Miracle-dz/UniFAR-FTUs huggingface dataset:
Beyond disciplinary boundaries: speaking back to critical knowledges, liberation, and community

This article explores critical directions for forging new disciplinary traditions within community psychology, as discussed by a panel at the conclusion of the 6th International Conference on Community Psychology (ICCP 2016). The conference itself was constructed as an enactment of a decolonizing approach, looking at the entire globalized system from the African continent and centring knowledges produced by Africans and the diaspora. Several panellists were invited to offer their reflections on the emerging discussions, and absences or silences they observed at the conference, as well as how community research and action can develop a research and teaching programme that is liberatory. Panellists’ comments pointed to the importance of the decolonization project globally and the implications of decoloniality for community research and action. The challenge for community research and action is to build alliances and networks across space and time, and with various social movements. The discipline needs to centre and draw out the voices of those who have been excluded, to retrieve and reclaim ways of knowing, being, and doing because these are key to tackling the coloniality of power and to forging new ways of doing ethical and just community research and action.
Long-lived Adaptive Collect with Applications ( Extended Abstract )

A distributed algorithm is adaptive if the worst case step complexity of its operations is bounded by a function of the number of processes that are concurrently active during the operation (rather than a function of N , the total number of processes, which is usually much larger). In this paper we present long-lived and adaptive algorithms for collect i n the read/write shared-memory model. Replacing the reads and writes in long-lived shared memory algorithms with our adaptive collect results in many cases in a corresponding long-lived algorithm which is adaptive. Examples of such applications, which are discussed in the paper are atomicsnapshots, and l-exclusion. Following the long-lived and adaptive collect we present a more pragmatic version of collect, called active set . This algorithm is slightly weaker than the collect but has severa l advantages. We employ this algorithm to transform algorithms, such as the Bakery algorithm, into their correspond ing adaptive long-lived version, which is more efficient tha n the version that was obtained with the collect. Previously, long-lived and adaptive algorithms in this model were presented only for the renaming problem [2]. A one-shot and adaptive collect algorithm was presented in [10].
Identification of time-varying systems with fast changing parameters using forgetting factor approach

In this paper, the basic principle of parameter identification of TVARX model using Recursive method with Forgetting Factor is given. Physical phenomena exhibit nonstationary or time varying behavior for a number of reasons. System identification is an experimental approach for determining the dynamic model of a system. One of the key elements for implementing this system model identification approach is the parameter adaptation algorithm, which drives the parameters of the adjustable prediction model from the data available at each sampling instant. The input is chosen as pseudo-random binary sequence which is frequency rich signal. The results are taken for fast varying parameters of first order TVARX model and the effect of variable forgetting factor is also observed. The performance is evaluated by calculating different performance measures of true and estimated values of model parameters for noisy and without noisy conditions. From the results, estimated parameters are nearly equal to that of actual model and small error is found at the instant of parameters changing.
Exploring generative perspective of convolutional neural networks by learning random field models

This paper studies the convolutional neural network (ConvNet or CNN) from a statistical modeling perspective. The ConvNet has proven to be a very successful discriminative learning machine. In this paper, we explore the generative perspective of the ConvNet. We propose to learn Markov random field models called FRAME (Filters, Random field, And Maximum Entropy) models using the highly sophisticated filters pre-learned by the ConvNet on the big ImageNet dataset. We show that the learned models can generate realistic and rich object and texture patterns in natural scenes. We explain that each learned model corresponds to a new ConvNet unit at the layer above the layer of filters employed by the model. We further show that it is possible to learn a generative ConvNet model with a new layer of multiple filters, and the learning algorithm admits an EM interpretation with binary latent variables.
Virtual Teams: The Impact of Advanced Knowledge and Process Collaboration Technologies on Software Development Team Processes and Performance

Virtual teams are becoming an important aspect of organisational life in many industries. In software development, virtual teams can be particularly useful as team members with the right skill set can generate code for a project no matter where they are in the world. However, this virtual setting often has limitations in terms of communication abilities, conflict, trust and performance. To improve the process of virtual software development, advanced knowledge and process collaboration technologies can be used. This proposal outlines an experiment to test the impact of using an advanced collaboration technology named MILOS in a virtual software development environment. It is hypothesised that by using MILOS as opposed to a less advanced collaboration technology, the measures of team trust, interaction quality and performance will be improved, with team conflict reduced. Virtual Teams: The Impact of Advanced Knowledge and Process Collaboration Technologies on Software Development Team Processes and Performance Alistair McKinnon
An Interactive 3 D Visualization for Content-Based Image Retrieval

