Miracle-dz/UniFAR-FTUs huggingface dataset:
High performance low complexity receiver for v-blast

A method of combining ZF-SIC (MMSE-SIC) and a reduced ML search is proposed (named ZF-SIC-SEARCH and MMSE-SIC-SEARCH) which gives V-BLAST decoding performance close to that of ML (maximum likelihood) while retaining the complexity comparable to that of ZF-SIC (MMSE-SIC). We show that ZF-SIC-SEARCH is same as ML algorithm for Mt = 2 (Mt denotes number of transmitting antennas). Our algorithm first determines a reduced set of candidate solution vectors and then chooses the one nearest (in the sense of Euclidean distance) to the received vector. For Mt = 2 in ZF-SIC-SEARCH, the diversity order analysis of one of these solution vectors named as true mapped vector shows that the true mapped vector enjoys additional diversity due to selection combining. We also present a method to further reduce complexity for higher order constellations by formulating the problem in an equivalent real domain. This alternative, though inferior to ML, still has significant performance improvement over conventional ZF-SIC/MMSE-SIC. Simulation results are presented for 5times5 MIMO system.
Tweet specific extractive summarization framework towards trending topic analysis

Twitter establishes itself as a critical element to any social networking based applications serving itself as a rich information delivering platform. However, some users, especially new users, often find it difficult to understand trending topics in Twitter when confronted with overwhelming and unorganized tweets. Previously, there has been attempts to provide a short snippet to summarize a topic but, this does not scale up to user's expectation as it does not provide any analyzed summary of tweets. This work aims to develop a Tweet Specific Extractive Summarization system performing Trending Topic Analysis. This system analyzes trending topics through Topic based sentiment classification which summarizes the public views on selected trending topics and generates extractive sub summaries of topics over the time period using novel Tweet Feature Graph Model (TFGM). Tweet Specific Extraction Summarization framework differs from the traditional summarization in few aspects. First, conflicting summary generation could be avoided with sentiment classification enhanced by common and tweet specific feature extraction thereby sorting the data into separate sentiment corpus. Second, volume-based followed by topic modelled approach of detecting sub topic in the corpus help detect subtopics under the trending topic more efficiently. Finally, Summary generation is accomplished using the Tweet Feature Graph Model (TFGM) which incorporates tweet specific salient features. This model increases relevancy of tweets in content selection phase which in turn contributes to the increase in quality of the summaries generated.
Undifferentiated embryonal sarcoma of the liver in an adult patient

Undifferentiated embryonal sarcoma of the liver (UESL) is rare primary hepatic sarcoma and is known to occur in pediatric patients. This case is the UESL occurred in a 51-year old male patient. Multilocular cystic lesion was composed of primitive spindle cells without specific differentiation. This rare case would help to review differential diagnosis of primary sarcoma in liver and cystic neoplasm of the liver.
Mining Interest Association Rules in Website Based on Hidden Markov Model

Generally, a user will access a Web site with a certain interest. Mining Web users' interest access patterns has been an important research direction in Web usage mining. These patterns are a kind of the special interest association rules essentially. In this paper, we propose a new approach for mining such rules based on hidden Markov model (HMM). In our approach, pages' contents and Web server's log need to be preprocessed firstly. Next we present some definitions of users' access interest in a Web site. In addition, a new incremental algorithm Hmm_R is given to discover the interest association rules. Finally, we report on experiments conducted with simulative and real data and then testify that the algorithm can find all interest association rules efficiently.
Signal stochastic decomposition over continuous dictionaries

We propose a Bayesian nonparametrics method, including algorithm for posterior computation, for the sparse regression problem. Our method applies in a general setting, when there are direct or indirect noisy observations of the signal. We try to make a wide focus on smoothness properties and sparsity of the approximate. As an example, we consider the ill-posed inverse problem of Quantum Homodyne Tomography.
ii Preface

The majority of the state-of-the-art approaches to recognizing textual entailment focus on defining a generic approach to RTE. A generic approach never works well for every single entailment pair: there are entailment pairs that are recognized poorly by all the generic systems. Automatic identification of such entailment pairs and applying to them an RTE algorithm that is specific to them could thus increase an overall performance of an entailment engine (that in this case will combine a generic RTE algorithm with a number of RTE algorithms for the problematic entailment pairs). We identify one subtype of entailment pairs and develop a two-part probabilistic model for their classification into true and false entailments and evaluate it relative both to a baseline and to the RTE systems. We show that the model performs better than the baseline and the average of the systems from the RTE2 on both the balanced and unbalanced datasets we have created for evaluation.
The metrical dependency of tone placement in Optimality Theory

