Application Technologies and Challenges of Big Data Analytics in Anti-Money Laundering and Financial Fraud Detection

As financial criminal methods become increasingly sophisticated, traditional anti-money laundering and fraud detection approaches face significant challenges. This study focuses on the application technologies and challenges of big data analytics in anti-money laundering and financial fraud detection. The research begins by outlining the evolutionary trends of financial crimes and highlighting the new characteristics of the big data era. Subsequently, it systematically analyzes the application of big data analytics technologies in this field, including machine learning, network analysis, and real-time stream processing. Through case studies, the research demonstrates how these technologies enhance the accuracy and efficiency of anomalous transaction detection. However, the study also identifies challenges faced by big data analytics, such as data quality issues, algorithmic bias, and privacy protection concerns. To address these challenges, the research proposes solutions from both technological and managerial perspectives, including the application of privacy-preserving technologies like federated learning. Finally, the study discusses the development prospects of Regulatory Technology (RegTech), emphasizing the importance of synergy between technological innovation and regulatory policies. This research provides guidance for financial institutions and regulatory bodies in optimizing their anti-money laundering and fraud detection strategies.

Raman spectroscopy as process analytical tool in downstream processing of biotechnology

Downstream processing or product recovery plays a vital role in the development of bioprocesses.To improve the bioprocess efficiency,some unconventional methods are much required.The continuous manufacturing in downstream processing makes the Process Analytical Technologies(PATs)as an important tool.Monitoring and controlling bioprocess are an essential factor for the principles of PAT and quality by design.Spectroscopic methods can apply to monitor multiple analytes in real-time with less sample processing with significant advancements.Raman spectroscopy is an extensively used technique as an analytical and research tool owing to its modest process form,non-destructive,non-invasive optical molecular spectroscopic imaging with computer-based analysis.Generally,its application is essential for the analysis and characterization of biological samples,and it is easy to operate with minimal sample.The innovation on various types of enhanced Raman spectroscopy was designed to enhance the Raman analytical technique.Raman spectroscopy could couple with chemometrics to provide reliable alternative analysis method of downstream process analysis.Thus,this review aims to provide useful insight on the application of Raman spectroscopy for PAT in downstream processing of biotechnology and Raman data analysis in biological fields.

Privacy-preserving analytics for the securitization market: a zero-knowledge distributed ledger technology application

A zero-knowledge proof or protocol is a cryptographic technique for verifying private data without revealing it in its clear form.In this paper,we evaluate the potential for zero-knowledge distributed ledger technology to alleviate asymmetry of information in the asset-backed securitization market.To frame this inquiry,we conducted market data analyses,a review of prior literature,stakeholder interviews with investors,originators and security issuers and collaboration with blockchain engineers and researchers.We introduce a new system which could enable all market participants in the securitization lifecycle(e.g.investors,rating agencies,regulators and security issuers)to interact on a unique decentralized platform while maintaining the privacy of loan-level data,therefore providing the industry with timely analytics and performance data.Our platform is powered by zkLedger(Narula et al.2018),a zero-knowledge protocol developed by the MIT Media Lab and the first system that enables participants of a distributed ledger to run publicly verifiable analytics on masked data.

UV/Vis-based process analytical technology to improve monoclonal antibody and host cell protein separation

Process analytical technology(PAT) is gaining more interest in the biomanufacturing industry because of its potential to improve operational control and compliance through real-time quality assurance.Currently, biopharmaceutical producers mainly monitor chromatographic processes with ultraviolet/visible(UV/Vis) absorbance. However, this measurement has a very limited correlation with purity and quantity. The current study aims to determine the concentration of monoclonal antibody(mAb) and host cell proteins(HCPs) using a build-in UV/Vis monitoring during Protein A affinity chromatography and to optimize the separation conditions for high purity of mAb and minimizing the HCPs content. The eluate was analyzed through in-line UV/Vis at 280 and 410 nm, representing mAb and HCPs concentration,respectively. Each 0.1 column volume(CV) fraction of UV/Vis chromatogram peak area were calculated,and different separation conditions were then compared. The optimum conditions of mAb separation were found as 12 CV loading, elution at pH 3.5, and starting the collection at 0.5 CV point, resulting in high m Ab recovery of 95.92% and additional removal of 49.98% of HCP comparing with whole elution pool. This study concluded that UV/Vis-based in-line monitoring at 280 and 410 nm showed a high potential to optimize and real-time control Protein A affinity chromatography for mAb purification from HCPs.

