title: Use of depth and colour eigenfaces for face recognition

abstract: In the present paper a face recognition technique is developed based on depth and colour information. The main objective of the paper is to evaluate three different approaches (colour, depth, combination of colour and depth) for face recognition and quantify the contribution of depth. The proposed face recognition technique is based on the implementation of the principal component analysis algorithm and the extraction of depth and colour eigenfaces. Experimental results show significant gains attained with the addition of depth information.


title: Acquiring temporal constraints between relations

abstract: We consider the problem of automatically acquiring knowledge about the typical temporal orderings among relations (e.g., actedIn(person, film) typically occurs before wonPrize (film, award)), given only a database of known facts (relation instances) without time information, and a large document collection. Our approach is based on the conjecture that the narrative order of verb mentions within documents correlates with the temporal order of the relations they represent. We propose a family of algorithms based on this conjecture, utilizing a corpus of 890m dependency parsed sentences to obtain verbs that represent relations of interest, and utilizing Wikipedia documents to gather statistics on narrative order of verb mentions. Our proposed algorithm, GraphOrder, is a novel and scalable graph-based label propagation algorithm that takes transitivity of temporal order into account, as well as these statistics on narrative order of verb mentions. This algorithm achieves as high as 38.4% absolute improvement in F1 over a random baseline. Finally, we demonstrate the utility of this learned general knowledge about typical temporal orderings among relations, by showing that these temporal constraints can be successfully used by a joint inference framework to assign specific temporal scopes to individual facts.


title: Indentifying Emotional Characteristics from Short Blog Texts

abstract: Emotion is at the core of understanding ourselves and others, and the automatic expression and detection of emotion could enhance our experience with technologies. In this paper, we explore the use of computational linguistic tools to derive emotional features. Using 50 and 200 word samples of naturally-occurring blog texts, we find that some emotions are more discernible than others. In particular automated content analysis shows that authors expressing anger use the most affective language and also negative affect words; authors expressing joy use the most positive emotion words. In addition we explore the use of co-occurrence semantic space techniques to classify texts via their distance from emotional concept exemplar words: This demonstrated some success, particularly for identifying author expression of fear and joy emotions. This extends previous work by using finer-grained emotional categories and alternative linguistic analysis techniques. We relate our finding to human emotion perception and note potential applications.


title: REGION-BASED ENDOCARDIUM TRACKING ON REAL-TIME THREE- DIMENSIONAL ULTRASOUND

abstract: Matrix-phased array transducers for real-time 3-D ultrasound enable fast, noninvasive visualization of cardiac ventricles. Typically, 3-D ultrasound images are semiautomatically segmented to extract the left ventricular endocardial surface at end-diastole and end-systole. Automatic segmentation and propagation of this surface throughout the entire cardiac cycle is a challenging and cumbersome task. If the position of the endocardial surface is provided at one or two time frames during the cardiac cycle, automated tracking of the surface over the remaining time frames could reduce the workload of cardiologists and optimize analysis of 3-D ultrasound data. In this paper, we applied a region-based tracking algorithm to track the endocardial surface between two reference frames that were manually segmented. To evaluate the tracking of the endocardium, the method was applied to 40 open-chest dog datasets with 484 frames in total. Ventricular geometry and volumes derived from region-based endocardial surfaces and manual tracing were quantitatively compared, showing strong correlation between the two approaches. Statistical analysis showed that the errors from tracking were within the range of interobserver variability of manual tracing. Moreover, our algorithm performed well on ischemia datasets, suggesting that the method is robust-to-abnormal wall motion. In conclusion, the proposed optical flow-based surface tracking method is very efficient and accurate, providing dynamic "interpolation" of segmented endocardial surfaces.


Myocardial viability: evidence provided by the analysis of left ventricular systolic function


title: Inductive power transfer system with a rotary transformer for contactless energy transfer on rotating applications

abstract: This paper examines an inductive power transfer (IPT) system with a rotary transformer as an alternative solution to slip ring systems for a contactless energy transfer to rotating equipment. A prototype system is set up, consisting of a rotating ball bearing shaft and an exemplary sensor circuit mounted on the shaft. Three possible transformer configurations are analyzed theoretically and experimentally regarding the self-inductance, the coupling factor and the losses in the litz wire. To utilize the intrinsic stray inductances of the rotary transformer, a series compensated resonant converter is implemented for the prototype system.


title: Submitted to Interacting with Computers special issue on HCI and the Older Population Corresponding author:

abstract: Relational agents-computational artifacts designed to build and maintain long-term social-emotional relationships with users-may provide an effective interface modality for older adults. This is especially true when the agents use simulated face-to-face conversation as the primary communication medium, and for applications in which repeated interactions over long time periods are required, such as in health behavior change. In this article, we discuss the design of a relational agent for older adults that plays the role of an exercise advisor, and report on the results of a longitudinal study involving 21 adults aged 62-84, half of whom interacted with the agent daily for 2 months in their homes and half who served as a standard-of-care control. Results indicate the agent was accepted and liked, and was significantly more efficacious at increasing physical activity (daily steps walked) than the control.


title: Performance Analysis of 6LoWPAN and CoAP for Secure Communications in Smart Homes

abstract: Smart grids and smart homes improve energy management by coupling communication capabilities to their devices. Due to computational constraints of these devices, employment of simplified communication protocols is necessary. In this paper, we investigate the use of communication protocols based on CoAP and 6LoWPAN in smart home environments. Specifically, we analyze the vulnerabilities a smart home employing CoAP and 6LoWPAN may be susceptible to. We also present a performance analysis of the use of these protocols for ensuring secure communicationsin smart homes.


title: A Survey on Opportunistic Routing Protocols for Wireless Sensor Networks

abstract: Abstract Opportunistic routing is a new paradigm in routing for wireless sensor network which chooses the node closest to the target node for forwarding the data. It uses the broadcasting nature of wireless sensor networks. Opportunistic routing has increased the efficiency, throughput and reliability of sensor networks. Many energy saving techniques has been introduced using opportunistic routing in wireless sensor networks for increasing the network lifetime. In this article we have elaborated the basic concept of Opportunistic routing, different areas in which it has been claimed to be beneficial, some protocols their metrics and their drawbacks.


title: A Model-Predictive Motion Planner for the IARA Autonomous Car

abstract: We present the Model-Predictive Motion Planner (MPMP) of the Intelligent Autonomous Robotic Automobile (IARA). IARA is a fully autonomous car that uses a path planner to compute a path from its current position to the desired destination. Using this path, the current position, a goal in the path and a map, IARA's MPMP is able to compute smooth trajectories from its current position to the goal in less than 50 ms. MPMP computes the poses of these trajectories so that they follow the path closely and, at the same time, are at a safe distance of eventual obstacles. Our experiments have shown that MPMP is able to compute trajectories that precisely follow a path produced by a Human driver (distance of 0.15 m in average) while smoothly driving IARA at speeds of up to 32.4 km/h (9 m/s).


title: Design and implementation of a 300% strain soft artificial muscle

abstract: We present the inverse pneumatic artificial muscle (IPAM), a new soft actuator that is powered by pneumatics in a manner inverse to traditional pneumatic muscles: low pressure, rather than high, contracts the muscle. The IPAM improves on the 50-year-old standard in soft pneumatic actuators, the McKibben muscle, but retains many of the advantages that have drawn roboticists to this artificial muscle over the years. The McKibben muscle produces up to 40% strain, and has nonlinear control with friction and hysteresis, whereas the IPAM attains strains of over 300% and has a nearly linear mapping between input pressure and force/length output and no sliding friction. Crucially, the IPAM retains the soft structure, low weight, compliance, and robustness that the McKibben muscle boasts. We present a simple model to describe the behavior of the muscle, as well as force, displacement, pressure, and speed tests validating the model and characterizing the IPAM's performance. Further, we present two practical implementations using the IPAM: an active brace and a robotic finger.


title: A 140-GHz high-gain broadband tapered box-horn array antenna

abstract: A high-gain broadband low-profile low-loss antenna array of box horn at 140 GHz frequency fed by waveguide is proposed in this study. The element spacing is larger than one wavelength, resulting from the aperture size of horn and the width of the waveguide, which causes grating lobes. The simulated grating lobes in the E- and H-plane are below −16 dB and −19 dB, suppressed by a tapered structure and a special horn type of box horn, respectively. The horn array antenna exhibits 40.7-dBi peak gain and a relative impedance bandwidth of 25.26% from 120 GHz to 155.37 GHz under the condition of voltage standing wave ratio (VSWR) less than 2.


title: AdDroid: privilege separation for applications and advertisers in Android

abstract: Advertising is a critical part of the Android ecosystem---many applications use one or more advertising services as a source of revenue. To use these services, developers must bundle third-party, binary-only libraries into their applications. In this model, applications and their advertising libraries share permissions. Advertising-supported applications must request multiple privacy-sensitive permissions on behalf of their advertising libraries, and advertising libraries receive access to all of their host applications' other permissions. We conducted a study of the Android Market and found that 49% of Android applications contain at least one advertising library, and these libraries overprivilege 46% of advertising-supported applications. Further, we find that 56% of the applications with advertisements that request location (34% of all applications) do so only because of advertisements. Such pervasive overprivileging is a threat to user privacy. We introduce AdDroid, a privilege separated advertising framework for the Android platform. AdDroid introduces a new advertising API and corresponding advertising permissions for the Android platform. This enables AdDroid to separate privileged advertising functionality from host applications, allowing applications to show advertisements without requesting privacy-sensitive permissions.