Kim, Sun-Hoi. 2002. The metrical dependency of tone placement in Optimality Theory. Studies in Phonetics, Phonology and Morphology 8.1. 17-38. In this paper, I examine the metrical dependency of tone placement in OT. In Creek and Shingazidja, the determination of tone placement heavily draws on the special relationship between high tone and the metrically prominent position in the prosodic domain. In Shingazidja the metrically prominent position in the metrical phrase is tonally marked by high tone whereas the metrically prominent position in the prosodic word is tonally marked by high tone in Creek. In determining the metrically prominent position, the prosody of intonational phrase is metrically computed in Shingazidja whereas the prosody of prosodic word is metrically computed in Creek. In the metrical phrase in Shingazidja, the metrically prominent position is occupied by the rightmost vowel of the leftmost foot whereas the metrically prominent position is occupied by the rightmost vowel of the rightmost foot in the prosodic word in Creek. The ranking relationship of conflicting constraints formalizes the factors affecting the placement of high tone and the construction of metrical structure, and the parametric difference in the ranking relationship differentiates Shingazidja tonology from Creek tonology. (Hyupsung University)
Cedex Discussion Paper Series Does Consultation Improve Decision Making?

This paper reports an experiment designed to test whether prior consultation within a group affects subsequent individual decision making in tasks where demonstrability of correct solutions is low. In our experiment subjects considered two paintings created by two different artists and were asked to guess which artist made each painting. We observed answers given by individuals under two treatments: in one, subjects were allowed the opportunity to consult with other participants before making their private decisions; in the other there was no such opportunity. Our primary findings are that subjects in the first treatment evaluate the opportunity to consult positively but they perform significantly worse and earn significantly less.
MgII absorption through intermediate redshift galaxies

The current status and remaining questions of MgII absorbers are reviewed with an eye toward new results incorporating high quality Hubble Space Telescope images of the absorbing galaxies. In the end, we find that our current picture of extended gaseous regions around galaxies at earlier epochs is in need of some revision; MgII absorbing “halos” appear to be patchier and their geometry less regular than previously inferred. We also find that the so-called “weak” MgII absorbers are associated with normal galaxies over a wide range of impact parameters, suggesting that this class of absorber does not strictly select low surface brightness, dwarf galaxies, or IGM material. We emphasise the need for a complete survey of the galaxies in quasar fields, and the importance of obtaining rotation curves of confirmed absorbing galaxies.
Semi-supervised face image retrieval using sparse coding with identity constraint

We aim to develop a scalable face image retrieval system which can integrate with partial identity information to improve the retrieval result. To achieve this goal, we first apply sparse coding on local features extracted from face images combining with inverted indexing to construct an efficient and scalable face retrieval system. We then propose a novel coding scheme that refines the representation of the original sparse coding by using identity information. Using the proposed coding scheme, face images with large intra-class variances will still be quantized into similar visual words if they share the same identity. Experimental results show that our system can achieve salient retrieval results on LFW dataset (13K faces) and outperform linear search methods using well known face recognition feature descriptors.
Supplier evaluation and selection under uncertainty via an integrated model using cross-efficiency Data Envelopment Analysis and Monte Carlo simulation

This paper addresses a key objective of the supply chain strategic design, i.e., the optimal selection of suppliers under uncertainty. A methodology integrating the cross-efficiency Data Envelopment Analysis and the Monte Carlo approach is proposed. Their combination allows overcoming the deterministic feature of the classical cross-efficiency DEA. Moreover, we define an indicator of the robustness of the determined supplier ranking. The resulting technique allows managing the supplier selection problem while considering nondeterministic input and output data, a significant circumstance for assessing potential suppliers, with which there are no previous commercial relationships. The approach helps buyers in choosing the right partners under uncertainty and ranking them upon a multiple sourcing strategy.
Towards Enriching an ITS with Affective Support

Recent progress in affective computing is having an important impact on the development of Intelligent Tutoring Systems (ITS). Many ITS use action logs to record user’s interaction with the system, such as to discover important information that help instructional designers to improve the ITS performance. However, finer grain interaction data as well as emotional information gathered from external sources is required to determine affective or mental states that can be used to enrich learner’s experience with affective support. In this paper, we discuss what is needed to design an experiment for capturing relevant information from an ITS to improve the learner’s competence in solving algebraic word problems considering learners’ emotional and mental states.
Higher Education in Sudan and Knowledge Management Applications