3D visualization for Content-Based Images Retrieval (CBIR) eases integration of searching and browsing images in a large image database. While many researchers proposed visualization system for CBIR, most approaches display images based on a fixed set of image features. However, not all features are always equally important for users. Moreover, in most systems, all images in the database are displayed regardless of the user’s interest. Displaying too many images consume the resources and may confuse the users. In this paper, we propose an interactive 3D visualization system for Content-based image retrieval named 3D MARS. In 3D MARS, only relevant images are displayed on projection-based immersive Virtual Reality system or desktop VR. Based on the users’ feedback, the system dynamically reorganize its visualization scheme. 3D MARS eases tedious task of searching images from a large set of images. In addition, the sphere display mode effectively visualize clusters in the image database. This will be a powerful analyzing tool for CBIR researchers.
THE EVALUATION OF A VIRTUAL-AIDED DESIGN ENGINEERING REVIEW (VADER) SYSTEM FOR AUTOMATED KNOWLEDGE CAPTURE AND REUSE

Conducting knowledge capture and embedding it into a products’ through lifecycle remains a key issue in engineering industries; particularly with regard to rationale associated knowledge emanating during formal design reviews. Manual, and often interruptive, methods with associated costly overheads, exacerbate the already time consuming process. As well as these disadvantages, manual methods can potentially capture the wrong data due to human error or not fullycapturing all the pertinent information and associated relationships. Consequently, industries are seeking automated engineering knowledge capture and rationale that adds value to product and processes, potentially reaping the benefits of time and cost. Previous work by the authors proved how userlogging in virtual environments aid unobtrusive capture of engineering knowledge and rationale in design tasks. This paper advances the work further through a Virtual Aided Design Engineering Review (VADER) system developed to automatically and unobtrusively capture both multimodal human-computer and human-human interactivity during design reviews via the synchronous time-phased logging of software interactions, product models, audio, video and input devices. By processing the captured data review reports and records can be automatically generated as well as allowing fast knowledge retrieval. The backbone of VADER is a multimodal device and data fusion architecture to capture and synchronise structured and unstructured data in realtime. Visualisation is through a 3D virtual environment. In addition to allowing engineers to visualise and annotate 3D design models, the system provides a timeline interface to search and visualise the captured decisions from a design review. The VADER system has been put through its initial industrial trial and reported herein. Objective and subjective analysis indicate the VADER system is intuitive to use and can lead to savings in both time and cost with regard to project reviews.
A New Approach to Disk-Based Scalable Mass Storage System

We present a new approach to create large-scale cost-effective mass storage systems using high-capacity disks. The architecture is optimized across multiple dimensions to support streaming and large-block data access. Because I/O requests in these applications are to a small fraction of data, we power-cycle drives as needed to create a very high-density storage system. Data protection is provided through a new variant of RAID, termed power-managed RAIDTM, which generates parity without requiring all drives in the RAID set to be powered on. To increase bandwidth, the system employs several concurrency mechanisms including load balancing I/O streams across many parallel RAID controllers. A number of optimizations are made to the interconnection architecture and caching schemes that lowers the cost of storage to that of typical automated tape library systems while exploiting the performance and reliability advantages of disk systems. Recent results at COPAN Systems have proven the viability of this new storage category and product. 1. Background Growing reference information, regulatory data and rich media archives [1] are providing new impetus for mass storage systems. Unlike transaction applications, these systems access a small fraction of the data infrequently or on a scheduled basis. One such application is backup and restore that is characterized by large-block streaming writes and infrequent reads. With their need for large-scale storage, these applications are very sensitive to cost. Historically, they have been addressed by automated tape libraries. While concerns with performance, lack of data protection, and the reliability of tapes [2] have always favored disk systems, their limited capacity and high cost have prevented them from replacing tape. The advent of highcapacity SATA drives and their cost approaching that of tape motivates us to revisit this design issue. Existing approaches to high-capacity storage have been incremental, typically substituting Fibre Channel (FC) disks with lower cost ATA disks in standard RAID arrays. This does not result in increased storage density or the cost per unit storage of tape libraries which usually have a 3X advantage over disk systems. Therefore, a fundamentally different approach is required. We believe the best approach is to use an application and workload-driven architecture to provide the performance and reliability of disks at the scale and cost of tape. 2. A New Approach: Application Specific Storage System The specific needs of archival storage applications help define the architectural constraints. These include: • I/O requests to large block with sequential or predictable access
Roles in social networks: Methodologies and research issues