title: European guidelines for the diagnosis and treatment of pelvic girdle pain

abstract: A guideline on pelvic girdle pain (PGP) was developed by "Working Group 4" within the framework of the COST ACTION B13 "Low back pain: guidelines for its management", issued by the European Commission, Research Directorate-General, Department of Policy, Coordination and Strategy. To ensure an evidence-based approach, three subgroups were formed to explore: (a) basic information, (b) diagnostics and epidemiology, and (c) therapeutical interventions. The progress of the subgroups was discussed at each meeting and the final report is based on group consensus. A grading system was used to denote the strength of the evidence, based on the AHCPR Guidelines (1994) and levels of evidence recommended in the method guidelines of the Cochrane Back Review group. It is concluded that PGP is a specific form of low back pain (LBP) that can occur separately or in conjunction with LBP. PGP generally arises in relation to pregnancy, trauma, arthritis and/or osteoarthritis. Uniform definitions are proposed for PGP as well as for joint stability. The point prevalence of pregnant women suffering from PGP is about 20%. Risk factors for developing PGP during pregnancy are most probably a history of previous LBP, and previous trauma to the pelvis. There is agreement that non risk factors are: contraceptive pills, time interval since last pregnancy, height, weight, smoking, and most probably age. PGP can be diagnosed by pain provocation tests (P4/thigh thrust, Patrick's Faber, Gaenslen's test, and modified Trendelenburg's test) and pain palpation tests (long dorsal ligament test and palpation of the symphysis). As a functional test, the active straight leg raise (ASLR) test is recommended. Mobility (palpation) tests, X-rays, CT, scintigraphy, diagnostic injections and diagnostic external pelvic fixation are not recommended. MRI may be used to exclude ankylosing spondylitis and in the case of positive red flags. The recommended treatment includes adequate information and reassurance of the patient, individualized exercises for pregnant women and an individualized multifactorial treatment program for other patients. We recommend medication (excluding pregnant women), if necessary, for pain relief. Recommendations are made for future research on PGP.


title: Acquisition and analysis of volatile memory from android devices

abstract: The Android operating system for mobile phones, which is still relatively new, is rapidly gaining market share, with dozens of smartphones and tablets either released or set to be released. In this paper, we present the first methodology and toolset for acquisition and deep analysis of volatile physical memory from Android devices. The paper discusses some of the challenges in performing Android memory acquisition, discusses our new kernel module for dumping memory, named dmd, and specifically addresses the difficulties in developing device-independent acquisition tools. Our acquisition tool supports dumping memory to either the SD on the phone or via the network. We also present analysis of kernel structures using newly developed Volatility functionality. The results of this work illustrate the potential that deep memory analysis offers to digital forensics investigators.


title: On-line novelty detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

abstract: Leakage detection is an important issue in many chemical sensing applications. Leakage detection by thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the array. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.


title: Elicitation technique selection: how do experts do it?

abstract: Requirements elicitation techniques are methods used by analysts to determine the needs of customers and users, so that systems can be built with a high probability of satisfying those needs. Analysts with extensive experience seem to be more successful than less experienced analysts in uncovering the user needs. Less experienced analysts often select a technique based on one of two reasons: (a) it is the only one they know, or (b) they think that a technique that worked well last time must surely be appropriate this time. We present the results of in-depth interviews with some of the world's most experienced analysts. These results demonstrate how they select elicitation techniques based on a variety of situational assessments.


title: Infected Pressure Ulcers in Elderly Individuals

abstract: Pressure ulcers in elderly individuals can cause significant morbidity and mortality and are a major economic burden to the health care system. Prevention should be the ultimate objective of pressure ulcer care, and it requires an understanding of the pathophysiology leading to pressure ulcers and the means of reducing both intrinsic and extrinsic risk factors. Clinical manifestations are protean, and early recognition requires a low threshold of suspicion. Clinical examination often underestimates the degree of deep-tissue involvement, and its findings are inadequate for the detection of associated osteomyelitis. Microbiological data, if obtained from deep-tissue biopsy, are useful for directing antimicrobial therapy, but they are insufficient as the sole criterion for the diagnosis of infection. Imaging studies, such as computed tomography and magnetic resonance imaging, are useful, but bone biopsy and histopathological evaluation remain the gold standard for the detection of osteomyelitis. The goals of treatment of pressure ulcers should be resolution of infection, promotion of wound healing, and establishment of effective infection control.


title: A Survey of LoRaWAN for IoT: From Technology to Application

abstract: LoRaWAN is one of the low power wide area network (LPWAN) technologies that have received significant attention by the research community in the recent years. It offers low-power, low-data rate communication over a wide range of covered area. In the past years, the number of publications regarding LoRa and LoRaWAN has grown tremendously. This paper provides an overview of research work that has been published from 2015 to September 2018 and that is accessible via Google Scholar and IEEE Explore databases. First, a detailed description of the technology is given, including existing security and reliability mechanisms. This literature overview is structured by categorizing papers according to the following topics: (i) physical layer aspects; (ii) network layer aspects; (iii) possible improvements; and (iv) extensions to the standard. Finally, a strengths, weaknesses, opportunities and threats (SWOT) analysis is presented along with the challenges that LoRa and LoRaWAN still face.


title: Human–Robot Synchrony: Flexible Assistance Using Adaptive Oscillators

abstract: We propose a novel method for movement assistance that is based on adaptive oscillators, i.e., mathematical tools that are capable of extracting the high-level features (amplitude, frequency, and offset) of a periodic signal. Such an oscillator acts like a filter on these features, but keeps its output in phase with respect to the input signal. Using a simple inverse model, we predicted the torque produced by human participants during rhythmic flexion extension of the elbow. Feeding back a fraction of this estimated torque to the participant through an elbow exoskeleton, we were able to prove the assistance efficiency through a marked decrease of the biceps and triceps electromyography. Importantly, since the oscillator adapted to the movement imposed by the user, the method flexibly allowed us to change the movement pattern and was still efficient during the nonstationary epochs. This method holds promise for the development of new robot-assisted rehabilitation protocols because it does not require prespecifying a reference trajectory and does not require complex signal sensing or single-user calibration: the only signal that is measured is the position of the augmented joint. In this paper, we further demonstrate that this assistance was very intuitive for the participants who adapted almost instantaneously.


title: A Ka-Band patch antenna array with improved circular polarization

abstract: In this paper, a Ka-Band patch sub-array structure for millimeter-wave phased array applications is demonstrated. The conventional corner truncated patch is modified to improve the impedance and CP bandwidth alignment. A new sub-array feed approach is introduced to reduce complexity of the feed line between elements and increase the radiation efficiency. A sub-array prototype is built and tested. Good agreement with the theoretical results is obtained.


title: Interactive navigation of multiple agents in crowded environments

abstract: We present a novel approach for interactive navigation and planning of multiple agents in crowded scenes with moving obstacles. Our formulation uses a precomputed roadmap that provides macroscopic, global connectivity for wayfinding and combines it with fast and localized navigation for each agent. At runtime, each agent senses the environment independently and computes a collision-free path based on an extended "Velocity Obstacles" concept. Furthermore, our algorithm ensures that each agent exhibits no oscillatory behaviors. We have tested the performance of our algorithm in several challenging scenarios with a high density of virtual agents. In practice, the algorithm performance scales almost linearly with the number of agents and can run at interactive rates on multi-core processors.


title: Digital Watermarking Applications and Techniques: A Brief Review

abstract: The frequent availability of digital data such as audio, images and videos became possible to the public through the expansion of the internet. Digital watermarking technology is being adopted to ensure and facilitate data authentication, security and copyright protection of digital media. It is considered as the most important technology in today's world, to prevent illegal copying of data. Digital watermarking can be applied to audio, video, text or images. This paper includes the detail study of watermarking definition and various watermarking applications and techniques used to enhance data security.


title: Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference

abstract: In logic-based approaches to reasoning tasks such as Recognizing Textual Entailment (RTE), it is important for a system to have a large amount of knowledge data. However, there is a tradeoff between adding more knowledge data for improved RTE performance and maintaining an efficient RTE system, as such a big database is problematic in terms of the memory usage and computational complexity. In this work, we show the processing time of a state-of-the-art logic-based RTE system can be significantly reduced by replacing its search-based axiom injection (abduction) mechanism by that based on Knowledge Base Completion (KBC). We integrate this mechanism in a Coq plugin that provides a proof automation tactic for natural language inference. Additionally, we show empirically that adding new knowledge data contributes to better RTE performance while not harming the processing speed in this framework.


title: Measurement of AT electric railway system currents at power-supply frequency and validation of a multiconductor transmission-line model

abstract: An electric traction system supplied at 2 /spl times/ 25 kV with autotransformers (ATs) is considered. The conductors' arrangement is that of the new European High Speed Railway Line (HSRL) under construction: The overhead supply conductors in contact with the train pantograph are connected to a symmetrical circuit (the feeder) with the purpose of current balancing; the traction return current flows from the rolling stock axles back to the supply (i.e., substation) through the traction rails and additional return conductors. The test campaign carried on the Rome-Naples HSRL allowed the validation of the multiconductor transmission line model used for system analysis. Measurements were performed in normal system configuration (2 /spl times/ 25-kV supply) and degraded configuration (1 /spl times/ 25 kV with AT and feeder not operating). Metrological issues (accuracy and consistency) are detailed for the presented results.


