153 research outputs found
Deep introspective SLAM: deep reinforcement learning based approach to avoid tracking failure in visual SLAM
No full textReliable and consistent tracking is essential to realize the dream of power-on-and-go autonomy in mobile robots. Our investigation with state-of-the-art visual navigation and mapping tools (e.g. ORB-SLAM) reveals that these tools suffer from frequent and unexpected tracking failures, especially when tested in the wild. This hinders the ability of robots to reach a goal position less than 10 meters away, without tracking failure, thereby limiting the prospects of real autonomy. We present an introspection-based approach (Introspective-SLAM) that enables SLAM to evaluate safety of navigation steps with respect to tracking failure, before the steps are actually taken. Navigation steps that appear unsafe are thereby avoided, and an alternative path to the goal is planned. We propose a novel deep reinforcement learning (DQN) based network to evaluate safety of future navigation steps using a single image only. Surprisingly, training of our DQN completes in a short amount of time (< 60 h). Even then, this network outperforms several handcrafted and Q-learning based pipelines to achieve state-of-the-art performance. Interestingly, training the DQN in realistic simulators (MINOS), consisting of reconstructed interiors, shows good generalization across real world indoor-outdoor settings. Finally, extensive testing of visual SLAM, equipped with our DQN, shows that tracking failures occur frequently and are a major hindrance in reaching the goal. Currently, there is no standard benchmark to evaluate active visual SLAM approaches. We have released a benchmark of 50 episodes with this work. We hope these findings/benchmark will encourage progress for power-on-and-go visual SLAM without any manual supervision.
Seizure detection from EEG signals using Multivariate Empirical Mode Decomposition
No full textWe present a data driven approach to classify ictal (epileptic seizure) and non-ictal EEG signals using the multivariate empirical mode decomposition (MEMD) algorithm. MEMD is a multivariate extension of empirical mode decomposition (EMD), which is an established method to perform the decomposition and time-frequency (T−F) analysis of non-stationary data sets. We select suitable feature sets based on the multiscale T−F representation of the EEG data via MEMD for the classification purposes. The classification is achieved using the artificial neural networks. The efficacy of the proposed method is verified on extensive publicly available EEG datasets
Adaptive evolution and elucidating the potential inhibitor against schizophrenia to target DAOA (G72) isoforms
No full textSheikh Arslan Sehgal,1,2 Shazia Mannan,2,* Sumaira Kanwal,2,* Ishrat Naveed,1 Asif Mir1 1Department of Bioinformatics and Biotechnology, International Islamic University, Islamabad, Pakistan; 2Department of Biosciences, COMSATS Institute of Information Technology, Sahiwal, Pakistan *These authors contributed equally to this work Abstract: Schizophrenia (SZ), a chronic mental and heritable disorder characterized by neurophysiological impairment and neuropsychological abnormalities, is strongly associated with d-amino acid oxidase activator (DAOA, G72). Research studies emphasized that overexpression of DAOA may be responsible for improper functioning of neurotransmitters, resulting in neurological disorders like SZ. In the present study, a hybrid approach of comparative modeling and molecular docking followed by inhibitor identification and structure modeling was employed. Screening was performed by two-dimensional similarity search against selected inhibitor, keeping in view the physiochemical properties of the inhibitor. Here, we report an inhibitor compound which showed maximum binding affinity against four selected isoforms of DAOA. Docking studies revealed that Glu-53, Thr-54, Lys-58, Val-85, Ser-86, Tyr-87, Leu-88, Glu-90, Leu-95, Val-98, Ser-100, Glu-112, Tyr-116, Lys-120, Asp-121, and Arg-122 are critical residues for receptor–ligand interaction. The C-terminal of selected isoforms is conserved, and binding was observed on the conserved region of isoforms. We propose that selected inhibitor might be more potent on the basis of binding energy values. Further analysis of this inhibitor through site-directed mutagenesis could be helpful for exploring the details of ligand-binding pockets. Overall, the findings of this study may be helpful in designing novel therapeutic targets to cure SZ. Keywords: schizophrenia, bioinformatics, modeling, docking, DAOA, G72, DAO, computer-aided drug designing, phylogenetic analysis, d-amino acid oxidase activato
Dinaphthodiospyrol H: a natural α-glucosidase inhibibitor extracted from Diospyros kaki L.f
No full text: The roots of Diospyro kaki L.f., known for their anti-inflammatory, antimicrobial and antidiabetic properties, are the source of dimeric naphthoquinones, including dinaphthodiospyrol H. α-Glucosidase is an enzyme involved in regulation of blood glucose levels and its inhibition helps in the control of the postprandial hyperglycaemia. In this study, an in vitro evaluation of dinaphthodiospyrol H was carried out and the compound inhibited α-glucosidase with an IC50 value of 57.38 ± 0.87 μg/mL, revealing a significant potential that supports the traditional application of D. kaki in the treatment of diabetes mellitus. Additionally, computational studies, including docking and molecular dynamics, were used to investigate ligand-target complex and showed that the compound targets the same site with which acarbose interacts. Overall, the findings provide new basis to translate the traditional use of D. kaki into modern medicinal chemistry