MUETEK Analytic GmbH和BTG Pulp & Paper Technology合并业务

BTG浆纸科技公司(BTG Pulp ＆ Paper Technolo-gy)于2001年1月16日,以其在瑞士Eclpens的集团总部取得了德国Muetek Analytic BmbH多数股权。BTG聘请Ms.Lydia Bley和Mr.Alfred

A review on edge analytics:Issues,challenges,opportunities,promises,future directions,and applications

Edge technology aims to bring cloud resources(specifically,the computation,storage,and network)to the closed proximity of the edge devices,i.e.,smart devices where the data are produced and consumed.Embedding computing and application in edge devices lead to emerging of two new concepts in edge technology:edge computing and edge analytics.Edge analytics uses some techniques or algorithms to analyse the data generated by the edge devices.With the emerging of edge analytics,the edge devices have become a complete set.Currently,edge analytics is unable to provide full support to the analytic techniques.The edge devices cannot execute advanced and sophisticated analytic algorithms following various constraints such as limited power supply,small memory size,limited resources,etc.This article aims to provide a detailed discussion on edge analytics.The key contributions of the paper are as follows-a clear explanation to distinguish between the three concepts of edge technology:edge devices,edge computing,and edge analytics,along with their issues.In addition,the article discusses the implementation of edge analytics to solve many problems and applications in various areas such as retail,agriculture,industry,and healthcare.Moreover,the research papers of the state-of-the-art edge analytics are rigorously reviewed in this article to explore the existing issues,emerging challenges,research opportunities and their directions,and applications.

Science,technology,and innovation in health for the next twenty years:A survey analysis in Colombia

Background:Colombia is a Latin American country with a very complex social and political context that has not allowed the allocation of sufficient resources to the fields of science,technology,and innovation(STI).This is particularly worrying for the area of health since not enough resources are allocated for public health,research,or education.Methods:The so-called“Great Survey in Health 2019”was administered online through the SurveyMonkey platform to 5298 people in different regions of the country,representing the public,private,and academic sectors.The questionnaire consisted of 46 open and closed questions,including demographic inquiries.Data analysis involved textual analytics and sentiment analysis.Results:Overall,56%of those surveyed were women within the adult life cycle.Most respondents had a postgraduate education.Greater participation was observed in the Oriental,Bogotá,and Antioquia regions,which also concentrate the largest number of resources for STI.Among the main recommendations derived from the results,priorities include investing in research,personalised medicine,promoting the social appropriation of knowledge,addressing mental health,regulating research through a statute,promoting undergraduate research,and establishing recertification exams to pursue excellence.Conclusion:The results of this original study serve as a fundamental input to promote and strengthen the STI processes in life sciences and health.They serve as a guide to generate public policies and actions that guarantee better health and well-being for the Colombian population,strategically proposing a clear roadmap for the next 20 years.

The Multiplicative Analytic Hierarchy Process (MIAHP) as a Quality Criterion Determining the Technological Value of the Egyptian Cotton Varieties

This study was undertaken to develop a numerical process that can be used as a quality criterion to determine the technological value of the Egyptian cotton varieties, which in turn would denote the end-use of their fibers. However the material used in the study comprised the 6 Egyptian cotton varieties Giza70, Giza80, Giza86, Giza88, Giza90 and Giza92. According to the local practice in Egypt, Giza70, Giza88 and Giza92 belong to the Extra-Long Staple (ELS) category, while Giza80, Giza86 and Giza90 are included under the Long Staple (LS) category. The regression analysis of the relationships between fiber properties and yarn skein strength (lea product) of the 2 carded ring counts 40 and 50 Ne, was employed to drive an equation for calculating the Multiplicative Analytic Hierarchy Process (MIAHP) values. The values of the MIAHP have been used as numerical determinations of the technological values of the Egyptian cotton varieties. Nevertheless, the findings of this study clarified that with respect to the criteria weights, the pair-wise comparisons denoted that fiber length properties of Egyptian cotton ranked first where they revealed the most dominant effect on yarn strength, while tensile properties ranked second with a relative weight close to that of fiber length. On the contrary, the relative weight of fiber fineness (micronaire reading) was found to be marginal. With regard to the relative weight of sub-criterion, the pair-wise comparisons indicated that the role of fiber tenacity as a determinant of yarn strength is much superior to that of fiber elongation. Further the global weights of the sub-criterion of fiber length pointed out that the UHML (upper half mean length) plays an important role in determining yarn strength of the Egyptian cotton comparing with either the UI (uniformity index) or the SFC (short fiber content). In conformity with the values of the MIAHP, it was found that in the order of descending rank, Giza88 ranked first, followed by Giza92, Giza70, Giza86, Giza80 and finally Giza90.