title: INDIGENOUS KNOWLEDGE CREATION PRACTICES:

abstract: Knowledge management in general, and knowledge creation in particular, gives organizations a competitive advantage in the knowledge era. Although there is a lack of deliberate knowledge management and creation efforts in modern Ethiopia, the country possesses 1,700-year old indigenous practices of knowledge creation. This research in progress seeks to explore the extent to which indigenous knowledge creation practices can inform knowledge creation practices in organizations. We use Nonaka’s SECI model (Socialization Externalization Combination Internalization) to guide our inquiry, and rely on a qualitative, interpretive field study approach to investigate indigenous knowledge management initiatives and their transferability. This research will be relevant not only to researchers interested in knowledge management in the developing world, but also for those interested in conducting research within indigenous communities.


title: Triple-negative breast cancer: clinical features and patterns of recurrence.

abstract: PURPOSE ::: To compare the clinical features, natural history, and outcomes for women with "triple-negative" breast cancer with women with other types of breast cancer. ::: ::: ::: EXPERIMENTAL DESIGN ::: We studied a cohort of 1,601 patients with breast cancer, diagnosed between January 1987 and December 1997 at Women's College Hospital in Toronto. Triple-negative breast cancers were defined as those that were estrogen receptor negative, progesterone receptor negative, and HER2neu negative. The prognostic significance of triple-negative breast cancer was explored. ::: ::: ::: RESULTS ::: The median follow-up time of the 1,601 women was 8.1 years. One hundred and eighty of 1,601 patients (11.2%) had triple-negative breast cancer. Compared with other women with breast cancer, those with triple-negative breast cancer had an increased likelihood of distant recurrence (hazard ratio, 2.6; 95% confidence interval, 2.0-3.5; P < 0.0001) and death (hazard ratio, 3.2; 95% confidence interval, 2.3-4.5; P < 0.001) within 5 years of diagnosis but not thereafter. The pattern of recurrence was also qualitatively different; among the triple-negative group, the risk of distant recurrence peaked at approximately 3 years and declined rapidly thereafter. Among the "other" group, the recurrence risk seemed to be constant over the period of follow-up. ::: ::: ::: CONCLUSIONS ::: Triple-negative breast cancers have a more aggressive clinical course than other forms of breast cancer, but the adverse effect is transient.


title: An Investigation of Noise-Tolerant Relational Concept Learning Algorithms

abstract: We discuss the types of noise that may occur in relational learning systems and describe two approaches to addressing noise in a relational concept learning algorithm. We then evaluate each approach experimentally.


title: On the design of deformable input- / state-lattice graphs

abstract: In this paper we describe a novel and simple to implement yet effective lattice design algorithm, which simultaneously produces input and state-space sampled lattice graphs. The presented method is an extension to the ideas suggested by Bicchi et al. on input lattices and is applicable to systems which can be brought into (2,n) chained form, such as kinematic models of unicycles, bicycles, differential-drive robots and car-like vehicles (pulling several trailers). We further show that a transformation from chained form to path coordinates allows the resulting lattice to be bent along any C1 continuous path. We exploit this fact by shaping it along the skeleton of arbitrary structured environments, such as the center of road lanes and corridors. In our experiments in both structured (i.e. on-road) and unstructured (i.e. parking lot) scenarios, we successfully demonstrate for the first time the applicability of lattice-based planning approaches to search queries in arbitrary environments.


Putrevu / Exploring the Origins and Information Processing Differences Between Men and Women 1 EXPLORING THE ORIGINS AND INFORMATION PROCESSING DIFFERENCES BETWEEN MEN AND WOMEN : IMPLICATIONS FOR ADVERTISERS


title: Fine-Grained Named Entity Classification with Wikipedia Article Vectors

abstract: This paper addresses the task of assigning multiple labels of fine-grained named entity (NE) types to Wikipedia articles. To address the sparseness of the input feature space, which is salient particularly in fine-grained type classification, we propose to learn article vectors (i.e. entity embeddings) from hypertext structure of Wikipedia using a Skip-gram model and incorporate them into the input feature set. To conduct large-scale practical experiments, we created a new dataset containing over 22,000 manually labeled instances. The results of our experiments show that our idea gained statistically significant improvements in classification results.


title: Vitamin D intake is inversely associated with rheumatoid arthritis: results from the Iowa Women's Health Study.

abstract: OBJECTIVE ::: Vitamin D is a potent regulator of calcium homeostasis and may have immunomodulatory effects. The influence of vitamin D on human autoimmune disease has not been well defined. The purpose of this study was to evaluate the association of dietary and supplemental vitamin D intake with rheumatoid arthritis (RA) incidence. ::: ::: ::: METHODS ::: We analyzed data from a prospective cohort study of 29,368 women of ages 55-69 years without a history of RA at study baseline in 1986. Diet was ascertained using a self-administered, 127-item validated food frequency questionnaire that included supplemental vitamin D use. Risk ratios (RRs) and 95% confidence intervals (95% CIs) were estimated using Cox proportional hazards regression, adjusting for potential confounders. ::: ::: ::: RESULTS ::: Through 11 years of followup, 152 cases of RA were validated against medical records. Greater intake (highest versus lowest tertile) of vitamin D was inversely associated with risk of RA (RR 0.67, 95% CI 0.44-1.00, P for trend = 0.05). Inverse associations were apparent for both dietary (RR 0.72, 95% CI 0.46-1.14, P for trend = 0.16) and supplemental (RR 0.66, 95% CI 0.43-1.00, P for trend = 0.03) vitamin D. No individual food item high in vitamin D content and/or calcium was strongly associated with RA risk, but a composite measure of milk products was suggestive of an inverse association with risk of RA (RR 0.66, 95% CI 0.42-1.01, P for trend = 0.06). ::: ::: ::: CONCLUSION ::: Greater intake of vitamin D may be associated with a lower risk of RA in older women, although this finding is hypothesis generating.


title: Sending mixed signals: multilevel reputation effects in peer-to-peer lending markets

abstract: Online peer-to-peer (P2P) lending organizations enable an individual to obtain an unsecured loan from a collection of individuals without the participation of a bank. Previous research has addressed the use of reputation systems to reduce information asymmetry based on individual history within online markets. Within the last few years one of the market leaders in P2P lending, Prosper.com, has sought to replace the information vetting and monitoring typically done by the bank with a community of users free to select its community members based on any criteria it chooses. By embedding individual reputations within a community reputation, incentives become aligned for peers to select highly qualified borrowers and produce more costly information signals to reduce the adverse selection and moral hazard risk typical of any principle-agent relationship. This study draws on theory from the Principle-Agent perspective to empirically examine the signals that enhance community reputation.


title: Private Circuits: Securing Hardware against Probing Attacks

abstract: Can you guarantee secrecy even if an adversary can eavesdrop on your brain? We consider the problem of protecting privacy in circuits, when faced with an adversary that can access a bounded number of wires in the circuit. This question is motivated by side channel attacks, which allow an adversary to gain partial access to the inner workings of hardware. Recent work has shown that side channel attacks pose a serious threat to cryptosystems implemented in embedded devices. In this paper, we develop theoretical foundations for security against side channels. In particular, we propose several efficient techniques for building private circuits resisting this type of attacks. We initiate a systematic study of the complexity of such private circuits, and in contrast to most prior work in this area provide a formal threat model and give proofs of security for our constructions.


title: Security ontology: Simulating threats to corporate assets

abstract: Threat analysis and mitigation, both essential for corporate security, are time consuming, complex and demand expert knowledge. We present an approach for simulating threats to corporate assets, taking the entire infrastructure into account. Using this approach effective countermeasures and their costs can be calculated quickly without expert knowledge and a subsequent security decisions will be based on objective criteria. The ontology used for the simulation is based on Landwehr's [ALRL04] taxonomy of computer security and dependability.


title: Contrastive Learning Using Spectral Methods

abstract: In many natural settings, the analysis goal is not to characterize a single data set in isolation, but rather to understand the difference between one set of observations and another. For example, given a background corpus of news articles together with writings of a particular author, one may want a topic model that explains word patterns and themes specific to the author. Another example comes from genomics, in which biological signals may be collected from different regions of a genome, and one wants a model that captures the differential statistics observed in these regions. This paper formalizes this notion of contrastive learning for mixture models, and develops spectral algorithms for inferring mixture components specific to a foreground data set when contrasted with a background data set. The method builds on recent moment-based estimators and tensor decompositions for latent variable models, and has the intuitive feature of using background data statistics to appropriately modify moments estimated from foreground data. A key advantage of the method is that the background data need only be coarsely modeled, which is important when the background is too complex, noisy, or not of interest. The method is demonstrated on applications in contrastive topic modeling and genomic sequence analysis.


title: DemNet: A Convolutional Neural Network for the detection of Alzheimer's Disease and Mild Cognitive Impairment

abstract: The early diagnosis of Alzheimer's Disease (AD) and its prodromal form, Mild Cognitive Impairment (MCI), has been the subject of extensive research in recent years. Some recent studies have shown promising results in the diagnosis of AD and MCI using structural Magnetic Resonance Imaging (MRI) scans. In this paper, we propose the use of a Convolutional Neural Network (CNN) in the detection of AD and MCI. In particular, we modified the 16-layered VGGNet for the 3-way classification of AD, MCI and Healthy Controls (HC) on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset achieving an overall accuracy of 91.85% and outperforming several classifiers from other studies.