All organic memory devices utilizing C60 molecules and insulating polymers
No full textThe convergence of mobile technologies combined with stricter power requirements and increasing demands have strained the current memory technology. Newer technologies such as phase changing, ferroelectric, and magnetic random access memories are unsatisfactory in meeting the new requirements. We propose a new memory technology based on our initial discovery of charge storage in C60 molecules within poly (4-vinyl phenol) (PVP). To understand the memory potential, we created single-layer devices consisting of ~30nm films of PVP+C60 sandwiched between aluminum (Al) electrodes. Current versus voltage (I-V) sweeps showed a significant hysteresis of 75nA, with distinguishable memory states. Room temperature charging of C60 was confirmed indirectly through capacitance versus voltage measurements and directly by monitoring the A1g characteristic peak of C60 during Raman measurements. We demonstrated memory operations by applying read-write-erase (RWE) pulses. The PVP+C60 devices exhibited memory retention for over 1 hour and response times of around 10ns. Characteristic hysteresis was demonstrated at the nanoscale. Conduction models were fitted at room temperature to the I-V curves. It was found that combination of direct and Fowler-Nordheim tunneling were the principle conduction mechanisms.
For a more technologically viable memory device, we developed a multi-layer device structure, consisting of a polystyrene (PS) capping layer. The resulting asymmetrical I-V curve exhibited a hysteresis ratio of 103. RWE cycles were measured with clearly distinguishable states. The memory retentions were measured over 2 hours and the response time around 10ns. The stability of the multi-layer devices was improved. I-V measurements at temperatures varying from 4.2 K to 298 K were performed to construct a theoretical model. The I-V curves were found to be temperature independent and exhibited similar tunneling behaviors as the single-layer devices. A simple model for conduction and memory operation is proposed based on the I-V fits.
These devices exhibit the characteristics needed to satisfy the new demands for memory application and have the potential of becoming the first universal memory technology. They possess the high speed, non-volatility, thermal stability, and potentially high memory densities to make them ideal for use in laptops, iPhones, mp3 players, portable video players, GPS systems, and other mobile devices.Ph.D.Includes bibliographical references
Handbook of Manufacturing Systems and Design
No full textThis handbook provides a comprehensive overview of manufacturing systems, their role in product/process design, and their interconnection with Industry 4.0 perspective, especially related to design, manufacturing, and operations.
Handbook of Manufacturing Systems and Design: An Industry 4.0 Perspective presents theories and concepts of Industry 4.0, with a focus on the different types of manufacturing systems, associated design, and control strategies. It concentrates on the operations in Industry 4.0, emphasizing supply chain, logistics, risk management, and reverse engineering perspectives. Offering basic concepts and applications through to advanced topics, the handbook is a comprehensive source of knowledge as well as a vehicle to explore the future possibilities of design, techniques, methods, and operations associated with Industry 4.0. Concepts with practical applications in the form of case studies are added to each chapter to round out the many attributes this handbook offers.
This handbook targets students, engineers, managers, designers, and manufacturers. It will assist in their understanding of the core concepts of manufacturing systems in connection with Industry 4.0 and optimize alignment between supply and demand in real-time for effective implementation of the design concepts
Determining the Prevalence and Correlates of Information Seeking Anxiety Among Postgraduates in Pakistan
No full textAbstractThis study examined the prevalence and correlatives of information seeking anxiety in postgraduate students of the University of the Punjab, Lahore using Information Seeking Anxiety Scale (ISAS). The participants’ selection was made using a stratified convenient sampling due to non-availability through random process. Postgraduate students were approached through a questionnaire, containing ISAS and demographic variables, with descriptive and inferential statistics used for data analysis. Results indicated the prevalence of information seeking anxiety among postgraduates as a large majority of the sample did face more than low anxiety for overall ISAS and all its sub-scales. Participants’ age, gender, faculty, program of study, study stage, computer proficiency, and research experience also appeared to be correlatives to the information seeking anxiety. These useful insights had serious implications to viable information literacy (IL) programs and could be used as a guide by academic information professionals managing information services, especially those engaged in IL instructions.</jats:p
A cross-cultural evaluation of the psychometric properties of information seeking anxiety scale in Pakistani environment
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