Study progression in application of process analytical technologies on film coating

Film coating is an important unit operation to produce solid dosage forms,thereby,the monitoring of this process is helpful to find problems in time and improve the quality of coated products.Traditional methods adopted to monitor this process include measurement of coating weight gain,performance of disintegration and dissolution test,etc.However,not only do these methods cause destruction to the samples,but also consume time and energy.There have recently emerged the applications of process analytical technologies(PAT)on film coating,especially some novel spectroscopic and imaging technologies,which have the potential to real-time track the progress in film coating and optimize production efficiency.This article gives an overview on the application of such technologies for film coating,with the goal to provide a reference for the further researches.

学习分析数据互操作规范IMS Caliper Analytics解读

全球的MOOC浪潮推动了在线课程大规模传播和发展,由此产生了海量多样的数据。"大数据"分析技术加速应用到教育领域,评估、分析和利用这些数据对于学习效果的提升有着重要的影响。当前,各类学习系统和学习工具都按其自有的格式存储和传输数据,造成其数据通用性差,而且难以被分享和深度利用。标准化组织IMS针对目前学习系统难以跨平台收集学习数据以及数据标准不一的问题,制定了一项学习分析数据互操作规范——Caliper Analytics,试图解决学习分析中有关以统一的形式收集并分析数据的关键问题。该规范通过"计量组谱"构建记录和存储分析数据的通用格式,并通过"Sensor API"捕获和传递散落在各个平台中的分析数据。这将有利于学习分析的数据交换和跨平台使用,从而让有价值的学习分析数据得以更好地利用。这个统一的标准能促使更有效地实现对在线课程质量、效果及性能的分析;帮助院校、教师和教学设计师等数字化教学内容的开发者测量、修改及迭代教育产品;帮助学习者更好地使用学习分析结果持续提升学习绩效。该规范应用前景广泛,但还将面临数据源的呈现方式、数据自有的目标用途、教育机构的组织文化、分析技术的实施效果以及商业模式上的潜在风险等方面的挑战。

Big Data Analytics in Telecommunications: Literature Review and Architecture Recommendations

This paper focuses on facilitating state-of-the-art applications of big data analytics(BDA) architectures and infrastructures to telecommunications(telecom) industrial sector.Telecom companies are dealing with terabytes to petabytes of data on a daily basis. Io T applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts(POC) on a severely limited BDA technology stack(as compared to the available technology stack), i.e.,we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-the-art lambda architecture for BDA pipeline implementation(called Lambda Tel) based completely on open source BDA technologies and the standard Python language, along with relevant guidelines.We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe Lambda Tel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.

Integrating Research Analytic Framework and Personality Matching for Supervisor Recommendation

Supervisor selection is important for research students in their future studies and careers.Currently,students rely on information search or friends recommendation to find potential research supervisors.However,due to the challenges of incomplete and asymmetric information,students can hardly find suitable supervisors that match their research interests as well as personalities.Existing methods mainly consider topic-relevance and candidate-quality,and overlook the significance of connectivity consideration and two-sided matching degree of individuals personality styles.It proposes a novel supervisor recommendation approach that integrates relevance,connectivity,quality and personality-matching dimensions.The results of user-based evaluations demonstrate that the proposed approach generates more satisfactory recommendations as compared to that of all baseline methods.The present solution has been implemented as a social network recommendation service on ScholarMate.

