Centralized Platform Research Articles

Distributed Incentive Mechanism Based on Hyperledger Fabric

Crowd sensing is a new type of data acquisition method that can efficiently and diversify the realization of sensing tasks. However, this method currently has some problems, such as data storage being overly dependent on third-party platforms, and there is a lack of reliable data credible evaluation methods. To solve this problem, our paper proposes a distributed incentive mechanism based on Hyperledger Fabric (HF-DIM) in the Crowd sensing scenario. In particular, the following questions are studied: How to achieve distributed incentive to solve the traditional incentive that relies on a centralized platform? How to evaluate the credibility of the sensing data provided by the users? To the former question, we implement a multi-attribute auction algorithm based on smart contracts, and distributed incentives are implemented using blockchain deployed contracts. To the latter question, We propose a K-nearest neighbor outlier detection algorithm based on geographic location and similarity to evaluate the credibility of the data and establish a reputation index based on the credibility of the data. Through simulation experiments using real data set, the feasibility and effectiveness of the proposed framework and algorithm are verified.

OPPORTUNITIES, RISKS AND STRATEGIES TO MINIMIZE THE RISK FINTECH LENDING: STUDY META SYNTHESIS

This study aims to configure by identifying opportunities, risks and strategies to minimize the risk ofthe existence of fintech lending as a financial intermediary institution using a meta-synthesis methodological approach. The number of articles sampled as much as 29 articles. The results show that business and investment opportunities in this sector are indicated by a large market share, the number of repeat borrowers, an element of trust between borrowers and lenders, a technology-based and uncomplicated loan system and without business guarantees. While the risk indicated by weaknesses in credit management or credit management is a risk that really needs to be considered, including in determining interest rates, and determining borrowers to be funded without credit analysis considerations. The strategy needed is to use a low interest rate strategy, a better management management strategy, a strategy to capture opportunities as well as a collaboration and growth strategy, as well as the need for the Government to make clear and centralized regulations and P2P platforms.
 
 Keywords: Opportunity, Risk, Fintech Lending Strategy, Meta Synthesis.

Privacy Protection of Task in Crowdsourcing: Policy-Hiding and Attribute Updating Attribute-Based Access Control Based on Blockchain

Crowdsourcing is a new way to solve complex problems by using human intelligence. However, the tasks and user information privacy concerned in crowdsourcing have not been adequately addressed. It is necessary to design a privacy protection mechanism for tasks that need to be restricted to specific user groups. Ciphertext-policy attribute-based encryption (CP-ABE) is an efficient and feasible cryptographic tool, particularly for crowdsourcing systems. The encryptor can choose the access policy independently, which limits the scope of decryption users. At present, most CP-ABE schemes adopt a centralized management platform, which poses problems such as high trust-building costs, DDoS attacks, and single point of failure. In this paper, we propose a new access control scheme based on CP-ABE and blockchain, which has the properties of policy hiding and attribute updating. To protect the privacy of worker’s attributes, we adopt a test algorithm based on a fully homomorphic cryptosystem to confidentially judge whether the worker’s attribute lists match the hidden attributes policy in ciphertext or not before the decryption. Experiment results and comprehensive comparisons show that our mechanism is more flexible, private, and scalable than existing schemes.

Supporting farming smart documentation system by modular blockchain solutions

For more than a decade, various farm-specific models have been developed by collaborating and integrating sensing technologies as a step toward successful data-farm documentation and effective decision-making. However, the stored and gathered data continues to rely on cloud infrastructure or centralized platform control, which is particularly vulnerable to threats such as data tampering, data distortion, confidentiality, and manipulation, which caused the farm product data difficult to trace to its provenance. In this paper, we propose a farm transaction model by demonstrating a flow of farm transaction simulation implicated by MBC sensing instrument with an array of sensors, controllers, networking hardware, computing equipment, and internal memory functions to enhance data integrity and security farm object. Based on the proposed model, a proof-of-concept experimental system called Encapsulating Block Mesh (EBM) integrates blockchain technology with the specific application case of cocoa production has been implemented. Results have shown that farm objects represented by MBC take turn recording information on the process of generating, transacting, and consuming a farm product and encrypting it into a block was validated and linked in the EBM with the hash of transaction data that connected to each cocoa farm object in a simulation environment.