Knowledge is a foundation of nation building. The discipline of knowledge management has become a hot topic in business because of its prospects for dramatic improvement in organizational effectiveness. Higher education institutions are in the knowledge business, since they are involved in knowledge creation and dissemination and learning. This paper is an attempt to examine the applicability of the concepts of knowledge management to higher education institutions in the Sudan. Identifies a number of existing facilities, systems or projects which contribute to knowledge management in higher education, such as libraries, and electronic collections of learning materials, networks for e-mail communication, and management information systems which provide data on the student profile. Then considers the challenges associated with the creation of a knowledge environment in higher education, and explores the opportunities offered by viewing knowledge as an asset. It discusses the distinction between knowledge, information and data, definitions of Knowledge (explicit and tacit knowledge and the distinction between them). Elaborate brief information about knowledge management; background information about higher education in Sudan.
Elaborating Feedback Strategies for Maintaining Automation in Highly Automated Driving

Human errors are a major reason for traffic accidents. One of the aims of the introduction of automated driving functions in vehicles is to prevent such accidents as such systems are supposed to be more reliable, react faster with higher precision. Therefore, we assume that an increase of automation features will also increase safety. However, when drivers are not willing to relinquish control to the vehicle, safety benefits of automated vehicles do not take effect. Therefore, convincing drivers to actively make use of the automation when appropriate can increase traffic safety. In this paper we investigate the influence of system feedback in proactive, safety critical takeover situations in automated driving. In contrast to handover, which is initiated by the system, proactive takeover is initiated by the driver, who's intention for steering the car is the reason for driving manually. We compare auditory feedback with audio-visual feedback realized as a virtual co-driver in a user study. We conducted a virtual reality simulator study (n=38) to investigate how system feedback influences the willingness of drivers to relinquish control to the vehicle. There were three conditions of system feedback: in condition none no feedback was given, in condition audio spoken feedback was given, and in condition co-driver additionally to audio feedback, a virtual co-driver on the front passenger seat was displayed. Our research provides evidence that system feedback can lead to an increase of willingness to maintain automation and to follow its safety related advices.
Bilateral Neural Control of Visually Guided Hand Movement

Does the right cerebral cortex stay inactive when one slams down on the brake pedal with their right foot in order to stop a car as quickly as possible in an emergency situation? I think not. This is obviously against a common view that the neural control of movement was unilateral: cerebral control, contralateral; cerebellar control, ipsilateral [1,2]. Here we discuss our previous studies of temporary inactivation experiments in the motor cortex and cerebellar nucleus of the nonhuman primates, and hypothesize that neural control of initiation of visually guided hand movement is bilateral. In our previous studies, tow monkeys were trained to practice a visually guided hand reaching task. After the monkeys mastered the task, separate muscimol injections were made into cerebellar Dentate Nucleus (DN) or primary motor cortex (M1) to inactivate the local neural activity during performance of the task. After unilateral injections made into the DN or the M1, significantly delayed initiation of hand movement (reaction time, from Target-on/Go-signal to hand release from the home key) was observed whether the monkeys used either hand to perform the task. In contrast, significantly slowed hand movement (movement time, from hand release of the home key to reaching the target) was observed only when the monkeys used the hand ipsilateral to the injected DN or contralateral to the injected M1. These results from the two monkeys were consistent. Our data indicate that both the DN and the M1 bilaterally contribute to reaction time, and unilaterally to movement time. This furthers the hypothesis that motor control in the brain is bilateral rather than unilateral. This theory has been supported by several independent studies. Examples include that motor response was delayed bilaterally by the unilateral frontal cortex lesion [3]; and clinical studies reported that the reaction time exceeded the normal range bilaterally after unilateral excisions in the supplementary motor area [4]. In addition, both the DN and the M1 contain diverse capabilities in relation to cognitive aspect of motor control during visually guided hand movement [5-7]. Thus, bilateral involvement of the DN and the M1 may be not surprising. To initiate movement, contribution of neurons from relatively wider areas of the brain, even across both hemispheres of the brain is often required. In the future, analysis of potential neural correlation with the bilateral effects of the reaction time may need to be done in both sides of the brain, particularly during the pre-motor period. This will help to understand how the single neurons are involved in the movement bilaterally. Last, clinical frontline also can benefit from this new theory of bilateral neural control. The questions of how to incorporate this new theory of bilateral neural control of movement into the clinical examination or evaluation, and how to create new therapies during the rehabilitation, in particular, to patients with hemiplegia soon need to be answered.
Machine self-learning applications in security systems

A set of conflict resolution methods is investigated with the purpose to construct knowledge refinement and self-learning tools applicable in a wide range of security systems (SS). The introduction of ontologies simplifies the detection process and lowers the complexity of the machine learning procedures. Different conflict resolution ways lead to particular autonomous/intelligent applications in different types of SS. The proposed self-learning methods are combinable with other web/data mining, anomaly detection, statistical methods, and show new ways in the development of collective evolutionary systems.
Affect, risk, and decision making.

