A survey of R&D of intelligent STR system based on behavior pattern recognition in China

2016 ◽  
Vol 19 (2) ◽  
pp. 109-121 ◽  
Author(s):  
Jun Tang
Keyword(s):  
Pattern Recognition ◽  
Intelligent System ◽  
Behavior Pattern ◽  
Recognition System ◽  
Decision Procedures ◽  
Customer Behavior ◽  
Content Type ◽  
The Core ◽  
Core Elements ◽  
Str System

Purpose The purpose of this paper is to systematically study the research and development history of suspicious transaction reporting (STR) system in China, and introduce the core elements in constructing an intelligent surveillance system which could provide a solution to the situation of low effectiveness and efficiency in Chinese Financial Institutions (FIs) STR procedure nowadays. The solution outputs those falling out of the normal customer behavior profiles instead of only extracting data by the rules issued by authorities. Design/methodology/approach This paper reviews the latest literature, regulations and guidelines of STR gathered domestically and overseas, and hands out questionnaire surveys to hundreds of software vendors, regulators and FIs, details the current situation of poor deployment of intelligent in China and tells the difficulties of subjective STR decision procedures. Findings Few Chinese FIs have deployed real intelligent STR systems, most are using rule-based filtering systems conformed to the objective STR supervisory regulations. To change the embarrassing situation, the regulators have tried to introduce self-regulatory mode which allows the FIs to define STR decision procedures themselves. Limited by the FIs’ ability of information sharing and investigation scope, FIs could hardly unveil the whole schema of a money laundering organization. The pursuant objective FIs can reach is to construct a system that could tell what the normal customer behaviors look like and extract all those falling out of the system’s expectations as suspicious activities. Research limitations/implications Only the core elements of the total intelligent STR system are discussed, that is, what, why and how about the customer behavior pattern recognition system. Besides this, a total solution should also use a watch list, reporting decision, cases management, risk control, etc. Originality/value This paper for the first time argues that the orientation of regulatory rules in China has actually hindered the spreading of really effective intelligent system for these years. The author creatively puts forward a solution to the difficult problem for FIs to spot criminal schema directly, instead the FIs should only be required to determine whether the transactions carrying out currently are falling within the expected behavior pattern scopes, which is under the FIs’ capabilities due to the internationally accepted obligations of “Know Your Customer”.

Intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
G. Merlin Linda ◽  
N.V.S. Sree Rathna Lakshmi ◽  
N. Senthil Murugan ◽  
Rajendra Prasad Mahapatra ◽  
V. Muthukumaran ◽  
...  
Keyword(s):  
Spatial Information ◽  
Intelligent System ◽  
Gait Recognition ◽  
Research Work ◽  
Recognition System ◽  
Multimodal Fusion ◽  
Content Type ◽  
Surveillance Videos ◽  
Sensor Devices ◽  
Intelligent Recognition

PurposeThe paper aims to introduce an intelligent recognition system for viewpoint variations of gait and speech. It proposes a convolutional neural network-based capsule network (CNN-CapsNet) model and outlining the performance of the system in recognition of gait and speech variations. The proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech variations.Design/methodology/approachThis proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNN and used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in viewpoint. The proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of CNN-CapsNet.FindingsThis research work provides recognition of signal, biometric-based gait recognition and sound/speech analysis. Empirical evaluations are conducted on three aspects of scenarios, namely fixed-view, cross-view and multi-view conditions. The main parameters for recognition of gait are speed, change in clothes, subjects walking with carrying object and intensity of light.Research limitations/implicationsThe proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.Practical implicationsThis research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.Originality/valueThis proposed research work proves to be performing better for the recognition of gait and speech when compared with other techniques.

scholarly journals Artificial Auditory Perception Pattern Recognition System Based on Spatiotemporal Convolutional Neural Network

2019 ◽  
Vol 10 (1) ◽  
pp. 139
Author(s):  
Xia Fang ◽  
Han Fang ◽  
Zhan Feng ◽  
Jie Wang ◽  
Libin Zhou
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Convolutional Neural Network ◽  
Intelligent System ◽  
Human Perception ◽  
Principal Component ◽  
Recognition System ◽  
Stepper Motor ◽  
Pattern Recognition System ◽  
Perception System