Pengembangan Kecerdasan Buatan Whatsapp Chatbot untuk Mahasiswa

A chatbot is an artificial intelligence-based computer program that can carry out conversations via audio or text. This study intends to identify and analyze the types of artificial intelligence in the form of chatbots and their possible use as chatbot-based communication media. Currently, the practice in most is that branch employees need to consult with the central employees or search through official websites for work-related information. However, the process of obtaining the required information can take some time ranging from minutes to hours and is sometimes inconsistent as questions are answered by different employee members. There are WhatsApp chat groups for branch employees to interact with central employees, but group chats can be overwhelmed by questions due to the large number of members causing important messages to be ignored. In an effort to overcome this challenge, we developed a WhatsApp chatbot to overcome this problem by offering a centralized platform of communication for central employees and branch employees to share information via WhatsApp messages. Communication in the form of personalized messages between chatbots and users thus solving the overwhelming messaging problem that group chats pose. The Agile Kanban methodology was used to develop a system that promotes the use of Kanban boards to visualize development stages. A questionnaire is distributed to branch employees, head office employees and managers to test the system and collect opinions and suggestions from target users to assess whether the system is meeting its objectives. The biggest benefit of the Kanban methodology is the ability to continuously improve work. It can be used in any work environment and is great in situations where work arrives unexpectedly.

Fleet Management and Charging Scheduling for Shared Mobility-on-Demand System: A Systematic Review

Challenged by urbanization and increasing travel needs, existing transportation systems call for new mobility paradigms. In this article, we present the fleet management and charging scheduling of a shared mobility-on-demand system, whereby electric vehicle fleets are operated by a centralized platform to provide customers with mobility service. We provide a comprehensive review of system operation based on the operational objectives. The fleet scheduling strategies are categorized into four types: i) order dispatching, ii) order-dispatching and rebalancing, iii) order-dispatching, rebalancing and charging, and iv) extended. Specifically, we first identify mathematical modeling techniques implemented in the transportation network, then analyze and summarize the solution approaches including mathematical programming, reinforcement learning, and hybrid methods. The advantages and disadvantages of different models and solution approaches are compared. Finally, we present research outlook in various directions.

Colombia’s GHG Emissions Reduction Scenario: Complete Representation of the Energy and Non-Energy Sectors in LEAP

The signatory countries of the Paris Agreement must submit their updated Intended National Determined Contributions (INDCs) to the UNFCCC secretariat every five years. In Colombia, this activity was historically carried out with a wide set of diverse non-interconnected sector-specific models. Given the complexity of GHG emissions reporting and the evaluation of mitigation actions on a national scale, the need for a centralized platform was evident. Such approach would allow the integration and analysis of potential interactions among sectors, as well as to guarantee the homogeneity of assumptions and input parameters. In this paper, we describe the construction of an integrated bottom-up LEAP model tailored to the Colombian case, which covers all IPCC sectors. An integrated model facilitates capturing synergies and intersectoral interactions within the national GHG emissions system. Hence, policies addressing one sector and influencing others are identified and correctly assessed. Thus, 44 mitigation policies and mitigation actions were included in the model, in this way, identifying the sectors directly and being indirectly affected by them. The mitigation scenario developed in this paper reaches a reduction of 28% of GHG emissions compared with the reference scenario. The importance of including non-energy sectors is evident in the Colombian case, as GHG emission reductions are mainly driven by AFOLU. The first section describes the GHG emissions context in Colombia. Next, we describe the model structure, main input parameters, assumptions, considerations, and used LEAP functionalities. Results are presented from a GHG emissions accounting and energy demand perspective. The model allows for the correct estimate of the scope and potential of mitigation actions by considering indirect, unintended emissions reductions in all IPCC categories, as well as synergies with all mitigation actions included in the mitigation scenario. Moreover, the structure of the model is suitable for testing potential emission trajectories, facilitating its adoption by official entities and its application in climate policymaking.

