Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient face recognition method using a combined phase congruency/Gabor wavelet technique

In this paper, we present a Face Recognition method based on the combination of the Gabor Wavelets (GW) and the Phase Congruency (PC) method [1]. While the GW method allows an efficient space-frequency analysis to code the Face Image points, it requires significant down-sampling, in order to end up with a reasonably small-size feature vector. Now, the Phase Congruency method can be used as an efficient features detector, to uncover the salient local features of the face and can be computed using the GW Transform. An additional advantage of the Phase Congruency method is its insensitivity to variations in image illumination and contrast. The method proposed is to use the PC method in determining the salient points of the Face Image, thus replacing the random down-sampling method. The first step in our proposed method is to obtain the local frequency information of a face image using a multi-scale, multi-orientation set of Gabor filters, from which the Phase Congruency image is computed. We then use this method to select a limited number of maximum-value points, whose values are taken from the GW- transformed face images, forming a feature vector of about 5000 components. Preliminary results using the ORL face dataset show 98% recognition rate even without the use of the PCA method. Upon using the PCA method we can further reduce the number of components to 45 while still retaining the recognition rate of 98%. This as compared to a recognition rate of 96% using GW and PCA with a random 64:1 down-sampling on the GW coefficients. The proposed combined method, allows in addition to an efficient reduction in the number of image points used, the derivation of both the PC image and the GW feature vector representation, using a single GW transform.
Core Functions Analysis and Example Deployment of Virtual Honeynet

As conventional honeynet's low hardware utilization,complex configuration and difficult management are increasingly appearing,how to solve these problems has been getting more and more researcher's attention.Aiming at the problems that honeynet currently is facing,the paper proposed the necessity of using virtual technology to construct honeynet.Through the studying on core functions of honeynet,the paper analyzed and provided the workflow of core functions in virtual systerm.Based on that,we designed and implemented a proposal of the virtual honeynet.The results show that the established virtual honeynet works well and solves the shortcomings of conventional honeynet in a certain extent.
Competing Bandits: The Perils of Exploration Under Competition

Most online platforms strive to learn from interactions with consumers, and many engage in exploration: making potentially suboptimal choices for the sake of acquiring new information. We initiate a study of the interplay between exploration and competition: how such platforms balance the exploration for learning and the competition for consumers. Here consumers play three distinct roles: they are customers that generate revenue, they are sources of data for learning, and they are self-interested agents which choose among the competing platforms. We consider a stylized duopoly model in which two firms face the same multi-armed bandit instance. Users arrive one by one and choose between the two firms, so that each firm makes progress on its bandit instance only if it is chosen. We study whether and to what extent competition incentivizes the adoption of better bandit algorithms, and whether it leads to welfare increases for consumers. We find that stark competition induces firms to commit to a "greedy" bandit algorithm that leads to low consumer welfare. However, we find that weakening competition by providing firms with some "free" consumers incentivizes better exploration strategies and increases consumer welfare. We investigate two channels for weakening the competition: relaxing the rationality of consumers and giving one firm a first-mover advantage. We provide a mix of theoretical results and numerical simulations. Our findings are closely related to the "competition vs. innovation" relationship, a well-studied theme in economics. They also elucidate the first-mover advantage in the digital economy by exploring the role that data can play as a barrier to entry in online markets.
Haptic emulation of hard surfaces with applications to orthopaedic surgery

ii TABLE OF CONTENTS. iii LIST OF TABLES. vi LIST OF FIGURES . vii ACKNOWLEDGEMENTS. xii 1.0 HAPTIC EMULATION OF A HARD SURFACE WITH APPLICATIONS TO ORTHOPAEDIC SURGERY. 1 1.
Improvement of the exemplar-based inpainting