Risk is perceived and acted on in 2 fundamental ways. Risk as feelings refers to individuals' fast, instinctive, and intuitive reactions to danger. Risk as analysis brings logic, reason, and scientific deliberation to bear on risk management. Reliance on risk as feelings is described with "the affect heuristic. " The authors trace the development of this heuristic across a variety of research paths. The authors also discuss some of the important practical implications resulting from ways that this heuristic impacts how people perceive and evaluate risk, and, more generally, how it influences all human decision making. Finally, some important implications of the affect heuristic for communication and decision making pertaining to cancer prevention and treatment are briefly discussed.
Performance of Double-Pole Four-Throw Double-Gate RF CMOS Switch in 45-nm Technology

In this paper, we have investigated the design parameters of RF CMOS switch, which will be used for the wireless tele-communication systems. A double-pole four-throw double-gate radio-frequency complementary-metal-oxide-semicon- ductor (DP4T DG RF CMOS) switch for operating at the 1 GHz is implemented with 45-nm CMOS process technology. This proposed RF switch is capable to select the data streams from the two antennas for both the transmitting and receiving processes. For the development of this DP4T DG RF CMOS switch we have explored the basic concept of the proposed switch circuit elements required for the radio frequency systems such as drain current, threshold voltage, resonant frequency, return loss, transmission loss, VSWR, resistances, capacitances, and switching speed.
Primary school teachers' experiences of well-being : how can well-being be supported by schools and educational psychologists?

With the additional responsibilities that come from the new SEND Code of practice and a government focus on supporting the mental health of children, the well-being of teachers was deemed a relevant and useful focus of research. This study aimed to elicit teachers’ experiences of well-being and the factors that support well-being, considering the role for the school and the Educational Psychologist. Data was collected from five Key Stage Two teachers in the same local authority using semi-structured interviews and analysed using Interpretative Phenomenological Analysis (Smith, Flowers and Larkin, 2009). The concept of well-being, professional identity, interpersonal relationships and interpersonal approaches, managing the demands of the role and personal resources were developed as superordinate themes. Conclusions and suggestions have been provided for schools and Educational Psychologists to discuss, which focus on a whole school approach to supporting well-being.
Internet of touch: analysis and synthesis of touch across wearable and mobile devices

We demonstrate a method that allows two users to communicate remotely using their sense of touch by dynamically applying vibrotactile feedback to one user's forearm using two different input methods. User input on a standard mobile touch-screen device or a purpose-built touch-sensitive wearable is analyzed in real time, and used to control intensity, location, and motion parameters of the vibrotactile output to synthesize the stroke on a second users arm. Our method demonstrates that different input methods can be used for generating similar vibrotactile sensations.
Fast Antenna Subset Selection for MIMO Wireless Systems

Along with the multiple-input multiple-output (MIMO) system gains, comes a price in hardware complexity and cost due to multiple RF chains. It is possible to alleviate this cost and at the same time maintain many advantages of MIMO systems by a technique known as antenna selection. In this paper, we propose a new receive antenna selection algorithm which is based on the analysis of the channel capacity. It can achieve very nearly outage capacity with the optimal selection method while keeping low computational complexity. Besides, the bit error rate (BER) performance under space-time block coding (STBC) transmit scheme demonstrates the significant performance of the proposed selection algorithm
Dynamic Purpose-Based Access Control

This article presents a new approach for privacy preserving access control based on RBAC. The separation of authorization of access purpose from access decision improves the flexibility of private data control. A key feature of this approach is dynamic. The access purpose is determined in a dynamic manner, based on subject attributes, context attributes and authorization policies. Intended purposes are dynamically associated with the requested data object during the access decision. Finally, we give the algorithm to achieve the compliance computation between the access purpose and intended purposes.
Genome-Wide Search Reveals the Existence of a Limited Number of Thyroid Hormone Receptor Alpha Target Genes in Cerebellar Neurons

Thyroid hormone (T3) has a major influence on cerebellum post-natal development. The major phenotypic landmark of exposure to low levels of T3 during development (hypothyroidism) in the cerebellum is the retarded inward migration of the most numerous cell type, granular neurons. In order to identify the direct genetic regulation exerted by T3 on cerebellar neurons and their precursors, we used microarray RNA hybridization to perform a time course analysis of T3 induced gene expression in primary cultures of cerebellar neuronal cell. These experiments suggest that we identified a small set of genes which are directly regulated, both in vivo and in vitro, during cerebellum post-natal development. These modest changes suggest that T3 does not acts directly on granular neurons and mainly indirectly influences the cellular interactions taking place during development.