applicability and some expected benefits of SDN in a selected use case scenario.

Violent and nonviolent video games differentially affect physical aggression for individuals high vs. low in dispositional anger. <=SEP=> Although numerous experiments have shown that exposure to violent video games (VVG) causes increases in aggression, relatively few studies have investigated the extent to which this effect differs as a function of theoretically relevant individual difference factors. This study investigated whether video game content differentially influences aggression as a function of individual differences in trait anger. Participants were randomly assigned to play a violent or nonviolent video game before completing a task in which they could behave aggressively. Results showed that participants high in trait anger were the most aggressive, but only if they first played a VVG. This relationship held while statistically controlling for dimensions other than violent content on which game conditions differed (e.g. frustration, arousal). Implications of these findings for models explaining the effects of video games on behavior are discussed.

Avoiding, finding and fixing spreadsheet errors - A survey of automated approaches for spreadsheet QA <=SEP=> Spreadsheet programs can be found everywhere in organizations and they are used for a variety of purposes, including financial calculations, planning, data aggregation and decision making tasks. A number of research surveys have however shown that such programs are particularly prone to errors. Some reasons for the error-proneness of spreadsheets are that spreadsheets are developed by end users and that standard software quality assurance processes are mostly not applied. Correspondingly, during the last two decades, researchers have proposed a number of techniques and automated tools aimed at supporting the end user in the development of error-free spreadsheets. In this paper, we provide a review of the research literature and develop a classification of automated spreadsheet quality assurance (QA) approaches, which range from spreadsheet visualization, static analysis and quality reports, over testing and support to model-based spreadsheet development. Based on this review, we outline possible opportunities for future work in the area of automated spreadsheet QA.

Applying High-Resolution Visible Imagery to Satellite Melt Pond Fraction Retrieval: A Neural Network Approach <=SEP=> During summer, melt ponds have a significant influence on Arctic sea-ice albedo. The melt pond fraction (MPF) also has the ability to forecast the Arctic sea-ice in a certain period. It is important to retrieve accurate melt pond fraction (MPF) from satellite data for Arctic research. This paper proposes a satellite MPF retrieval model based on the multi-layer neural network, named MPF-NN. Our model uses multi-spectral satellite data as model input and MPF information from multi-site and multiperiod visible imagery as prior knowledge for modeling. It can effectively model melt ponds evolution of different regions and periods over the Arctic. Evaluation results show that the MPF retrieved from MODIS data using the proposed model has an RMSE of 3.91% and a correlation coefficient of 0.73. The seasonal distribution of MPF is also consistent with previous results.

Multimaterial 3D Printing of Graphene-Based Electrodes for Electrochemical Energy Storage Using Thermoresponsive Inks. <=SEP=> The current lifestyles, increasing population, and limited resources result in energy research being at the forefront of worldwide grand challenges, increasing the demand for sustainable and more efficient energy devices. In this context, additive manufacturing brings the possibility of making electrodes and electrical energy storage devices in any desired three-dimensional (3D) shape and dimensions, while preserving the multifunctional properties of the active materials in terms of surface area and conductivity. This paves the way to optimized and more efficient designs for energy devices. Here, we describe how three-dimensional (3D) printing will allow the fabrication of bespoke devices, with complex geometries, tailored to fit specific requirements and applications, by designing water-based thermoresponsive inks to 3D-print different materials in one step, for example, printing the active material precursor (reduced chemically modified graphene (rCMG)) and the current collector (copper) for supercapacitors or anodes for lithium-ion batteries. The formulation of thermoresponsive inks using Pluronic F127 provides an aqueous-based, robust, flexible, and easily upscalable approach. The devices are designed to provide low resistance interface, enhanced electrical properties, mechanical performance, packing of rCMG, and low active material density while facilitating the postprocessing of the multicomponent 3D-printed structures. The electrode materials are selected to match postprocessing conditions. The reduction of the active material (rCMG) and sintering of the current collector (Cu) take place simultaneously. The electrochemical performance of the rCMG-based self-standing binder-free electrode and the two materials coupled rCMG/Cu printed electrode prove the potential of multimaterial printing in energy applications.

Knowledge management and organizational culture: a theoretical integrative framework <=SEP=> Purpose – Organizational culture is a critical factor in building and reinforcing knowledge management in organizations. However, there is no theoretical framework that comprehensively explains the effect of organizational culture on knowledge management in organizations. This paper endeavors to develop a theoretical integrative framework for organizational knowledge management and organizational culture. Design/methodology/approach – This is a conceptual paper. It modifies the ‘‘competing value framework’’ by adding a new dimension representing ethical and trusting culture, and then integrates it with the SECI model of knowledge creation and conversion by identifying the conceptual parallels between the two frameworks and then analyzing the interaction effects among the dimensions. Findings – Based on the congruity between the modified competing values framework and the knowledge creation and conversion framework, the paper formulates six propositions about the propensity of organizations of different dominant cultural styles to engage in the four processes of knowledge creation and conversion. Research limitations/implications – The dynamic nature of the framework presented in the paper points to the importance of longitudinal and comparative research in understanding the effects of organizational culture on organizational knowledge management systems in organizations. Practical implications – The proposed integrative framework would facilitate organizational learning and lead to the improvement of knowledge management practices in organizations as it helps managers to understand the linkages between culture and knowledge management. Originality/value – This paper presents a new framework linking organizational culture to knowledge management. It moves away from analyzing culture only in terms of its positive and negative influences on knowledge management. Instead, it suggests a typology of the kind of knowledge management processes that organizations are likely to focus on depending on the culture that prevails in an organization.

Improving lip-reading performance for robust audiovisual speech recognition using DNNs <=SEP=> This paper presents preliminary experiments using the Kaldi toolkit [1] to investigate audiovisual speech recognition (AVSR) in noisy environments using deep neural networks (DNNs). In particular we use a single-speaker large vocabulary, continuous audiovisual speech corpus to compare the performance of visual-only, audio-only and audiovisual speech recognition. The models trained using the Kaldi toolkit are compared with the performance of models trained using conventional hidden Markov models (HMMs). In addition, we compare the performance of a speech recognizer both with and without visual features over nine different SNR levels of babble noise ranging from 20dB down to -20dB. The results show that the DNN outperforms conventional HMMs in all experimental conditions, especially for the lip-reading only system, which achieves a gain of 37.19% accuracy (84.67% absolute word accuracy). Moreover, the DNN provides an effective improvement of 10 and 12dB SNR respectively for both the single modal and bimodal speech recognition systems. However, integrating the visual features using simple feature fusion is only effective in SNRs at 5dB and above. Below this the degradion in accuracy of an audiovisual system is similar to the audio only recognizer.