Towards an Integrated Vehicle Management System in DriveOS

Modern automotive systems feature dozens of electronic control units (ECUs) for chassis, body and powertrain functions. These systems are costly and inflexible to upgrade, requiring ever increasing numbers of ECUs to support new features such as advanced driver assistance (ADAS), autonomous technologies, and infotainment. To counter these challenges, we propose DriveOS, a safe, secure, extensible, and timing-predictable system for modern vehicle management in a centralized platform. DriveOS is based on a separation kernel, where timing and safety-critical ECU functions are implemented in a real-time OS (RTOS) alongside non-critical software in Linux or Android. The system enforces the separation, or partitioning, of both software and hardware among different OSes. DriveOS runs on a relatively low-cost embedded PC-class platform, supporting multiple cores and hardware virtualization capabilities. Instrument cluster, in-vehicle infotainment and advanced driver assistance system services are implemented in a Yocto Linux guest, which communicates with critical real-time services via secure shared memory. The RTOS manages a real-time controller area network (CAN) interface that is inaccessible to Linux services except via well-defined and legitimate communication channels. In this work, we integrate three Qt-based services written for Yocto Linux, running in parallel with a real-time longitudinal controller task and multiple CAN bus concentrators, for vehicular sensor data processing and actuation. We demonstrate the benefits and performance of DriveOS with a hardware-in-the-loop CARLA simulation using a real car dataset.

Secure Internal Data Markets

The data market concept has gained a lot of momentum in recent years, fuelled by initiatives to set up such markets, e.g., on the European level. Still, the typical data market concept aims at providing a centralised platform with all of its positive and negative side effects. Internal data markets, also called local or on-premise data markets, on the other hand, are set up to allow data trade inside an institution (e.g., between divisions of a large company) or between members of a small, well-defined consortium, thus allowing the remuneration of providing data inside these structures. Still, while research on securing global data markets has garnered some attention throughout recent years, the internal data markets have been treated as being more or less similar in this respect. In this paper, we outline the major differences between global and internal data markets with respect to security and why further research is required. Furthermore, we provide a fundamental model for a secure internal data market that can be used as a starting point for the generation of concrete internal data market models. Finally, we provide an overview on the research questions we deem most pressing in order to make the internal data market concept work securely, thus allowing for more widespread adoption.

FCSIT WhatsApp Chatbot

WhatsApp is currently one of the most widely used communication mediums among students in tertiary education in the form of both personal messages and group messaging chats. Currently, the practice in most Malaysian Universities is that students need to consult the faculty staff or search through the faculty’s website to obtain information related to their academic studies. However, the process of obtaining needed information can take some time ranging from minutes to hours and at times are not consistent as the queries are answered by different staff members. There are WhatsApp chat groups for students to interact with faculty staff, but the chat group can be overwhelmed by questions due to the huge number of group members hence causing important messages to be overlooked. In an attempt to overcome these challenges, we developed a FCSIT (Faculty of Computer Science and Information Technology) WhatsApp chatbot to solve these problems by offering a centralized platform of communication for both faculty staff and students to carry out information sharing through WhatsApp messages. Communication is in the form of personalized messages between the chatbot and the user thus solving the problem of overwhelming messages posed by group chats. Agile Kanban methodology was used to develop the system which promotes the use of a Kanban board to visualize the development stages. A questionnaire was distributed to lecturers, faculty staff and students to test the system and to gather opinions and suggestions from targeted users, which is the FCSIT community, in order to assess whether the system fulfils its objectives.

Seamless security apprise method for improving the reliability of sustainable energy-based smart home applications

Smart homes rely on sustainable energy sources and information technologies for providing ambient assisted living (AAL) support for humans. The significance of automation and energy optimization is prominent in providing secure and reliable control over in-home applications. Security is one of the drawbacks in smart home scenarios where the connected network of applications and sustainable energy sources are exposed to risk. This article introduces the seamless security apprises method (SSAM) to monitor the connected network's administered security measure. The proposed method monitors the lifetime of the administered security measures by verifying its exploitation and vulnerable levels in a periodic manner. In this verification process, the distributed security is classified for different operating and communicating states of the connected applications. For this state-based analysis, Q-learning is adapted to identify and update the state and its associated security measure. It reduces the early termination of the security measure due to identity thefts and provides continuous support for the operating applications. Therefore, sustainable energy resources are efficiently exploited without facing convergence in application functions. The cyber security features of the connected network are exploited in administering the security from a centralized platform. The proposed method's performance is verified using the verification time, security level, energy efficiency, and security loss.