It is difficult to combine human sensory cognition with quality detection to form a pattern recognition system based on human perception. In the future, miniature stepper motor modules will be widely used in advanced intelligent equipment. However, the reducer module based on powder metallurgy parts and the stepper motor may have various defects during operation, with varying definitions of those that affect the user comfort. It is tremendously important to develop an intelligent system to effectively simulate human senses. In this work, an elaborated personification of the perceptual system is proposed to simulate the ventral and flow of the human perception system: two branch systems consisting of a spatiotemporal convolutional neural network (S-CNN) and a concatenated HoppingNet temporal convolutional neural network (T-CNN). To ensure high robustness of the system, we combined principal component analysis (PCA) with the opinions of an experienced quality control (QC) team members to screen the data, and used a bionic ear to simulate human perception characteristics. After repeated comparisons of the tester, the results show that our anthropoid pattern sensing system has high accuracy and robustness for a stepper motor module.

Virtual assembly with physical information: a review

2015 ◽  
Vol 35 (3) ◽  
pp. 206-220 ◽  
Author(s):  
Keyan Liu ◽  
Xuyue Yin ◽  
Xiumin Fan ◽  
Qichang He
Keyword(s):  
General Structure ◽  
Virtual Assembly ◽  
Research Trend ◽  
Future Directions ◽  
Content Type ◽  
The Core ◽  
Core Elements ◽  
Comprehensive Survey ◽  
Key Issues ◽  
New Research

Purpose – The purpose of this paper is to give a comprehensive survey on the physics-based virtual assembly (PBVA) technology in a novel perspective, to analyze current drawbacks and propose several promising future directions. Design/methodology/approach – To provide a deep insight of PBVA, a discussion of the developing context of PBVA and a comparison against constraint-based virtual assembly (CBVA) is put forward. The core elements and general structure are analyzed based on typical PBVA systems. Some common key issues as well as common drawbacks are discussed, based on which the research trend and several promising future directions are proposed. Findings – Special attention is paid to new research progresses and new ideas concerning recent development as well as new typical systems of the technology. Advantages of PBVA over CBVA are investigated. Based on the analysis of typical PBVA systems and the evolution of PBVA, the core elements of the technology and the general structure of its implementation are identified. Then, current PBVA systems are summarized and classified. After that, key issues in the technology and current drawbacks are explored in detail. Finally, promising future directions are given, including both the further perfecting of the technology and the combination with other technologies. Originality/value – The PBVA technology is put into a detailed review and analysis in a novel way, providing a better insight of both the theory and the implementation of the technology.

Intelligent system for sports movement quantitative analysis

2020 ◽  
pp. 1-9
Author(s):  
Yanhong Ren ◽  
Bo Chen ◽  
Aizeng Li
Keyword(s):  
Deep Learning ◽  
Quantitative Analysis ◽  
Human Body ◽  
Intelligent System ◽  
Comprehensive Evaluation ◽  
Fuzzy Theory ◽  
Performance Comparison ◽  
The Core ◽  
Core Elements ◽  
Quantitative Analysis Method

Action is the key to sports and the core factor of standardization, quantification, and comprehensive evaluation. However, in the actual competition training, the occurrence of sports activities is often fleeting, and it is difficult for human eyes to identify quickly and accurately. There are many existing quantitative analysis methods of sports movements, but because there are many complex factors in the actual scene, the effect is not ideal. How to improve the accuracy of the model is the key to current research, but also the core problem to be solved. To solve this problem, this paper puts forward an intelligent system of sports movement quantitative analysis based on deep learning method. The method in this paper is firstly to construct the fuzzy theory human body feature method, through which the influencing factors in the quantitative analysis of movement can be distinguished, and the effective classification can be carried out to eliminate irrelevantly and simplify the core elements. Through the method of human body characteristics based on fuzzy theory, an intelligent system of deep learning quantitative analysis is established, which optimizes the algorithm and combines many modern technologies including DBN architecture. Finally, the accuracy of the method is improved by sports action detection, figure contour extraction, DBN architecture setting, and normalized sports action recognition and quantification. To verify the effect of this model, this paper established a performance comparison experiment based on the traditional method and this method. The experimental results show that compared with the traditional three methods, the accuracy of the in-depth learning sports movement quantitative analysis method in this paper has greatly improved and its performance is better.