The expansion of web user roles is, nowadays, a fact due to the ability of users to interact, discuss, exchange ideas and opinions, and form social networks through the web. The interaction level among users leads to the appearance of several social roles which can be characterized as positions, behaviors, or virtual identities. These roles may be developed in social networks, and they keep changing and evolving over time. In this article, a survey of the state-of-the-art approaches is presented regarding the identification of roles within the context of a social network. It is shown that social roles exist as a function of each other; they appear and evolve through user interaction. Different approaches are analyzed and additional characteristics that should be taken into account during the role analysis are discussed.
French family business and longevity: Have they been conducting sustainable development policies before it became a fashion?

This paper weaves together two strands of literature: one on sustainable development (SD) and one on family business (FB), with a focus on the longevity of FB. We investigate the SD literature and then review the FB one on longevity, in light of the key questions related to SD. Using 27 h of fully transcribed interviews, with 17 different FB owners or family members, from six long-standing French FBs, we set out to identify what factors family members associate with the longevity of their company. We check with what consistency these factors relate to the FB and SD literature.
You don't know how strong you are until being strong is your only option : examining resiliency in survivors of a parent or caregiver's suicide

Suicide is a prevalent public health issue in the United States as it intimately effects many Americans annually. This study explored the bereavement and coping processes as well as strength and resiliency of adult children who lost their parent to death by suicide. Twelve adult children were recruited for this study through social media and suicide support groups. Participants were interviewed by phone and interviews were transcribed and analyzed using an inductive approach. The following themes were identified: intensity of the loss, secondary trauma of suicide, feelings of stigma, solace in talking about their parent, researching mental illness, attending grief groups, and advocating for suicide prevention. This research is limited in scope but provides important information for clinicians caring for suicide survivors. Future research should explore secondary trauma of suicide survivors as this was a significant theme within the study.
Automated Visual Recognition of Individual African

African penguins (Spheniscus demersus) carry a pattern of black spots on their chests that does not change from season to season during their adult life. Further, as far as we can tell, no two penguins have exactly the same pattern. We have developed a real-time system that can confidently locate African penguins whose chests are visible within video sequences or still images. An extraction of the chest spot pattern allows the generation of a unique biometrical identifier for each penguin. Using these identifiers an authentication of filmed or photographed African penguins against a population database can be performed. This paper provides a detailed technical description of the developed system and outlines the scope and the conditions of application Figure 1. Identification of an African Penguin by its Chest Pattern: Screenshot of Software Prototype; African penguins carry a unique pattern of black spots on their chest. The detection of the chest location and the decomposition of the spot pattern allow checking a photographed individual (here penguin ‘David’ from Bristol Zoo) against a population database. (figure source [18], [19])
A declarative approach to active databases

A general description is provided of the field of active databases, focusing on the main problems yet to be solved. The author suggests that deductive databases may contribute to the understanding of some of these problems. Classes of applications that can be specified in a declarative manner are indicated. Important classes of active database applications can have a declarative interface supporting the designer during rule generation, resulting in collections of rules with an efficient and well-understood behavior. <<ETX>>
Animation through Body Language : A study using the fictional character Mokhtar

Learning to read body language is something we do throughout our whole life. It is a complex non-verbal language that can express more than words. In this study we investigate the possibility to use only body language to portray emotions to the viewer. In a background of a game project we have used a character that has his face covered, therefore, facial expression is not visible during the online survey, which we used as a method for our investigation. As a foundation we have created four character animations to portray anger, frustration, exhaustion and hurt. To find the answer if it is possible to recognize those five emotions in the character animations survey, participants were obligated to name the emotion expressed on each of the video clips. The results of this study show that the characters body language could be sufficient to portray those five emotions. However, it was concluded that body language could be enough to represent the character's emotional state to the viewer; but by including facial expressions we could help to portray the emotion even further.
Performance evaluation of a secure Low Level Reader Protocol(LLRP) connection

Summary The recently ratified Low Level Reader Protocol (LLRP) specifies the interaction between a RFID Reader and Client. It has been of much interest in the RFID community but adoption is being stalled by its lack of formal scrutiny especially with regard to its security. This paper surveys the work that has been undertaken on this protocol, assesses its security vulnerabilities and examines possible security solutions. It then presents the design and implementation of LLRP endpoints that use Transport Layer Security (TLS) to setup a secure LLRP connection. Based on previous performance studies, appropriate metrics are selected to indicate the performance of the resulting TLS-LLRP connection. Specifically, the overhead of securing a LLRP connection using TLS is quantified and a detailed analysis of the results is undertaken to determine the TLS cipher suites and parameters that provide the best compromise between the level of security and performance.
Infusing moral education into English language teaching: an ontogenetic analysis of social values in EFL textbooks in Hong Kong