title: A planar wideband Quasi-Yagi antenna with high gain and FTBR

abstract: This paper presents the design of a planar Quasi-Yagi antenna capable of achieving high Front-to-Back ratio (i.e. FTBR > 34 dB), high gain (i.e. > 6.4 dBi) and relatively wide bandwidth (i.e. up to almost 1 GHz). This antenna is designed to cover the 2.45 GHz ISM band. The overall dimensions of the antenna are 69 × 64 × 1.575 mm3. The antenna is made up of 5 director elements, 1 driven dipole and a reflector ground plane. Wide bandwidth is made possible through the strong coupling of the first director element and the driven dipole element. The antenna is optimized in order to achieve the above mentioned performance criteria. This antenna can be very useful for applications requiring highly directive radiation patterns such as point-to-point communications and wireless power transfer. The radiation characteristics of this antenna can be further enhanced by building a phased array based on it.


title: Variational Kullback-Leibler divergence for Hidden Markov models

abstract: Divergence measures are widely used tools in statistics and pattern recognition. The Kullback-Leibler (KL) divergence between two hidden Markov models (HMMs) would be particularly useful in the fields of speech and image recognition. Whereas the KL divergence is tractable for many distributions, including Gaussians, it is not in general tractable for mixture models or HMMs. Recently, variational approximations have been introduced to efficiently compute the KL divergence and Bhattacharyya divergence between two mixture models, by reducing them to the divergences between the mixture components. Here we generalize these techniques to approach the divergence between HMMs using a recursive backward algorithm. Two such methods are introduced, one of which yields an upper bound on the KL divergence, the other of which yields a recursive closed-form solution. The KL and Bhattacharyya divergences, as well as a weighted edit-distance technique, are evaluated for the task of predicting the confusability of pairs of words.


title: An UWB-UHF semi-passive RFID System for localization and tracking applications

abstract: We present a novel radio-frequency identification (RFID) system with capability of localization and tracking of passive or semi-passive tags. Localization and tracking features are enabled by backscatter modulation on ultra-wide bandwidth tag's antenna. A ultra-high frequency signal allows the wake-up of the tags enabling the reduction of energy consumption and ensuring compatibility with existing RFID systems. The overall system as well as the reader and tag architectures are introduced. The localization and tracking performance evaluation is presented in some reference scenarios.


title: Optimal redundancy resolution with task scaling under hard bounds in the robot joint space

abstract: For robots that are redundant with respect to a given task, we present an optimal differential kinematic inversion method in the presence of hard bounds on joint range, joint velocity, and joint acceleration. These hard bounds specify the robot motion capabilities that cannot be exceeded at any time. On the other hand, scaling of the desired task trajectory is allowed whenever the robot capabilities are insufficient to execute the original task. For a problem formulated in this way, we have recently presented the Saturation in the Null Space (SNS) algorithm that produces an efficient solution, based on Jacobian pseudoinversion and recovery in the null space of the saturation effects of a reduced number of joint velocity commands. To investigate the optimality properties of the SNS algorithm, we recast the problem as a constrained quadratic programming (QP) problem, in which the joint velocity norm as well as the task scaling are to be minimized. Its solution leads to a variant of the original algorithm, the Optimal Saturation in the Null Space (Opt-SNS). The Opt-SNS guarantees an optimal solution also when the basic SNS fails to do so and improves the numerical performance over the state-of-the-art QP solver. The possible existence of discontinuous solutions for the formulated problem is avoided by the introduction of a task scaling margin. The extension to the multi-task case is also presented. Simulation results for the 7R lightweight KUKA LWR IV robot illustrate the properties and computational efficiency of the new algorithm.


title: Detecting Driver Drowsiness: A survey of system designs and technology.

abstract: Driving and transporting goods are necessary for human activity. As a consequence of drivers spending a considerable amount of time at the workplace, and usually under pressure, vehicular accidents have become a great contributor to mortality in several countries. Traffic accidents in countries such as the United States are a central concern. For instance, the U.S. National Highway Traffic Safety Administration (NHTSA) Fatality Analysis Reporting System Encyclopedia [1] shows that there were approximately 55,926 vehicles involved in collisions in 2007, 9,797 of which were due to driver fatigue and inattention. The reported driver-related factors include the driver was drowsy, sleepy, asleep, and/or fatigued, the driver was under the influence of alcohol, drugs, and/or medication, the driver was inattentive (talking, eating, etc.), a cellular telephone was present in the vehicle, a cellular telephone was in use in vehicle.


title: Forecasting Stock Time-Series using Data Approximation and Pattern Sequence Similarity

abstract: Time series analysis is the process of building a model using statistical techniques to represent characteristics of time series data. Processing and forecasting huge time series data is a challenging task. This paper presents Approximation and Prediction of Stock Time-series data (APST), which is a two step approach to predict the direction of change of stock price indices. First, performs data approximation by using the technique called Multilevel Segment Mean (MSM). In second phase, prediction is performed for the approximated data using Euclidian distance and Nearest-Neighbour technique. The computational cost of data approximation is O(n ni) and computational cost of prediction task is O(m |NN|). Thus, the accuracy and the time required for prediction in the proposed method is comparatively efficient than the existing Label Based Forecasting (LBF) method [1].


Building Trust in a Human-Robot Team with Automatically Generated Explanations


title: Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games

abstract: Reinforcement learning (RL) is an area of research that has blossomed tremendously in recent years and has shown remarkable potential for artificial intelligence based opponents in computer games. This success is primarily due to the vast capabilities of convolutional neural networks, that can extract useful features from noisy and complex data. Games are excellent tools to test and push the boundaries of novel RL algorithms because they give valuable insight into how well an algorithm can perform in isolated environments without the real-life consequences. Real-time strategy games (RTS) is a genre that has tremendous complexity and challenges the player in short and long-term planning. There is much research that focuses on applied RL in RTS games, and novel advances are therefore anticipated in the not too distant future. However, there are to date few environments for testing RTS AIs. Environments in the literature are often either overly simplistic, such as microRTS, or complex and without the possibility for accelerated learning on consumer hardware like StarCraft II. This paper introduces the Deep RTS game environment for testing cutting-edge artificial intelligence algorithms for RTS games. Deep RTS is a high-performance RTS game made specifically for artificial intelligence research. It supports accelerated learning, meaning that it can learn at a magnitude of 50 000 times faster compared to existing RTS games. Deep RTS has a flexible configuration, enabling research in several different RTS scenarios, including partially observable state-spaces and map complexity. We show that Deep RTS lives up to our promises by comparing its performance with microRTS, ELF, and StarCraft II on high-end consumer hardware. Using Deep RTS, we show that a Deep Q-Network agent beats random-play agents over 70% of the time. Deep RTS is publicly available at https://github.com/cair/DeepRTS.


NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager


title: Improving Efficiency of Autonomous Vehicles by V2V Communication

abstract: Autonomous vehicles are widely regarded as a promising technology to improve the safety of transportation systems. However, the efficiency of vehicles may be compromised to ensure safety when there are large uncertainties in perception and prediction of the behaviors of other road participants due to limitations in sensors. To remedy this problem, vehicle to vehicle (V2V) communication is applied to improve efficiency of autonomous vehicles during interactions with other vehicles. By requiring the vehicles to communicate their intentions with one another, the efficiency of the vehicles can be improved in terms of smaller variations in their speed profiles and smaller delay as demonstrated in the simulations.


title: Chromatic SSVEP BCI paradigm targeting the higher frequency EEG responses

abstract: A novel approach to steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) is presented in the paper. To minimize possible side-effects of the monochromatic light SSVEP-based BCI we propose to utilize chromatic green-blue flicker stimuli in higher, comparing to the traditionally used, frequencies. The developed safer SSVEP responses are processed an classified with features drawn from EEG power spectra. Results obtained from healthy users support the research hypothesis of the chromatic and higher frequency SSVEP. The feasibility of proposed method is evaluated in a comparison of monochromatic versus chromatic SSVEP responses. We also present preliminary results with empirical mode decomposition (EMD) adaptive filtering which resulted with improved classification accuracies.


title: Bluetooth: Vision, Goals, and Architecture

abstract: A few years ago it was recognized that the vision of a truly low-cost, low-power radio-based cable replacement was feasible. Such a ubiquitous link would provide the basis for portable devices to communicate together in an ad hoc fashion by creating personal area networks which have similar advantages to their office environment counterpart - the local area network (LAN). Bluetooth is an effort by a consortium of companies to design a royalty free technology specification enabling this vision. This article describes the vision and goals of the Bluetooth program and introduces the radio-based technology.


title: Tactile Displays: Guidance for Their Design and Application

abstract: OBJECTIVE ::: This article provides an overview of tactile displays. Its goal is to assist human factors practitioners in deciding when and how to employ the sense of touch for the purpose of information representation. The article also identifies important research needs in this area. ::: ::: ::: BACKGROUND ::: First attempts to utilize the sense of touch as a medium for communication date back to the late 1950s. For the next 35 years progress in this area was relatively slow, but recent years have seen a surge in the interest and development of tactile displays and the integration of tactile signals in multimodal interfaces. A thorough understanding of the properties of this sensory channel and its interaction with other modalities is needed to ensure the effective and robust use of tactile displays. ::: ::: ::: METHODS ::: First, an overview of vibrotactile perception is provided. Next, the design of tactile displays is discussed with respect to available technologies. The potential benefit of including tactile cues in multimodal interfaces is discussed. Finally, research needs in the area of tactile information presentation are highlighted. ::: ::: ::: RESULTS ::: This review provides human factors researchers and interface designers with the requisite knowledge for creating effective tactile interfaces. It describes both potential benefits and limitations of this approach to information presentation. ::: ::: ::: CONCLUSION ::: The sense of touch represents a promising means of supporting communication and coordination in human-human and human-machine systems. ::: ::: ::: APPLICATION ::: Tactile interfaces can support numerous functions, including spatial orientation and guidance, attention management, and sensory substitution, in a wide range of domains.