Abstract. This paper proposes an improved exemplar-based inpainting using image segmentation, image quilting, and spatial blending to reduce the excessively propagating texture and pathological geometric configurations. A graph-based segmentation is used to generate an initial segmented map. The segmented regions are merged by a K-means approach with texture similarity to generate a further texture-based segmented map, which reduces the candidate source space and determines whether to utilize image quilting in the iterative updating process. An improved spatial blending is introduced as a postprocess to smooth the filled image when the filling process is completed. Experimental results show that this exemplar-based inpainting approach has a good visual effect and reduces the computing time.
Towards Green and Soft

Wireless communication systems have been developing from the first generation (1G) to the latest, fourth generation (4G) to satisfy ever increasing and more diverse mobile traffic demand. The thousand‐fold wireless traffic increase anticipated by 2020 and the global recognition of the importance of green communications, however, pose very tough challenges for fifth generation (5G) design. The design metric of spectrum efficiency (SE) maximization, which was highly emphasized in previous communication systems, will have to be jointly pursued with, amongst other metrics, energy efficiency (EE). In this chapter, we will describe green network design considerations from the perspective of network architecture, signaling and control, and high SE and EE transmission techniques. The motivations, requirements, and worldwide activities for green radio are introduced, and one particular EE and SE co‐design framework is presented for link‐level optimization. The impact of system parameters such as frequency bandwidth, total power, antenna number, and transceiver number on EE–SE performance is analyzed. Promising 5G technologies, such as large scale antenna systems and non‐orthogonal multiple access are investigated in terms of EE–SE co‐design. To satisfy user requirements, future networks should be user‐centric rather than cell‐centric, thus leading to 5G networks with “no more cells”. C‐RAN, a soft radio access architecture and an enabling element for 5G key technologies, is presented, describing how the baseband is centralized and virtualized to flexibly allocate resource and manage interference to save both radiated and circuit power. Since the future network will be more heterogeneous, with fluctuating traffic volumes and diversified services, a fundamental rethinking of signaling and control design in 5G is necessitated to facilitate energy saving. Finally, an aggregator‐based signaling optimization scheme that can accommodate trillions of wireless nodes in the Internet of Things is described. It is anticipated that 5G networks and beyond will be softer and greener.
Dynamics of heavy metal Pollution in Tropical lagoon of Gulf of Guinea, West Africa

In this study the accumulation of Iron (Fe), Zinc (Zn), Cobalt (Co), Chromium (Cr), Cadmium (Cd), Lead (Pb) and Nickel (Ni) in sediment, water, some fish samples (Schilbe mystus, Mormyrus rume, Gymnarchus niloticus, Cynoglossus senegalensis, and Chrysichthys nigrodigitatus ) and an aquatic plant Eichhornea crassipes collected from Lekki lagoon, Lagos Nigeria were examined. Heavy metals in the water, sediment, some selected fish and an aquatic plant were determined seasonally across nine sampling Stations; in the gills, liver and muscles of the fish species and in the root stem and leaves of Eichhornea crassipes using an atomic absorption spectrometer (AAS). Heavy metals concentrations in the sediment and water varied significantly, both spatially and seasonally. Metal concentrations varied between species and body parts while Co, Cr and Pb were not detected. Ni was found in the liver and gills of S. mystus and M. rume and Cr in the gills of G. niloticus only. In Eichhornea crassipes , metals detected were in the order: root>leaves>stem for Fe, Zn, Cr, and Cd; root>stem>leaves for Pb and Ni while Co was not detected. Heavy metal presence in Lekki Lagoon calls for monitoring of activities within and around the lagoon and policy development towards the sustainable ecosystem health services. Keywords: Pollutants, Heavy metals, Eichhornia crassipes, Bioaccumulation, Lekki lagoon
Engineering of Tannic Acid Inspired Antifouling and Antibacterial Membranes through Co-deposition of Zwitterionic Polymers and Ag Nanoparticles