Categorization of fabric design using multi-class least-square support vector machine

2014 ◽  
Vol 26 (1) ◽  
pp. 58-66 ◽  
Author(s):  
A. Ghosh ◽  
T. Guha ◽  
R. Bhar
Keyword(s):  
Pattern Recognition ◽  
Design Methodology ◽  
Inequality Constraints ◽  
Recognition System ◽  
Least Square ◽  
Support Vector ◽  
Content Type ◽  
Reasonable Degree ◽  
Vector Machines ◽  
Fabric Design

Purpose – The purpose of this paper is to give an approach for categorization of diverse textile designs using their textural features as extracted from their gray images by means of multi-class least-square support vector machines (LS-SVM). Design/methodology/approach – In this work, the authors endeavor to devise a pattern recognition system based on LS-SVM which performs a multi-class categorization of three basic woven designs namely plain, twill and sateen after analyzing their features. Findings – The result establishes that LS-SVM is able to classify the fabric design with a reasonable degree of accuracy and it outperforms the standard SVM. Originality/value – The algorithmic simplicity of LS-SVM resulting from replacement of inequality constraints by equality ones and ability of handling noisy data by accommodating an error variable in its algorithm make it eminently suitable for textile pattern recognition. This paper offers a maiden application of LS-SVM in textile pattern recognition.

scholarly journals Women in the boardroom and their impact on default risk: a pitch

2017 ◽  
Vol 30 (2) ◽  
pp. 137-146 ◽  
Author(s):  
Searat Ali
Keyword(s):  
Default Risk ◽  
Design Methodology ◽  
Gender Diversity ◽  
Early Career ◽  
Content Type ◽  
The Core ◽  
Early Career Researchers ◽  
Core Elements ◽  
Personal Reflections ◽  
And Training

Purpose The purpose of this pitch research letter (PRL) is to apply the pitching template developed by Faff (2015) to an academic project on boardroom gender diversity and default risk. Design/methodology/approach The pitching template helps the pitcher to identify the core elements that form the framework of the research project. The PRL encloses a brief background about the pitcher and pitch, followed by a brief commentary on the pitch and personal reflections of the pitcher on the pitch exercise itself. Findings One of the best aspects of the pitching template is that it forced the researchers to think each item over and over, enabling a synthesis of scattered ideas in a systematic way. Hence, it is strongly recommend learning and applying the pitching template as a tool to refine embryonic research ideas and to track the progress on the research projects. Originality/value This PRL is novel as it highlights the worth of performing the pitching exercise (i.e. quality publication), potential adoptability challenge and solutions (i.e. unfamiliarity and training), systematic process of learning the pitching template and application of the “rule of three” in pitching research. Such reflections are believed to be useful for early career researchers (ECRs).

scholarly journals Research on hospital-based shared governance: a scoping review

2020 ◽  
Vol 25 (4) ◽  
pp. 371-386
Author(s):  
Maiju Kyytsönen ◽  
Marco Tomietto ◽  
Moona Huhtakangas ◽  
Outi Kanste
Keyword(s):  
Thematic Analysis ◽  
Scoping Review ◽  
Shared Governance ◽  
Research Articles ◽  
Original Research ◽  
Content Type ◽  
The Core ◽  
Continuous Quality ◽  
Search Terms ◽  
Core Elements

PurposeThe purpose of this study is to review research on hospital-based shared governance (SG), focussing on its core elements.Design/methodology/approachA scoping review was conducted by searching the Medline (Ovid), CINAHL (EBSCO), Medic, ABI/INFORM Collection (ProQuest) and SveMed+ databases using SG and related concepts in hospital settings as search terms (May 1998–February 2019). Only original research articles examining SG were included. The reference lists of the selected articles were reviewed. Data were extracted from the selected articles by charting and then subjected to a thematic analysis.FindingsThe review included 13 original research articles that examined SG in hospital settings. The studied organizations had implemented SG in different ways, and many struggled to obtain satisfactory results. SG was executed within individual professions or multiple professions and was typically implemented at both unit- and organization-levels. The thematic analysis revealed six core elements of SG as follows: professionalism, shared decision-making, evidence-based practice, continuous quality improvement, collaboration and empowerment.Practical implicationsAn SG framework for hospital settings was developed based on the core elements of SG, the participants and the organizational levels involved. Hospitals considering SG should prepare for a time-consuming process that requires belief in the core elements of SG. The SG framework can be used as a tool to implement and strengthen SG in organizations.Originality/valueThe review resumes the tradition of systematically reviewing SG literature, which had not been done in the 21st century. General tendencies of the research scene and research gaps are pointed out.