The Rhododendron Plant Genome Database (RPGD): a comprehensive online omics database for Rhododendron

BackgroundThe genus Rhododendron L. has been widely cultivated for hundreds of years around the world. Members of this genus are known for great ornamental and medicinal value. Owing to advances in sequencing technology, genomes and transcriptomes of members of the Rhododendron genus have been sequenced and published by various laboratories. With increasing amounts of omics data available, a centralized platform is necessary for effective storage, analysis, and integration of these large-scale datasets to ensure consistency, independence, and maintainability.ResultsHere, we report our development of the Rhododendron Plant Genome Database (RPGD; http://bioinfor.kib.ac.cn/RPGD/), which represents the first comprehensive database of Rhododendron genomics information. It includes large amounts of omics data, including genome sequence assemblies for R. delavayi, R. williamsianum, and R. simsii, gene expression profiles derived from public RNA-Seq data, functional annotations, gene families, transcription factor identification, gene homology, simple sequence repeats, and chloroplast genome. Additionally, many useful tools, including BLAST, JBrowse, Orthologous Groups, Genome Synteny Browser, Flanking Sequence Finder, Expression Heatmap, and Batch Download were integrated into the platform.ConclusionsRPGD is designed to be a comprehensive and helpful platform for all Rhododendron researchers. Believe that RPGD will be an indispensable hub for Rhododendron studies.

Decentralized Stock and Cryptocurrency Exchange

We propose a new blockchain-based framework for a completely decentralized stock market and bitcoin exchange in this paper. By proposing a groundbreaking framework utilizing blockchain to build a decentralized bitcoin and stock exchange network, this paper discusses the shortcomings of conventional centralized stock exchange platforms, High transaction costs, vulnerable centralized governance, and a lack of clarity in consumer behavior and algorithms are just a few of the problems. Blockchain technology consists of a large number of computer nodes that share a shared ledger securely without the need for intermediaries of any sort. The proposed blockchain-based solution addresses the disadvantages of the centralized stock exchange architecture by ensuring the integrity and security of the properties and orders of the owner, by self-enforcing intelligent agreements between parties, and by consensus algorithms, by achieving democratic and effective decisions on the execution and settlement of orders. Intelligent contracts are used in the proposed architecture to enforce the validation of the owner's rights as well as the proper execution and settlement of orders, reducing the need for a central authority to ensure that the stock exchange process is accurate. The proposed system proposes a hybrid platform that incorporates cryptocurrency and stock trading. The solution was tested for a subset of rules for the Stock Exchange by implementing a prototype in Ethereum.