Recently, combining inorganic and organic components to develop a dual-functional surface (antibacterial and antifouling) has resulted in widespread investigations. However, the preparation of the dual-functional surface is limited by the availability of reactive surface chemistries at a material’s surface. Herein, owing to the multifunctionality of Tannic acid (TA), we proposed a universal, simple, and environmentally friendly approach to integrate the inorganic (Ag nanoparticles) and organic (zwitterionic) components into the membrane surface to simultaneously endow the surface with antifouling and antibacterial ability, respectively. The Ag nanoparticles (NPs) and zwitterionic polymer were codeposited onto the TA decorated surface. The obtained membrane surface exhibited long-term and robust bactericidal activity. Meanwhile, due to the zwitterionic structure, the membrane could effectively resist bacterial adhesion. Additionally, the proposed strategy could also be employed to construct many kinds of d.
SDPBS Web Server for Calculation of Electrostatics of Ionic Solvated Biomolecules

Abstract The Poisson-Boltzmann equation (PBE) is one important implicit solvent continuum model for calculating electrostatics of protein in ionic solvent. We recently developed a PBE solver library, called SDPBS, that incorporates the finite element, finite difference, solution decomposition, domain decomposition, and multigrid methods. To make SDPBS more accessible to the scientific community, we present an SDPBS web server in this paper that allows clients to visualize and manipulate the molecular structure of a biomolecule, and to calculate PBE solutions in a remote and user friendly fashion. The web server is available on the website https://lsextrnprod.uwm. edu/electrostatics/.
Study on vehicle routing problem with time windows

To solve multi-objective Vehicle Routing Problem with Time Windows(VRPTW),an immune algorithm based optimization solution of VRPTW is proposed.The mathematical model of scheduling problem and the frame of immune multiobjective optimization algorithm are expounded,and simulation experiments are done to validate this algorithm.Experimental result shows that the algorithm can solve the scheduling problem of logistics vehicles availably,and has the advantages of good application value.
Transfer of training between working memory task and attentional task

The present studies indicate that training effects in a certain domain may result in the acquired skills being transferred to other domains that require similar abilities. Cognitive training involves structured exercises that are prescribed and undertaken with the purpose of enhancing cognitive abilities, such as attention, memory, and problem solving. In contrast to symptomatic pharmacotherapy, non-pharmacological approaches may further improve patients’ situations. Our aim was to summarize the empirical evidence for the rehabilitation of individuals with cognitive disorders by using training tasks to enhance specific cognitive functions to combat against cognitive degradation and transfer the benefits to other widely used domains. Transfer of Training between Working Memory Task and Attentional Task Ting Guo Northeast Normal University, China Yanna Ren Okayama University, Japan Xiaotong Zhu Northeast Normal University, China Hong Chen Northeast Normal University, China Satoshi Takahashi Okayama University, Japan Jinglong Wu Okayama University, Japan Transfer of Training between Working Memory Task and Attentional Task
Operation of cooperative multiple robots using communication in a decentralized robotic system

Aiming at robotization of high-level tasks in dynamic and unpredictable environment, operation of cooperative multiple robots using communication in a decentralized robotic system is discussed. Functionality and strategy to realize cooperative motion of multiple autonomous robots are discussed. A decentralized robotic system developed so far and a task processing scenario by the system are introduced. Finally, some of the realized cooperative motion of multiple autonomous mobile robots are introduced.
Introduction to Solid State Physics

3rd edition, complete modern revision C. Kittel London: John Wiley. 1966. Pp. 648. Price £4 14s. Kind's new edition is to be welcomed. There is a revised format and attractive illustrations, and with the inclusion of much new material this book has become one of the best sources for undergraduate teaching. It is above all an interesting book, likely to give the student a wish to dig deeper into the solid state.
An overview of peak-to-average power ratio reduction techniques for OFDM

Besides a lot of advantages,such as powerful immunity,high spectrum efficiency,higher data transmission speed and so on,major shortage of OFDM is that the multiplex signal exhibits a very high peak-to-average power ratio(PAPR). This paper destribes some important PAPR reduction techniques for OFDM systems and shows the differences between them.
A Case Study on E-Banking Security Ã¢ÂÂ When Security BecomesToo Sophisticated for the User to Access Their Information