Processing, Recovery and Analysis of Precious Metals Using Molecular Recogntion Technology

IBC Advanced Technologies' Molecular Recognition Technology(MRT) products,trade named SuperLig,selectively and rapidly bind with target metal ions to remove them from solution.The MRT process can produce a high purity separation product of maximum added value at low cost.In this paper,applications of MRT in the precious metals industry,including selective commercial separations involving Au,Pd,Pt,Rh,and Ru,are described and discussed.Application of MRT to the analytical determination of precious metals is presented.Potential use of MRT in recovering precious metals from end-of-life(EOL) products is discussed.

An Analytical Model for the Electrolyser Performance Derived from Materials Parameters

Hydrogen is seen as a key element for the transition from a fossil fuel based economy to a renewable, sustainable economy. Hydrogen can be used either directly as an energy carrier or as a feedstock for the reduction of CO2 to synthetic hydrocarbons. Hydrogen can be produced by electrolysis, decomposing water in oxygen and hydrogen. This paper presents an overview of the three major electrolysis technologies: acidic (PEM), alkaline (AEL) and solid oxide electrolysis (SOEC). An updated list of existing electrolysers and commercial providers is provided. Most interestingly, the specific prices of commercial devices are also given when available. Despite tremendous development of the PEM technology in the past decades, the largest and most efficient electrolysers are still alkaline. Thus, this technology is expected to play a key role in the transition to the hydrogen society. A detailed description of the components in an alkaline electrolyser and an analytical model of the process are provided. The analytical model allows investigating the influence of the different operating parameters on the efficiency. Specifically, the effect of temperature on the electrolyte conductivity—and thus on the efficiency—is analyzed. It is found that in the typical range of operating temperatures for alkaline electrolysers of 65°C - 220°C, the efficiency varies by up to 3.5 percentage points, increasing from 80% to 83.5% at 65°C and 220°C, respectively.

Using the Analytical Hierarchy Process Model in the Prioritization of Information Assurance Defense In-Depth Measures?—A Quantitative Study

Organizational computing devices are increasingly becoming targets of cyber-attacks, and organizations have become dependent on the safety and security of their computer networks and their organizational computing devices. Business and government often use defense in-depth information assurance measures such as firewalls, intrusion detection systems, and password procedures across their enterprises to plan strategically and manage IT security risks. This quantitative study explores whether the analytical hierarchy process (AHP) model can be effectively applied to the prioritization of information assurance defense in-depth measures. In response to these threats, the President, legislators, experts, and others have characterized cyber security as a pressing national security issue. The methods used in this study consisted of emailing study participants a survey requesting that they prioritize five defense in-depth information assurance measures, anti-virus, intrusion detection, password, smart-cards, and encryption, with a range of responses from 1 - 5 using a Likert scale to consider standard cost, effectiveness, and perceived ease of use in terms of protection of organizational computing devices. The measures were then weighted, based on ranking. A pair-wise comparison of each of the five measures is then made using AHP to determine whether the Likert scale and the AHP model could be effectively applied to the prioritization of information assurance measures to protect organizational computing devices. The findings of the research reject the H0 null hypothesis that AHP does not affect the relationship between the information technology analysts’ prioritization of five defense in-depth dependent variables and the independent variables of cost, ease of use, and effectiveness in protecting organizational devices against cyber-attacks.

Understanding RFID Technology within a Business Intelligence Framework

Radio Frequency Identification (RFID) technology provides new and exciting opportunities for increasing organiza- tional, financial, and operational performance. With its focus on organizational efficiency and effectiveness, RFID technology is superior to barcodes in its ability to provide source automation features that increase the speed and volume of data collection for analysis. Today, applications that employ RFID are growing rapidly and this technology is in a continuous state of evolution and growth. As it continues to progress, RFID provides us with new opportunities to use business intelligence (BI) to monitor organizational operations and learn more about markets, as well as consumer attitudes, behaviors, and product preferences. This technology can even be used to prevent potentially faulty or spoiled products from ending up in the hands of consumers. However, RFID offers significant challenges to organizations that attempt to employ this technology. Most significantly, there exists the potential for RFID to overwhelm data collection and BI analytic efforts if organizations fail to effectively address RFID data integration issues. To this end, the purpose of this article is to explicate the dynamic technology of RFID and how it is being used today. Additionally, this article will provide insights into how RFID technology is evolving and how this technology relates to BI and issues related to data integration. This knowledge has never been more essential. While IT academic research into RFID development and issues has declined in recent years, RFID continues to be a vital area of exploration, especially as it relates to BI in the 21st century.