ФОРМУВАННЯ СУСПІЛЬНОЇ ЦІННОСТІ НА ОСНОВІ НАЯВНИХ ПЛАТФОРМНИХ РІШЕНЬ У ПУБЛІЧНОМУ СЕКТОРІ

The paper offers a substantiation of directions and essence of building up public value by implementing decentralized information platforms within the existing GaaP model based on government centralized platforms. The paper provides a critical analysis of the most resonant and significant foreign government centralized platforms from the UK, India, Estonia, Italy and Ukraine. Their example indicates the technological way of forming new public value using three main mechanisms of adjustment of business processes. While comparing with the existing practice of using centralized platforms, the author proposes a new meaning of building up public value through the introduction of decentralized information platforms. An important conclusion has been made that despite governments being skeptical about integrating state databases with registers based on blockchain, such integration is very likely to happen in 2–3 years, which will be possible due to introduction of new web modules and recognition of trusted private registers based on blockchain. The configuration of the existing organizational GaaP model allows creating additional public value and mobilizing state and private resources to arrange various configurations of public services. For this purpose, in each country, not only the GaaP model, but the three known mechanisms for its provision should be organized properly. In order to create a greater expected public value, public authorities need to correlate and coordinate the contributions of interested private and state entities to better meet different expectations and needs and avoid the consequences of opportunistic actions by third parties. Without the effective orchestration mechanisms, the GaaP model risks to have a significantly negative impact on society and creation of public value. The foreign experience shows that adoption of platform organization is not an absolute condition for a greater public value yet. State governance also requires greater functionality of mechanisms for organizing business processes (orchestration, choreography and deployment of small ecosystems) in terms of provision of public value from centralized information platforms for simultaneous support of different service delivery processes to select the optimal configuration of the method of public service delivery, the benefit of which can be appreciated only by its consumers-citizens and only if there is at least one alternative.

Centralizing Over-the-Counter Markets?

In traditional over-the-counter (OTC) markets, investors trade bilaterally through intermediaries referred to as dealers. An important regulatory question is whether to centralize OTC markets by shifting trades onto centralized platforms. We address this question in the context of the liquid Canadian government bond market. We document that even in this market, dealers charge markups, and show that there is a price gap between large investors who have access to a centralized platform and small investors who do not. We specify a model to quantify how much of this price gap is due to platform access and assess welfare effects. The model predicts that not all investors would use the platform even if platform access were universal. Nevertheless, the price gap would close by 32%-47%. Welfare would increase by 9%-30% because more trades are conducted by dealers who have high values to trade, for instance, because they seek to sell inventory.

Algorithmic matching of personal protective equipment donations with healthcare facilities during the COVID-19 pandemic

GetUsPPE.org has built a centralized platform to facilitate matches for PPE donations, with an active role in matching donors with the appropriate recipients. A manual match process was limited by volunteer hours, thus we developed an open-access matching algorithm using a linear programming-based transportation model. From April 14, 2020 to April 27, 2020, the algorithm was used to match 83,136 items of PPE to 135 healthcare facilities in need across the United States with a median of 214.3 miles traveled, 100% of available donations matched, met the full quantity of requested PPE for 67% of recipients matched, and with 46% matches under 30 miles traveled. Compared with the period April 1, 2020 to April 13, 2020, when PPE matching was manual, the algorithm resulted in a 280% increase in matches/day. This publicly available automated algorithm could be deployed in future situations when the healthcare supply chain is insufficient.

COVID-19 and the rise of virtual medicine in spine surgery: a worldwide study

PurposeThe COVID-19 pandemic forced many surgeons to adopt “virtual medicine” practices, defined as telehealth services for patient care and online platforms for continuing medical education. The purpose of this study was to assess spine surgeon reliance on virtual medicine during the pandemic and to discuss the future of virtual medicine in spine surgery.MethodsA comprehensive survey addressing demographic data and virtual medicine practices was distributed to spine surgeons worldwide between March 27, 2020, and April 4, 2020.Results902 spine surgeons representing seven global regions responded. 35.6% of surgeons were identified as “high telehealth users,” conducting more than half of clinic visits virtually. Predictors of high telehealth utilization included working in an academic practice (OR = 1.68, p = 0.0015) and practicing in Europe/North America (OR 3.42, p < 0.0001). 80.1% of all surgeons were interested in online education. Dedicating more than 25% of one’s practice to teaching (OR = 1.89, p = 0.037) predicted increased interest in online education. 26.2% of respondents were identified as “virtual medicine surgeons,” defined as surgeons with both high telehealth usage and increased interest in online education. Living in Europe/North America and practicing in an academic practice increased odds of being a virtual medicine surgeon by 2.28 (p = 0.002) and 1.15 (p = 0.0082), respectively. 93.8% of surgeons reported interest in a centralized platform facilitating surgeon-to-surgeon communication.ConclusionCOVID-19 has changed spine surgery by triggering rapid adoption of virtual medicine practices. The demonstrated global interest in virtual medicine suggests that it may become part of the “new normal” for surgeons in the post-pandemic era.