The importance of integrated therapies for personality disorder in forensic populations: attending to content and structure of delivery

2015 ◽  
Vol 1 (2) ◽  
pp. 99-110 ◽  
Author(s):  
Jane L. Ireland ◽  
Elisabeth Hansen
Keyword(s):  
Personality Disorder ◽  
Relevant Literature ◽  
Integrated Approach ◽  
Behaviour Therapy ◽  
Content Type ◽  
The Core ◽  
Cognitive Components ◽  
Effective Components ◽  
Integrated Therapy ◽  
Core Elements

Purpose – The purpose of this paper is to provide some practice considerations for working with personality disorder, focusing on the application of assessment, formulation and therapy to complex populations such as forensic clients. In addressing this it outlines the concept of a Multi-Modal Integrated Therapy (MMIT) and how this is applied to personality disorder intervention. Design/methodology/approach – The core elements to consider in the provision of an integrated approach are outlined, informed by a review of the relevant literature. The paper does not aim to provide evaluation data but is intended to be a clinical practice document. Findings – The value of integrating the effective components of therapy to address all aspects of working with forensic populations is evidenced. It is argued that appropriate approaches will capture cognitive components (including Early Maladaptive Schemas and also adaptive schemas), Cognitive Analytic Therapeutic approaches and Dialectical Behaviour Therapy components to produce an effective framework to capture the complexities of personality disorder in forensic populations. Practical implications – The paper outlines how a move away from focusing on a single approach to understanding and intervening with personality disorder is key with complex populations, such as those found within forensic settings. The authors argue that practitioners should focus routinely on the importance of integration of principles relevant to personality disorder work. Originality/value – The paper argues for: Adopting a truly multi-modal integrated approach to interventions with personality disorder, highlighting the importance of MMIT. The importance of accounting for complexity in personality presentation in forensic populations and capturing positive as well as negative functioning. The value in identifying what is effective within existing therapies and applying these components as part of a wider package. The core elements of an effective approach are indicated.

Social learning for enhancing social-ecological resilience to disaster-shocks: a policy Delphi approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
C. Emdad Haque ◽  
Fikret Berkes ◽  
Álvaro Fernández-Llamazares ◽  
Helen Ross ◽  
F. Stuart Chapin III ◽  
...  
Keyword(s):  
Social Learning ◽  
Ecological Resilience ◽  
Social Implications ◽  
Collaborative Process ◽  
Content Type ◽  
Policy Delphi ◽  
The Core ◽  
Social Ecological ◽  
Core Elements ◽  
Practical Implications

PurposeThe plethora of contributions to social learning has resulted in a wide range of interpretations, meanings and applications of social learning, both within and across disciplines. However, advancing the concept and using social learning methods and tools in areas like disaster-shocks requires interdisciplinary consolidation of understandings. In this context, the primary focus of this paper is on the contributions of social learning to disaster risk reduction (DRR).Design/methodology/approachBy applying a three-round policy Delphi process involving 18 purposefully selected scholars and expert-practitioners, the authors collected data on the meanings of social learning for two groups of professionals, DRR and social-ecological resilience. The survey instruments included questions relating to the identification of the core elements of social learning and the prospects for enhancing social-ecological resilience.FindingsThe results revealed strong agreement that (1) the core elements of social learning indicate a collective, iterative and collaborative process that involves sharing/networking, changes in attitudes and knowledge and inclusivity; (2) social learning from disasters is unique; and (3) linkages between disciplines can be built by promoting interdisciplinarity, networks and knowledge platforms; collaboration and coordination at all levels; and teaching and practicing trust and respect. Social learning is useful in preparing for and responding to specific disaster events through communication; sharing experience, ideas and resources; creating synergies for collective action and promoting resilience.Research limitations/implicationsThe policy Delphi process involved a limited number of participants to control the quality of the data. To the best of the authors’ knowledge, this paper is the first of its kind to identify the core elements of social learning, specifically, in the disaster-shock context. It also makes significant contributions to the interdisciplinary integration issues.Practical implicationsThe practical implications of this study are related to pre-disaster planning and mitigation through the application of social learning on disaster-shocks.Social implicationsThe social implications of this study are related to valuing social learning for the improvement of disaster planning, management, and policy formulation and implementation in reducing disaster risks.Originality/valueThe study provides a consensus view on the core elements of social learning and its role in DRR and resilience building. Relevant to all stages of DRR, social learning is best characterized as a collective, iterative and collaborative process. It can be promoted by enhancing networking and interdisciplinarity.

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