Transformation and risk assessment of the East Kolkata Wetlands (India)using fuzzy MCDM method and geospatial technology

The East Kolkata Wetlands (EKW) is located on the eastern periphery of the city of Kolkata and extends up to theBidyadhari-Matla River confluence. It is a Ramsar Site and acts as an absorber basin for a large number of con-taminants drained from Kolkata. Agricultural lands, sewage-fed fisheries, garbage dumping fields, horticulture,and built-up areas are included in this protected area, that covers approximately 125 km2. It reveals that climatechange reduces the variety of wetland ecosystem services and increases socio-economic vulnerability and eco-nomic stress. The human encroachment, reclamation of land for agriculture, aquaculture, and urban expansion inand around Kolkata has recently adversely threatened the EKW. The remotely sensed data, socio-economic data,and responses of inhabitants have been used to analyse the EKW’s risk and vulnerability. We employed geospatialanalysis by using the Multi-Criteria Decision Making (MCDM) method using nine risk factors. An in-depth analysisof the EKW using geospatial techniques and the Fuzzy Analytic Hierarchy Process (FAHP) helped to understandthe EKW transformations through vulnerability and risk analysis. The results show that the transformation of thewetland to aquaculture, eutrophication and pollution, road proximity, waste dumping, population density, andgrowth are the main factors for the deteriorating health, quality, and environment of the EKW. It also reveals thatquantitative and qualitative evaluations of ecosystem services, wetland degradation, transformation, and cause-effect rapport should be periodically assessed using scientific methods like FAHP, RS, GIS to formulate resilient,integrated plans and strategy for the sustainable management of the EKW.

Selection of IT Sourcing Alternatives in Public Sector Using the Analytic Hierarchy Process

Recent research carried out in the public sector shows that outsourcing can indisputably bring many benefits to the organizations which master the art of devising, deploying and maintaining outsourcing relationships. However, for many organizations, these benefits remain elusive, while outsourcing projects are usually accompanied by unexpected and often negative effects. The paper focuses on in-depth analysis of the current situation concerning outsourcing of information technology projects （IT-projects） in Slovenian public sector. Presented research initially analyses substantive, procedural and other relevant aspects of outsourcing and provides a set of applicable decision making criteria. Stemming from the analysis results, this paper eventually presents the development of a multi criteria decision-support model based on Analytic Hierarchy Process （AHP） which could facilitate enhanced evaluation, selection and implementation of IT outsourcing projects in the public sector.

Application of Industry： A AHP Method to Technolo Selection for Emerging Case Study of Chinese Biotechnology Enterprises

Selecting the promising technologies to incorporate in new products is challenging for enterprises, especially for those who compete in emerging high-technology industries. By integrating external factor evaluation （EFE） and internal factor evaluation （1FE） matrix, this study proposes a new technology selection method. The proposed fi＇am^work is applied to a real technology selection problem faced by a bio-technology enterprise in the context of China＇ s economic, political and social environment. Two major aspects and 24 external/internal factors are determined. This study uses analytic hierarchy process （AHP） method to sort the information and derives weights of each criterion. Empirical results indicate that the candidate technology is promising, and shall be developed as one of the enterprise＇s primary products.

A survey of data-centric technologies supporting decision-making before deploying military assets

In a time characterized by the availability of vast amounts of data,the effective utilization of information is critical for timely decision-making in military operations.However,processing large amounts of data requires computational resources and time.Therefore,decision makers have used data-centric technologies to take advantage of public and private data sources to support military operations.This survey explores the integration and application of data-centric technologies,such as data analytics,data science,and machine learning,to optimize decision-making workflows within military contexts supporting the deployment of military assets and resources.To address the information gap,this article presents a literature review,specifically a survey.Our survey examines the use of the mentioned technologies to process and analyze information that contributes to the phases of situational awareness,and planning in military environments.We then introduce a taxonomy of the approaches associated with implementing these technologies in military scenarios.Furthermore,we discuss relevant factors for the seamless integration of data-centric technologies into military decision-making processes,and reveal the importance of specialized personnel,architectures,and cybersecurity issues in the task of developing prototypes and models.The findings of this paper aim to provide valuable insights for military institutions,offering a deeper understanding of the use of data-centric technologies as innovative practices to enhance the effectiveness of military decision-making.