title: Multicast routing protocols in wireless mesh networks: a survey

abstract: Wireless mesh networks (WMNs) introduce a new type of network that has been applied over the last few years. One of the most important developing issues in WMNs is multicast routing, which is a key technology that provides dissemination of data to a group of members in an efficient way. In this article, after an introduction about the structure of a WMN, multicast routing algorithms and protocols in WMNs are surveyed in a detailed and efficient manner. Moreover, effort is made to scale the study into one of the important potential capabilities of multicast routing mechanisms in WMNs, which is taking advantage of using different channels and radios association. While nodes in a single-radio mesh network operating on single-channel have restrictions for capacity, equipping mesh routers with multiple radios using multiple channels can decrease the intention of capacity problem as well as increase the aggregate bandwidth available to the network and improving the throughput. Hence, the purpose of channel assignment is to decrease the interferences while increasing the network capacity and keeping the connectivity of the network. Therefore, this article investigates the multicast protocols considering a definition of three types of WMNs, based on channel-radio association including SRSC, SRMC and MRMC. In its follow, a classification for multicast routing algorithms regarding the achieved optimal solutions will be presented. Finally, a study of MRMC and its relevant problems will be offered, considering the joint channel assignment and the multicast tree construction problem.


title: A Comparative Analysis of Particle Swarm Optimization and K-means Algorithm For Text Clustering Using Nepali Wordnet

abstract: The volume of digitized text documents on the web have been increasing rapidly. As there is huge collection of data on the web there is a need for grouping(clustering) the documents into clusters for speedy information retrieval. Clustering of documents is collection of documents into groups such that the documents within each group are similar to each other and not to documents of other groups. Quality of clustering result depends greatly on the representation of text and the clustering algorithm. This paper presents a comparative analysis of three algorithms namely K-means, Particle swarm Optimization (PSO) and hybrid PSO+K-means algorithm for clustering of text documents using WordNet. The common way of representing a text document is bag of terms. The bag of terms representation is often unsatisfactory as it does not exploit the semantics. In this paper, texts are represented in terms of synsets corresponding to a word. Bag of terms data representation of text is thus enriched with synonyms from WordNet. K-means, Particle Swarm Optimization (PSO) and hybrid PSO+K-means algorithms are applied for clustering of text in Nepali language. Experimental evaluation is performed by using intra cluster similarity and inter cluster similarity.


2 The New Organizing Logic of Digital Innovation : An Agenda for Information Systems Research 1


title: Illuminant-invariant model-based road segmentation

abstract: Road segmentation is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following or vehicle detection and tracking. Significant efforts have been made in order to solve this task using vision-based techniques. One of the major challenges of these techniques is dealing with lighting variations, especially shadows. Many of the approaches presented within this field use ad-hoc mechanisms applied after an initial segmentation to recover shadowed road patches. In this paper, we present an innovative method to obtain a road segmentation algorithm robust to extreme shadow conditions. The novelty of the proposal is the use of a shadowless feature space in combination with a model-based region growing algorithm. The former projects the color images such that the shadow effect is greatly attenuated. The latter uses histogram models to label the pixels as belonging to the road or to the background. These models are constructed on a frame by frame basis independently of the road shape to avoid limitations when addressing unstructured roads. The results presented show the validity of our approach.


title: Signal Processing and Classification Approaches for Brain-Computer Interface

abstract: Research on brain-computer interface (BCI) systems began in the 1970s at the University of California Los Angeles (UCLA) (Vidal, 1973; 1977). The author gave in his papers the expression "Brain Computer Interface" which is the term currently used in literature. A BCI system is a direct communication pathway between a brain and an external artificial device. BCI systems were aimed at assisting, augmenting or repairing human cognitive or sensory-motor functions. The BCI systems (BCIs) allow control of an artificial device based on the features extracted from voluntary electric, magnetic, or other physical manifestations of brain activity collected from epior subdurally from the cortex or from the scalp or in invasive electrophysiological manner, i.e. brain signals recorded intracortically with single electrode or multi-electrode arrays (Dornhege et al., 2007). There is a variety of non-invasive techniques for measuring brain activity. These non-invasive techniques include, the electroencephalography (EEG), magnetoencephalography (MEG), positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and optical imaging. However, for technical, time resolution, realtime, and price constraints, only EEG monitoring and related techniques are employed in the BCI community. For more details refer to (Wolpaw et al., 2002; Mason et al., 2007; Dobkin, 2007). The neuronal electrical activity contain a broad band frequency, so the monitored brain signals are filtered and denoised to extract the relevant information (see section 3) and finally this information is decoded (see section 6) and commuted into device commands by synchronous control or more efficiently by self-paced or asynchronous control in order to detect whether a user is intending something or not (see chapter 7 in (Dornhege et al., 2007) for details), Fig. 1. For some specific BCI tasks, raw brain signal serves as stimulus as well as a control interface feedback. The direct BCIs can be seen as a new means of communication that may be used to allow tetraplegic or individuals with severe motor or neuromuscular diseases (e.g. Amyotrophic lateral sclerosis (ALS), brainstem stroke, brain or spinal cord injury, cerebral palsy, muscular


title: Position Sensorless Control Without Phase Shifter for High-Speed BLDC Motors With Low Inductance and Nonideal Back EMF

abstract: This paper presents a novel method for position sensorless control of high-speed brushless DC motors with low inductance and nonideal back electromotive force (EMF) in order to improve the reliability of the motor system of a magnetically suspended control moment gyro for space application. The commutation angle error of the traditional line-to-line voltage zero-crossing points detection method is analyzed. Based on the characteristics measurement of the nonideal back EMF, a two-stage commutation error compensation method is proposed to achieve the high-reliable and high-accurate commutation in the operating speed region of the proposed sensorless control process. The commutation angle error is compensated by the transformative line voltages, the hysteresis comparators, and the appropriate design of the low-pass filters in the low-speed and high-speed region, respectively. High-precision commutations are achieved especially in the high-speed region to decrease the motor loss in steady state. The simulated and experimental results show that the proposed method can achieve an effective compensation effect in the whole operating speed region.


Host-based Intrusion Detection and Prevention System (HIDPS)


Spherical Camera Localization in Man-made Environment Using 3 D-2 D Matching of Line Information


title: Low Power and High Speed Optimized 4-bit Array Multiplier Using MOD-GDI Technique

abstract: Multipliers are the most commonly used elements in today's digital devices. In order to achieve high data throughput in digital signal processing systems, hardware multiplication is the important factor. Depending on the applications which are emerging with the electronics devices, various types of multipliers are emerged. Among all the multipliers, the basic multiplier is Array Multiplier. This paper aims at design of an optimized, low power and high speed 4- bit array multiplier by proposing Modified Gate Diffusion Input (MOD-GDI) technique. With this technique the total propagation delay, power dissipation, and no. of transistors required to design are much more decreased than compared to the Gate Diffusion Input (GDI) and CMOS techniques. Simulations are carried out on mentor graphics tools with 90nm Process technology.


title: A compact FPGA-based processor for the Secure Hash Algorithm SHA-256

abstract: This work reports an efficient and compact FPGA processor for the SHA-256 algorithm. The novel processor architecture is based on a custom datapath that exploits the reusing of modules, having as main component a 4-input Arithmetic-Logic Unit not previously reported. This ALU is designed as a result of studying the type of operations in the SHA algorithm, their execution sequence and the associated dataflow. The processor hardware architecture was modeled in VHDL and implemented in FPGAs. The results obtained from the implementation in a Virtex5 device demonstrate that the proposed design uses fewer resources achieving higher performance and efficiency, outperforming previous approaches in the literature focused on compact designs, saving around 60% FPGA slices with an increased throughput (Mbps) and efficiency (Mbps/Slice). The proposed SHA processor is well suited for applications like Wi-Fi, TMP (Trusted Mobile Platform), and MTM (Mobile Trusted Module), where the data transfer speed is around 50Mbps.


title: Comparison between the two definitions of AI

abstract: Two different definitions of the Artificial Intelligence concept have been proposed in papers [1] and [2]. The first definition is informal. It says that any program that is cleverer than a human being, is acknowledged as Artificial Intelligence. The second definition is formal because it avoids reference to the concept of human being. The readers of papers [1] and [2] might be left with the impression that both definitions are equivalent and the definition in [2] is simply a formal version of that in [1]. This paper will compare both definitions of Artificial Intelligence and, hopefully, will bring a better understanding of the concept.