While eBanking security continues to increase in sophistication to protect against threats, the usability of the eBanking decreases resulting in poor security behaviors by the users. The current research evaluates security risks and measures taken for eBanking solutions. A case study is presented describing how increased complexity decreases vulnerabilities online but increases vulnerabilities from internal threats and eBanking users.
Comprehensive Review of Models and Methods for Inferences in Bio-Chemical Reaction Networks

The key processes in biological and chemical systems are described by networks of chemical reactions. From molecular biology to biotechnology applications, computational models of reaction networks are used extensively to elucidate their non-linear dynamics. The model dynamics are crucially dependent on the parameter values which are often estimated from observations. Over the past decade, the interest in parameter and state estimation in models of (bio-) chemical reaction networks (BRNs) grew considerably. The related inference problems are also encountered in many other tasks including model calibration, discrimination, identifiability, and checking, and optimum experiment design, sensitivity analysis, and bifurcation analysis. The aim of this review paper is to examine the developments in literature to understand what BRN models are commonly used, and for what inference tasks and inference methods. The initial collection of about 700 documents concerning estimation problems in BRNs excluding books and textbooks in computational biology and chemistry were screened to select over 270 research papers and 20 graduate research theses. The paper selection was facilitated by text mining scripts to automate the search for relevant keywords and terms. The outcomes are presented in tables revealing the levels of interest in different inference tasks and methods for given models in the literature as well as the research trends are uncovered. Our findings indicate that many combinations of models, tasks and methods are still relatively unexplored, and there are many new research opportunities to explore combinations that have not been considered—perhaps for good reasons. The most common models of BRNs in literature involve differential equations, Markov processes, mass action kinetics, and state space representations whereas the most common tasks are the parameter inference and model identification. The most common methods in literature are Bayesian analysis, Monte Carlo sampling strategies, and model fitting to data using evolutionary algorithms. The new research problems which cannot be directly deduced from the text mining data are also discussed.
Unleashing Artificial Intelligence onto Big Data: A Review

We live in an ocean of data. Big Data is characterized by vast amounts of data sized in the order of petabytes or even exabytes. Though Big Data has great potential, Big data by itself has no value unless one can derive meaningful results from it. That is where Artificial Intelligence pitches in. Artificial Intelligence's most common application is about finding patterns in enormous quantities of data. The confluence of Big Data and Artificial Intelligence allows companies to automate and improve complex descriptive, predictive and prescriptive analytical tasks. In other words, Big Data can offer great insights with the help of Artificial Intelligence (AI). Artificial Intelligence can act as a catalyst to derive tangible value from Big data and serve as key to unlocking Big data. This review article focuses on applications of artificial intelligence to Big Data, its Limitations and issues.
Application of image recognition technology in electrical equipment on-line monitoring

In order to reduce the amount of calculation of the traditional matching algorithm which is based on grayscale,the shape characteristics of image analysis technology is used and a new template matching algorithm is proposed.The algorithm first checks out the following interlacing data and roughly matches them,and then does precise matching.Therefore,it can greatly reduce the mount of data calculation.The algorithm which is applied in the image recognition of power transformer has an advantage of speed of calculation,and it can more quickly confirm the position of the power transformer.This paper also points out the prospect of applying remote digital video monitoring and image recognition technology in power systems.
Collaborative Learning in a Web-Based Environment: A Comparison Study