Design of an Interactive Geo-Location Mobile Application for Civil Societies in East Africa

This paper reports the developed mobile application through the use of advanced technologies such as mobile computing, cloud computing and Global Positioning System (GPS) in order to solve the challenges. The purpose of this study is find out how the recent advances and mass adoption of ICT by the public can best be leveraged to enhance the performance of Civil Society Organizations (CSOs) in East Africa. The data collection techniques used are through questionnaires, observations and conducting interviews with different stakeholders in the civil society arena i.e., the donors, the CSOs and the people in society that are given a voice by civil societies. In the system development phase, agile development methodology was used. Analysis of the data collected showed that there is a gap in the availability of a single or a centralized platform which can be easily accessed, user-friendly and reliable where different actors can readily get reliable and up-to-date information about the available CSOs they are interested in. To address this problem, an interactive online directory of CSOs has been developed. The platform is mobile based and enables CSOs to register and fill up their current details, thus ensuring that there is always correct and updated information. The platform is equipped with, among other features, a geo-mapping facility which enables users of the system to correctly geo-locate their civil societies of interest on a map view. The results of system evaluation showed that 88.125% of users were satisfied with the system basing on the evaluation criteria.

Central Bank Digital Loonie: Canadian Cash for a New Global Economy

Global economic digitization continues to advance at exponential speed. This development is in sharp contrast to the financial sector and payment systems that still operate on legacy infrastructure that lacks the flexibility to serve those technology needs. Further, the emergence of Decentralized Finance demonstrates the capacity to disrupt the financial sector, impact national sovereignty, and affect established monetary transmission channels. Hence, it is no surprise that nation-states and tech-firms alike are now building new digital infrastructures that circumvent the legacy practices. Central banks, in particular, are racing to explore the issuance of Central Bank-issued Digital Currencies (CBDCs) in an attempt to rediscover the very essence and use of fiat cash. In the past decade, the Bank of Canada (BoC) has emerged as an international thought leader on CBDCs. In early 2020, the BoC issued a contingency plan for the potential introduction of a CBDC and later that spring ran a global competition among universities to sample arm length’s designs. Being a finalist in this competition, this manuscript presents a design proposal for a Central Bank Digital Loonie (CBDL) based on careful academic research of the possible technological, legal, and economic components of such an unprecedented and historic expedition. We propose a two-phased approach. In the first phase, the BoC introduces a centralized platform as a public-good infrastructure that establishes digital cash and ensures global/domestic interoperability. In this phase, e-KYC-based authentication leverages existing private/public sector solutions but also safeguards users' privacy/data against third-party commercial interests while complying with AML/CFT. In the second phase, the BoC will expand the platform to an enterprise-level permissioned blockchain. This shared resource will transform CBDLs into programmable e-money within a “social operating system” that will enable Canadians to operate, innovate, compete, and thrive in this new global digital economy.

Blockchain-Enabled EHR Framework for Internet of Medical Things

The Internet of Medical Things (IoMT) offers an infrastructure made of smart medical equipment and software applications for healthcare services. Through the internet, the IoMT is capable of providing remote medical diagnosis and timely health services. The patients can use their smart devices to create, store and share their electronic health records (EHR) with a variety of medical personnel including medical doctors and nurses. However, unless the underlying commination within IoMT is secured, malicious users can intercept, modify and even delete the sensitive EHR data of patients. Patients also lose full control of their EHR since most healthcare services within IoMT are constructed under a centralized platform outsourced in the cloud. Therefore, it is appealing to design a decentralized, auditable and secure EHR system that guarantees absolute access control for the patients while ensuring privacy and security. Using the features of blockchain including decentralization, auditability and immutability, we propose a secure EHR framework which is mainly maintained by the medical centers. In this framework, the patients’ EHR data are encrypted and stored in the servers of medical institutions while the corresponding hash values are kept on the blockchain. We make use of security primitives to offer authentication, integrity and confidentiality of EHR data while access control and immutability is guaranteed by the blockchain technology. The security analysis and performance evaluation of the proposed framework confirms its efficiency.