title: Geometric and Textural Blending for 3D Model Stylization

abstract: Stylizing a 3D model with characteristic shapes or appearances is common in product design, particularly in the design of 3D model merchandise, such as souvenirs, toys, furniture, and stylized items. A model stylization approach is proposed in this study. The approach combines base and style models while preserving user-specified shape features of the base model and the attractive features of the style model with limited assistance from a user. The two models are first combined at the topological level. A tree-growing technique is utilized to search for all possible combinations of the two models. Second, the models are combined at textural and geometric levels by employing a morphing technique. Results show that the proposed approach generates various appealing models and allows users to control the diversity of the output models and adjust the blending degree between the base and style models. The results of this work are also experimentally compared with those of a recent work through a user study. The comparison indicates that our results are more appealing, feature-preserving, and reasonable than those of the compared previous study. The proposed system allows product designers to easily explore design possibilities and assists novice users in creating their own stylized models.


title: A Comparative Study of use of the Library and the Internet as Sources of Information by Graduate Students in the University Of Ghana

abstract: 1.0 INTRODUCTION Information is a vital and an indispensable component of any academic environment. It makes for effectiveness in any academic system. Both faculty and students need to use information daily in their various academic endeavors. For decades, faculty and students have actively used the library and its resources as their main information source. Alemna, (2000) states that for centuries libraries have served as repositories of information and knowledge that have provided the vital underpinnings for socio- economic, political and cultural development in any civilization. Their relationship with cultural progress has been so interdependent that it is needless to argue whether man's cultural advancement merely produces libraries as by product. According to Robinson (2006) simplistically, libraries and archives came into being to provide a central location for hard-to-find, scarce, expensive or unique material. Scarcity of information is the basis for the modern library. In countries where information continues to be scarce, a library's role is still unambiguous. In some countries where access to information is now akin to access to electricity or water, the reason to have freestanding storehouses of a subset of all information is harder to articulate. Libraries in such countries can provide access to more information than any user could want or need. Rangathan's rule "for every reader, his or her book," might be now redefined as "for every reader, huge amounts of free-floating content, anywhere, anytime. We now live in the information age where access to many Internet resources is just a few clicks away. The Internet is a technology, which has gained more popularity in many countries across the world and Ghana, is no exception. The Internet as a medium of communication and source of information has enabled students, researchers, business information seekers and information professionals to access information to enhance their work and communicate effectively. Robinson (2006) states that in 2004, seventy million American adults logged onto the Internet in a typical day. Over 95 percent of U.S. public libraries provided Internet access. Students, many faculty, and laypeople turn to online information sources before print or the library. As a result, library use, especially for walk-in reference questions and preparation for school and college reports has declined. 1.1 Statement of the Problem The University of Ghana has a number of libraries on its campus. The Balme library is the biggest and the central library of the University. In addition to the Balme library there are various departmental, school, institution and hall libraries on campus. The collections of these libraries are subject specific. Almost all the departments under the faculties and schools of the university have their own libraries. The University gained full Internet connectivity in the early part of 1998 to enhance the opportunities available to the academic community Alemna and Adanu, (2005). The Internet was not meant to do away with research in the library. Although the Internet has a lot of advantages, it cannot be compared with that of the traditional sources. Graduate students have adopted and continue to use the online information retrieval for their academic and research work at the expense of or without considering the importance and the quality of the traditional information centers as observed by the researcher. However, merely using the Internet was not guarantee quality and good information. Even though the Internet has large amount of information, the relevance, quality, and authenticity should not be neglected. The question to ask then is why do the graduate students continue or preferred using the Internet to the library as sources of information? Should the importance, quality, and authentic information derived from the library be relegated in place of the Internet? …


title: Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features

abstract: Corporate earnings are a crucial indicator for investment and business valuation. Despite their importance and the fact that classic econometric approaches fail to match analyst forecasts by orders of magnitude, the automatic prediction of corporate earnings from public data is not in the focus of current machine learning research. In this paper, we present for the first time a fully automatized machine learning method for earnings prediction that at the same time a) only relies on publicly available data and b) can outperform human analysts. The latter is shown empirically in an experiment involving all S&P 100 companies in a test period from 2008 to 2012. The approach employs a simple linear regression model based on a novel feature space of stock market prices and their pair wise correlations. With this work we follow the recent trend of now casting, i.e., of creating accurate contemporary forecasts of undisclosed target values based on publicly observable proxy variables.


title: Multi-DOF Counterbalance Mechanism for a Service Robot Arm

abstract: Low-cost but high-performance robot arms are required for widespread use of service robots. Most robot arms use expensive motors and speed reducers to provide torques sufficient to support the robot mass and payload. If the gravitational torques due to the robot mass, which is usually much greater than the payload, can be compensated for by some means; the robot would need much smaller torques, which can be delivered by cheap actuator modules. To this end, we propose a novel counterbalance mechanism which can completely counterbalance the gravitational torques due to the robot mass. Since most 6-DOF robots have three pitch joints, which are subject to gravitational torques, we propose a 3-DOF counterbalance mechanism based on the double parallelogram mechanism, in which reference planes are provided to each joint for proper counterbalancing. A 5-DOF counterbalance robot arm was built to demonstrate the performance of the proposed mechanism. Simulation and experimental results showed that the proposed mechanism had effectively decreased the torque required to support the robot mass, thus allowing the prospective use of low-cost motors and speed reducers for high-performance robot arms.


title: Image Denoising Using the Higher Order Singular Value Decomposition

abstract: In this paper, we propose a very simple and elegant patch-based, machine learning technique for image denoising using the higher order singular value decomposition (HOSVD). The technique simply groups together similar patches from a noisy image (with similarity defined by a statistically motivated criterion) into a 3D stack, computes the HOSVD coefficients of this stack, manipulates these coefficients by hard thresholding, and inverts the HOSVD transform to produce the final filtered image. Our technique chooses all required parameters in a principled way, relating them to the noise model. We also discuss our motivation for adopting the HOSVD as an appropriate transform for image denoising. We experimentally demonstrate the excellent performance of the technique on grayscale as well as color images. On color images, our method produces state-of-the-art results, outperforming other color image denoising algorithms at moderately high noise levels. A criterion for optimal patch-size selection and noise variance estimation from the residual images (after denoising) is also presented.


title: Intelligent universal transformer design and applications

abstract: Legacy transformers are passive, bulky, becoming expensive, and take longer time to deliver. They cannot provide the power quality or control which today's loads demand for proper functioning and the electric system needs for its survivability. Solid-state transformers have been promising technologies in recent years. EPRI is pursuing development of an innovative solution - the UTtrade (Intelligent Universal Transformer), based on R&D100 Award winner SGTO devices, advanced thermal- management technology and packaging concepts to provide flexible, precise quality and reliable power at affordable costs. The IUTtrade is a multi-function programmable power processing device ideal for Smart Grid and Sustainable Energy initiatives. This paper describes the design and application of this device.


title: Measuring contextual citation impact of scientific journals

abstract: This paper explores a new indicator of journal citation impact, denoted as source normalized impact per paper (SNIP). It measures a journal's contextual citation impact, taking into account characteristics of its properly defined subject field, especially the frequency at which authors cite other papers in their reference lists, the rapidity of maturing of citation impact, and the extent to which a database used for the assessment covers the field's literature. It further develops Eugene Garfield's notions of a field's ‘citation potential’ defined as the average length of references lists in a field and determining the probability of being cited, and the need in fair performance assessments to correct for differences between subject fields. A journal's subject field is defined as the set of papers citing that journal. SNIP is defined as the ratio of the journal's citation count per paper and the citation potential in its subject field. It aims to allow direct comparison of sources in different subject fields. Citation potential is shown to vary not only between journal subject categories – groupings of journals sharing a research field – or disciplines (e.g., journals in mathematics, engineering and social sciences tend to have lower values than titles in life sciences), but also between journals within the same subject category. For instance, basic journals tend to show higher citation potentials than applied or clinical journals, and journals covering emerging topics higher than periodicals in classical subjects or more general journals. SNIP corrects for such differences. Its strengths and limitations are critically discussed, and suggestions are made for further research. All empirical results are derived from Elsevier's Scopus.


title: Cognitive failures in daily life: Exploring the link with Internet addiction and problematic mobile phone use

abstract: Both the OCS and MPPUS were significantly positively correlated to scores on the CFQ.A significant difference between high and low scoring groups for both the MPPUS and the OCS and scores on the CFQ.Individuals in the higher groups presenting greater self reported cognitive failures. A questionnaire-based study aimed to explore the link between Internet addiction, problematic mobile phone use and the occurrence of cognitive failures in daily life. Previous research has suggested that individuals who have lower working memory capacity (WMC) and poorer attentional control (AC) maybe poorer at limiting the distraction effect posed by access to communicative digital media such as the Internet and mobile phones (Unsworth, McMillan, Brewer, & Spillers, 2012). 210 participants completed an online questionnaire which comprised of the Online Cognition Scale (OCS; Davis, Flett, & Besser, 2002), the Problematic Mobile Phone Use Scale (MPPUS; Bianchi & Phillips, 2005) and the Cognitive Failures Questionnaire (CFQ; Broadbent, Cooper, FitzGerald, & Parkes, 1982). Both the OCS and MPPUS were significantly positively correlated to scores on the CFQ. Further analysis revealed a significant difference between high and low scoring groups for both the MPPUS and the OCS and scores on the CFQ, with those in the higher groups presenting greater self reported cognitive failures. The results are interpreted as being symptomatic of individuals in the higher OCS and MPPUS groups as being less resilient to the distractions posed by digital media and technology with a suggested link to lower WMC and AC.


title: The Genetics of Transcription Factor DNA Binding Variation

abstract: Most complex trait-associated variants are located in non-coding regulatory regions of the genome, where they have been shown to disrupt transcription factor (TF)-DNA binding motifs. Variable TF-DNA interactions are therefore increasingly considered as key drivers of phenotypic variation. However, recent genome-wide studies revealed that the majority of variable TF-DNA binding events are not driven by sequence alterations in the motif of the studied TF. This observation implies that the molecular mechanisms underlying TF-DNA binding variation and, by extrapolation, inter-individual phenotypic variation are more complex than originally anticipated. Here, we summarize the findings that led to this important paradigm shift and review proposed mechanisms for local, proximal, or distal genetic variation-driven variable TF-DNA binding. In addition, we discuss the biomedical implications of these findings for our ability to dissect the molecular role(s) of non-coding genetic variants in complex traits, including disease susceptibility.