Collaborative learning has long been proven to be an effective approach in the traditional classroom setting. Despite the discussion of the benefits and potential of collaborative learning in a Web-based learning environment, there has been a lack of empirical studies showing whether and how distance learning students may benefit from this learning experience, particularly in comparison to their oncampus peers and from their own perspectives. This chapter reports on a study that uses a comparative approach to evaluate the effectiveness of collaborative learning and related teaching and learning outcomes in both distance learning and on-campus settings. The major findings of this study suggest that distance learning students tend to have more positive perceptions of collaborative learning than their peers in the traditional classroom setting. In addition, distance learning students tend to embrace collaborative learning readily and early compared to their on-campus peers. In terms of student class performance, this study shows that distance learning students can achieve essentially the same learning goals as their on-campus peers. However, there are individual differences in student performance. An analysis of factors contributing to the individual performance differences suggests that engagement is closely correlated to student class performance. This study also shows that, overall, both distance learning and on-campus students provide similar course and instructor evaluations for teaching effectiveness for classes with collaborative learning. Finally, the implications of this study and suggestions for future research are discussed.
Zn-Catalyzed Multicomponent KA2 Coupling: One-Pot Assembly of Propargylamines Bearing Tetrasubstituted Carbon Centers

Tetrasubstituted propargylamines comprise a unique class of highly useful compounds, which can be accessed through the multicomponent coupling between ketones, amines, and alkynes (KA2 coupling), an underexplored transformation. Herein, the development of a novel, highly efficient, and user-friendly catalytic system for the KA2 coupling, based on the environmentally benign, inexpensive, and readily available zinc acetate, is described. This system is employed in the multicomponent assembly of unprecedented, tetrasubstituted propargylamines derived from structurally diverse, challenging, and even biorelevant substrates. Notable features of this protocol include the demonstration of the enhancing effect that neat conditions can have on catalytic activity, as well as the expedient functionalization of hindered, prochiral cyclohexanones, linear ketones, and interesting molecular scaffolds such as norcamphor and nornicotine.
An Approach for Doctoral Students Conducting Context-Specific Review of Literature in IT, ICT, and Educational Technology

ABSTRACT Since 1980s the rate of technological change has been phenomenal, creating an impact on the information-seeking behaviors of doctoral students and other researchers. When searching the three fields of Information Technology (IT), Information and Communication Technology (ICT), and Educational Technology (EdTech), it is like opening a Pandora's Box; the variation in terminology is obvious. This makes searching, managing, and evaluating sources in these interdisciplinary fields challenging, and doctoral students trying to classify and analyze technology related studies can easily be overwhelmed. We offer a systematic, practical approach for reviewing and categorizing the literature by providing key search terms, a list of e-Journals, and an organizational structure for naming and framing studies. Doctoral students navigating their way through the literature review may find our resourcesa table-of-contents, an overview of the technology-related literature, and an annotated excerpt of an examined thesis—useful for writing a critical review.
Ni-Mo Sulfide Semiconductor Catalyst with High Catalytic Activity for One-Step Conversion of CO2 and H2S to Syngas in Non-Thermal Plasma

Carbon dioxide (CO2) and hydrogen sulfide (H2S) ordinarily coexist in many industries, being considered as harmful waste gases. Simultaneously converting CO2 and H2S into syngas (a mixture of CO and H2) will be a promising economic strategy for enhancing their recycling value. Herein, a novel one-step conversion of CO2 and H2S to syngas induced by non-thermal plasma with the aid of Ni-Mo sulfide/Al2O3 catalyst under ambient conditions was designed. The as-synthesized catalysts were characterized by using XRD, nitrogen sorption, UV-vis, TEM, SEM, ICP, and XPS techniques. Ni-Mo sulfide/Al2O3 catalysts with various Ni/Mo molar ratios possessed significantly improved catalytic performances, compared to the single-component catalysts. Based on the modifications of the physical and chemical properties of the Ni-Mo sulfide/Al2O3 catalysts, the variations in catalytic activity are carefully discussed. In particular, among all the catalysts, the 5Ni-3Mo/Al2O3 catalyst exhibited the best catalytic behavior with high CO2 and H2S conversion at reasonably low-energy input in non-thermal plasma. This method provides an alternative route for syngas production with added environmental and economic benefits.