ABSTRACT This paper investigates the representation of social values and their ontogenetic development in English as a foreign language textbooks in Hong Kong. Adopting a social semiotic approach, it considers social values in textbooks as semantic categories which are constructed by complex semiotic discursive resources, and develops an explicit framework to model what values are selected and how the values are constructed. Analysis of 19 textbooks from Primary 1 to Secondary 4–6 shows that the social values change from the personal domain (e.g. good hygiene and healthy lifestyle), through the interpersonal domain (e.g. politeness and respect), to the altruistic concern for all mankind. The result also suggests that the textbooks are more concerned with the didactic education of good citizens than with cultivating children’s critical thinking. The analytical framework and the findings can be used for the explicit instruction and critical analysis of social values in English language teaching.
A fully monolithic SiGe quadrature voltage controlled oscillator design for GSM/DCS-PCS applications

This paper describes the design and optimization in terms of phase noise of a fully monolithic SiGe Voltage Controlled Oscillator (VCO) with quadrature outputs. The proposed circuit is made of two cross-coupled differential VCO's, with integrated resonator, to ensure the quadrature outputs. The quadrature VCO core runs on 13 mA from a 2.7 V power supply. The simulated phase noise is about -140 dBc/Hz at 3 MHz frequency offset almost all over the tuning range. The oscillator is tuned from 1.44 GHz to 1.76 GHz with a tuning voltage varying from 0 to 3 V.
Point-based policy generation for decentralized POMDPs

Memory-bounded techniques have shown great promise in solving complex multi-agent planning problems modeled as DEC-POMDPs. Much of the performance gains can be attributed to pruning techniques that alleviate the complexity of the exhaustive backup step of the original MBDP algorithm. Despite these improvements, state-of-the-art algorithms can still handle a relative small pool of candidate policies, which limits the quality of the solution in some benchmark problems. We present a new algorithm, Point-Based Policy Generation, which avoids altogether searching the entire joint policy space. The key observation is that the best joint policy for each reachable belief state can be constructed directly, instead of producing first a large set of candidates. We also provide an efficient approximate implementation of this operation. The experimental results show that our solution technique improves the performance significantly in terms of both runtime and solution quality.
Detection of Circulating Tumor Cells

The increasing number of treatment options for patients with metastatic carcinomas has created an accompanying need for methods to determine if the tumor will be responsive to the intended therapy and to monitor its effectiveness. Ideally, these methods would be noninvasive and provide quantitative real-time analysis of tumor activity in a variety of carcinomas. Assessment of circulating tumor cells shed into the blood during metastasis may satisfy this need. Here we review the CellSearch technology used for the detection of circulating tumor cells and discuss potential future directions for improvements.
A Modified Construction for a Support Vector Classifier to Accommodate Class Imbalances

Given a training set with binary classification, the Support Vector Machine identifies the hyperplane maximizing the margin between the two classes of training data. This general formulation is useful in that it can be applied without regard to variance differences between the classes. Ignoring these differences is not optimal, however, as the general SVM will give the class with lower variance an unjustifiably wide berth. This increases the chance of misclassification of the other class and results in an overall loss of predictive performance. An alternate construction is proposed in which the margins of the separating hyperplane are different for each class, each proportional to the standard deviation of its class along the direction perpendicular to the hyperplane. The construction agrees with the SVM in the case of equal class variances. This paper will then examine the impact to the dual representation of the modified constraint equations.
Efficient Diffusion-based Illumination Normalization for Face Verification

In this paper, the problem of face verification across illumination is addressed. In order to cope with different lighting conditions, a preprocessing step is applied to the face image so as to make it independent on the illumination conditions. The illuminant invariant representation of the image is obtained by first applying an anisotropic diffusion process to the original image. Hence, it implies the numerical resolution of an elliptic partial differential equation on a large grid: the image. So, a comparison is performed on two methods to resolve such diffusion problems, namely the Gauss-Seidel relaxation and the Multigrid V-cycle. The preprocessing algorithm with its different resolution schemes is applied prior to the task of face verification. Experiments conducted on the challenging BANCA database showed a significant improvement in terms of face verification error rate, while staying computationally efficient.