Predicting Student Progress from Peer-Assessment Data


title: Analyses of Triaxial Accelerometer Calibration Algorithms

abstract: This paper proposes a calibration procedure in order to minimize the process time and cost. It relies on the suggestion of optimal positions, in which the calibration procedure takes place, and on position number optimization. Furthermore, this paper describes and compares three useful calibration algorithms applicable on triaxial accelerometer to determine its mathematical error model without a need to use an expensive and precise calibration means, which is commonly required. The sensor error model (SEM) of triaxial accelerometer consists of three scale-factor errors, three nonorthogonality angles, and three offsets. For purposes of calibration, two algorithms were tested-the Levenberg-Marquardt and the Thin-Shell algorithm. Both were then related to algorithm based on Matlab fminunc function to analyze their efficiency and results. The proposed calibration procedure and applied algorithms were experimentally verified on accelerometers available on market. We performed various analyses of proposed procedure and proved its capability to estimate the parameters of SEM without a need of precise calibration means, with minimum number of iteration, both saving time, workload, and costs.


title: Visual marker detection and decoding in AR systems: a comparative study

abstract: Visual markers are widely used in existing augmented reality (AR) applications. In most of such applications, the performance of an AR system depends highly on the tracking system for visual marker detection, tracking, and pose estimation. Currently, there are more than one marker based tracking/calibration systems available. It is thus desirable for the user to know which marker tracking system is likely to perform the best for a specific AR application. For this purpose, we compare several marker systems all using planar square coded visual markers. We present the evaluation results, both qualitatively and quantitatively, for the usability, efficiency, accuracy, and reliability. For a particular AR application, there are different marker detection and tracking requirements. Therefore, the purpose of this work is not to rank existing marker systems; instead, we try to analyze the strength and weakness of various aspects of the marker tracking systems and provide AR application developers with this information.


title: Hipsters on Networks: How a Small Group of Individuals Can Lead to an Anti-Establishment Majority

abstract: The spread of opinions, memes, diseases, and "alternative facts" in a population depends both on the details of the spreading process and on the structure of the social and communication networks on which they spread. One feature that can change spreading dynamics substantially is heterogeneous behavior among different types of individuals in a social network. In this paper, we explore how \textit{anti-establishment} nodes (e.g., \textit{hipsters}) influence spreading dynamics of two competing products. We consider a model in which spreading follows a deterministic rule for updating node states in which an adjustable fraction $p_{\rm Hip}$ of the nodes in a network are hipsters, who always choose to adopt the product that they believe is the less popular of the two. The remaining nodes are conformists, who choose which product to adopt by considering only which products their immediate neighbors have adopted. We simulate our model on both synthetic and real networks, and we show that the hipsters have a major effect on the final fraction of people who adopt each product: even when only one of the two products exists at the beginning of the simulations, a very small fraction of hipsters in a network can still cause the other product to eventually become more popular. Our simulations also demonstrate that a time delay $\tau$ in the knowledge of the product distribution in a population has a large effect on the final distribution of product adoptions. Our simple model and analysis may help shed light on the road to success for anti-establishment choices in elections, as such success --- and qualitative differences in final outcomes between competing products, political candidates, and so on --- can arise rather generically from a small number of anti-establishment individuals and ordinary processes of social influence on normal individuals.


title: Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment

abstract: Abstract A novel approach for unsupervised domain adaptation for neural networks is proposed. It relies on metric-based regularization of the learning process. The metric-based regularization aims at domain-invariant latent feature representations by means of maximizing the similarity between domain-specific activation distributions. The proposed metric results from modifying an integral probability metric such that it becomes less translation-sensitive on a polynomial function space. The metric has an intuitive interpretation in the dual space as the sum of differences of higher order central moments of the corresponding activation distributions. Under appropriate assumptions on the input distributions, error minimization is proven for the continuous case. As demonstrated by an analysis of standard benchmark experiments for sentiment analysis, object recognition and digit recognition, the outlined approach is robust regarding parameter changes and achieves higher classification accuracies than comparable approaches.


title: Comparison of Compositional and Morphological Atom-Probe Tomography Analyses for a Multicomponent Fe-Cu Steel

abstract: A multicomponent Fe-Cu based steel is studied using atom-probe tomography. The precipitates are identified using two different methodologies and subsequent morphological and compositional results are compared. The precipitates are first identified using a maximum separation distance algorithm, the envelope method, and then by a concentration threshold method, an isoconcentration surface. We discuss in detail the proper selection of the parameters needed to delineate precipitates utilizing both methods. The results of the two methods exhibit a difference of 44 identified precipitates, which can be attributed to differences in the basis of both methods and the sensitivity of our results to user-prescribed parameters. The morphology of the precipitates, characterized by four different precipitate radii and precipitate size distribution functions ~PSDs!, are compared and evaluated. A variation of less than ;8% is found between the different radii. Two types of concentration profiles are compared, giving qualitatively similar results. Both profiles show Cu-rich precipitates containing Fe with elevated concentrations of Ni, Al, and Mn near the heterophase interfaces. There are, however, quantitative disagreements due to differences in the basic foundations of the two analysis methods.


title: Material property of on-metal magnetic sheet attached on NFC/HF-RFID antenna and research of its proper pattern and size on

abstract: When a payment system with NFC/HF-RFID is installed in smart-phone, their communication with 13.56MHz is blocked by such metal as battery, coil and PCB. To solve this problem, magnetic sheet with high permeability is set between NFC/HF-RFID antenna and near-by metal. So far thin compound magnetic sheet or thin sintered ferrite has been used. In order to make thickness of these materials thinner, we propose amorphous magnetic sheet. Besides this amorphous magnetic sheet causes to increase the transmission effect.


title: Are They Different? Affect, Feeling, Emotion, Sentiment, and Opinion Detection in Text

abstract: A major limitation in the automatic detection of affect, feelings, emotions, sentiments, and opinions in text is the lack of proper differentiation between these subjective terms and understanding of how they relate to one another. This lack of differentiation not only leads to inconsistency in terminology usage but also makes the subtleties and nuances expressed by the five terms difficult to understand, resulting in subpar detection of the terms in text. In light of such limitation, this paper clarifies the differences between these five subjective terms and reveals significant concepts to the computational linguistics community for their effective detection and processing in text.


title: A convolution neural networks scheme for classification of motor imagery EEG based on wavelet time-frequecy image

abstract: Motor imagery classification using electroencephalogram (EEG) is increasingly becoming popular in brain-computer interface (BCI) field. In this paper, we present a novel convolution neural networks (CNN) approach for classifying motor imagery electroencephalogram (EEG). For this, we obtained time-frequency representations of EEGs in cases of left and right motor imageries using continuous wavelet transform (CWT). Through experiments using well known public benchmark dataset, it shows that the proposed method provides the improved accuracy compared to the traditional machine learning based classification methods. It confirms the usefulness of the CNN scheme for BCI research field.


title: SMIB power system model with PSS for transient stability studies

abstract: This paper presents the development of single machine infinite bus system (SMIB) model for transient stability studies with detailed synchronous machine model and a Power System Stabilizer (PSS) in Matlab/Simulink software. The proposed method of the SMIB simulator is computationally efficient and flexible for interfacing the synchronous machine with the external network and for extending to multimachine system representation. The Simulation on the SMIB for the machine model with manual control, with the excitation system included and with the excitation system and PSS is performed to evaluate the transient stability of the system when a three phase fault on the transmission line is occurred with different clearing times. The obtained results show an accurate performance of the model developed for stability studies.


title: Narrative Visualization: Telling Stories with Data

abstract: Data visualization is regularly promoted for its ability to reveal stories within data, yet these “data stories” differ in important ways from traditional forms of storytelling. Storytellers, especially online journalists, have increasingly been integrating visualizations into their narratives, in some cases allowing the visualization to function in place of a written story. In this paper, we systematically review the design space of this emerging class of visualizations. Drawing on case studies from news media to visualization research, we identify distinct genres of narrative visualization. We characterize these design differences, together with interactivity and messaging, in terms of the balance between the narrative flow intended by the author (imposed by graphical elements and the interface) and story discovery on the part of the reader (often through interactive exploration). Our framework suggests design strategies for narrative visualization, including promising under-explored approaches to journalistic storytelling and educational media.


Infiltration/Inflow Assessment and Detection in Urban Sewer System


ADAM: Detecting Intrusions by Data Mining


History and Evolution of GPU Architecture A Paper Survey


title: An Automatic System for Extracting Figures and Captions in Biomedical PDF Documents

abstract: Figures in biomedical articles often constitute direct evidence of experimental results. Image analysis methods can be coupled with text-based methods to improve knowledge discovery. However, automatically harvesting figures along with their associated captions from full-text articles remains challenging. In this paper, we present an automatic system for robustly harvesting figures from biomedical literature. Our approach relies on the idea that the PDF specification of the document layout can be used to identify encoded figures and figure boundaries within the PDF and enforce constraints among figure-regions. This allows us to harvest fragments of figures (subfigures), from the PDF, correctly identify subfigures that belong to the same figure, and identify the captions associated with each figure. Our method simultaneously recovers figures and captions and applies additional filtering process to remove irrelevant figures such as logos, to eliminate text passages that were incorrectly identified as captions, and to re-group subfigures to generate a putative figure. Finally, we associate figures with captions. Our preliminary experiments suggest that our method achieves an accuracy of 95% in harvesting figures-caption pairs from a set of 2, 035 full-text biomedical documents from Bio Creative III, containing 12, 574 figures.


title: Nurse staffing, burnout, and health care–associated infection

abstract: Background Each year, nearly 7 million hospitalized patients acquire infections while being treated for other conditions. Nurse staffing has been implicated in the spread of infection within hospitals, yet little evidence is available to explain this association. Methods We linked nurse survey data to the Pennsylvania Health Care Cost Containment Council report on hospital infections and the American Hospital Association Annual Survey. We examined urinary tract and surgical site infection, the most prevalent infections reported and those likely to be acquired on any unit within a hospital. Linear regression was used to estimate the effect of nurse and hospital characteristics on health care–associated infections. Results There was a significant association between patient-to-nurse ratio and urinary tract infection (0.86; P = .02) and surgical site infection (0.93; P = .04). In a multivariate model controlling for patient severity and nurse and hospital characteristics, only nurse burnout remained significantly associated with urinary tract infection (0.82; P = .03) and surgical site infection (1.56; P Conclusions We provide a plausible explanation for the association between nurse staffing and health care–associated infections. Reducing burnout in registered nurses is a promising strategy to help control infections in acute care facilities.


title: Design and Measurement of Reconfigurable Millimeter Wave Reflectarray Cells With Nematic Liquid Crystal

abstract: Numerical simulations are used to study the electromagnetic scattering from phase agile microstrip reflectarray cells which exploit the voltage controlled dielectric anisotropy property of nematic state liquid crystals (LCs). In the computer model two arrays of equal size elements constructed on a 15 mum thick tuneable LC layer were designed to operate at center frequencies of 102 GHz and 130 GHz. Micromachining processes based on the metallization of quartz/silicon wafers and an industry compatible LCD packaging technique were employed to fabricate the grounded periodic structures. The loss and the phase of the reflected signals were measured using a quasi-optical test bench with the reflectarray inserted at the beam waist of the imaged Gaussian beam, thus eliminating some of the major problems associated with traditional free-space characterization at these frequencies. By applying a low frequency AC bias voltage of 10 V, a 165deg phase shift with a loss 4.5-6.4 dB at 102 GHz and 130deg phase shift with a loss variation between 4.3-7 dB at 130 GHz was obtained. The experimental results are shown to be in close agreement with the computer model.


title: High-Performance Four-Stage CMOS OTA Suitable for Large Capacitive Loads

abstract: Designing four-stage operational transconductance amplifiers (OTAs) is often considered a challenging task mainly because of the required non trivial frequency compensation procedure. In this study, starting from the simplest architecture (a differential stage cascaded by three common source stages) a high-performance OTA is demonstrated, outperforming all the (few) previous implementations. Thanks to the frequency compensation scheme and to the adoption of a slew-rate enhancer section, the solution is able to drive large capacitive loads as high as 1 nF, rivaling in terms of bandwidth and speed even with three-stage counterparts, traditionally credited to be better because of the less number of high-impedance nodes. The solution, fabricated in a 0.35- $\mu{\rm m}$ technology, occupies 0.014- ${\rm mm}^{2}$ with DC consumption of 170 $\mu{\rm W}$ . It also achieves nearly 3-MHz gain bandwidth product while driving the 1-nF load with less than 0.5- $\mu{\rm s}$ 1% settling time.


title: Trajectory Tracking Control for a 3-DOF Planar Parallel Manipulator Using the Convex Synchronized Control Method

abstract: In this paper, in order to satisfy multiple closed-loop performance specifications simultaneously while improving tracking accuracy during high-speed, high-acceleration tracking motions of a 3-degree-of-freedom (3-DOF) planar parallel manipulator, we propose a new control approach, termed convex synchronized (C-S) control. This control strategy is based on the so-called convex combination method, in which the synchronized control method is adopted. Through the adoption of a set of n synchronized controllers, each of which is tuned to satisfy at least one of a set of n closed-loop performance specifications, the resultant set of n closed-loop transfer functions are combined in a convex manner, from which a C-S controller is solved algebraically. Significantly, the resultant C-S controller simultaneously satisfies all n closed-loop performance specifications. Since each synchronized controller is only required to satisfy at least one of the n closed-loop performance specifications, the convex combination method is more efficient than trial-and-error methods, where the gains of a single controller are tuned to satisfy all n closed-loop performance specifications simultaneously. Furthermore, during the design of each synchronized controller, a feedback signal, termed the synchronization error, is employed. Different from the traditional tracking errors, this synchronization error represents the degree of coordination of the active joints in the parallel manipulator based on the manipulator kinematics. As a result, the trajectory tracking accuracy of each active joint and that of the manipulator end-effector is improved. Thus, possessing both the advantages of the convex combination method and synchronized control, the proposed C-S control method can satisfy multiple closed-loop performance specifications simultaneously while improving tracking accuracy. In addition, unavoidable dynamic modeling errors are addressed through the introduction of a robust performance specification, which ensures that all performance specifications are satisfied despite allowable variations in dynamic parameters, or modeling errors. Experiments conducted on a 3-DOF P-R-R-type planar parallel manipulator demonstrate the aforementioned claims.


title: Instant inkjet circuits: lab-based inkjet printing to support rapid prototyping of UbiComp devices

abstract: This paper introduces a low cost, fast and accessible technology to support the rapid prototyping of functional electronic devices. Central to this approach of 'instant inkjet circuits' is the ability to print highly conductive traces and patterns onto flexible substrates such as paper and plastic films cheaply and quickly. In addition to providing an alternative to breadboarding and conventional printed circuits, we demonstrate how this technique readily supports large area sensors and high frequency applications such as antennas. Unlike existing methods for printing conductive patterns, conductivity emerges within a few seconds without the need for special equipment. We demonstrate that this technique is feasible using commodity inkjet printers and commercially available ink, for an initial investment of around US$300. Having presented this exciting new technology, we explain the tools and techniques we have found useful for the first time. Our main research contribution is to characterize the performance of instant inkjet circuits and illustrate a range of possibilities that are enabled by way of several example applications which we have built. We believe that this technology will be of immediate appeal to researchers in the ubiquitous computing domain, since it supports the fabrication of a variety of functional electronic device prototypes.


title: Application of Feature Extraction Method in Customer Churn Prediction Based on Random Forest and Transduction

abstract: With the development of telecom business, customer churn prediction becomes more and more important. An outstanding issue in customer churn prediction is high dimensional problem. Curse of dimensionality will easily occur if effective feature extraction is not applied during modeling. Among the most popular feature extraction approaches, principal component analysis (PCA) method based on induction learning usually loses certain information contained in the features of test data. Different with induction learning method, a new method based on Random Forest and Transduction is developed in this paper. Experiments results on the UCI data show that compared to PCA the proposed method makes full use of the information contained in training samples and test data and improves the performance of learning machine effectively with fewer features. Application of this new method on customer churn prediction also shows it’s efficient.


title: Relationship between Total Lymphocyte count (TLC) and CD4 count among peoples living with HIV, Southern Ethiopia: a retrospective evaluation

abstract: BackgroundCD4 count is a standard measure of immunodeficiency in adults infected with HIV to initiate and monitor highly active antiretroviral therapy; however, it may not be feasible in resource poor countries. There is a need to have another marker of immunodeficiency that is less resource demanding.ObjectiveThe objective of this study was to assess the relationship between total lymphocyte count and CD4 count in one of the resource poor countries, Ethiopia.MethodsThis was a retrospective evaluation. A total of 2019 cases with total lymphocyte and CD4 counts from three hospitals (Yirgalem, Hossana and Arba-Minch) were included in the study. Pearson correlation, linear regression and Receiver Operating Characteristic (ROC) were used.ResultFor adults, the sensitivity, specificity, positive and negative predictive values of TLC < 1200 cells/mm3 to predict CD4 count < 200 cells/mm3 were 41%, 83.5%, 87.9% and 32.5%, respectively. For subjects aged less than 18 years, these values were 20.2%, 87%, 82% and 27.1%, respectively. A TLC ≤ 1780 cells/mm3 was found to have maximal sensitivity (61%) and specificity (62%) for predicting a CD4 cell count of < 200 cells/mm3. Meanwhile, a TLC ≤ 1885 cells/mm3 would identify only 59% of patients with CD4 count of < 350 cells/mm3(sensitivity, 59%; and specificity, 61%). The combined sensitivity and specificity for patients above 40 years of age was greater.ConclusionOur data revealed low sensitivity and specificity of TLC as a surrogate measure for CD4 count.


Experimental Study on Glass Fiber Reinforced Concrete Moderate Deep Beam