Single Client Research Articles

Counterparty credit risk: Lessons from recent events

This paper looks at the lessons learned for risk management from two recent events, the default of Archegos Capital Management in March 2021 and the unusually large price jumps in energy markets in summer 2022. The paper finds that the counterparty exposure from margined derivatives transactions exceeded the required initial margin significantly in both cases, so that the exposures were largely uncollateralised when it mattered. In addition, the standardised approach for counterparty credit risk (SA-CCR) resulted in regulatory capital requirements which were insufficient to cover the banks' losses from the unwinding of large and concentrated derivatives exposures. This made it difficult, even for some large banks, to identify the high loss potential of the transactions with a single client.

Literature Review and Analysis of Workplace Counseling and Mental health in Taiwan

<p>諮商心理理論與實務在企業中實踐員工諮商與心理健康。本研究旨在回顧台灣地區企業員工諮商與心理健康文獻，有助於了解台灣企業員工諮商與心理健康研究的發展背景。本研究採用文獻回顧分析了解台灣地區有關企業員工諮商與心理健康迄今的研究成果，探討重要研究變項。研究資料來源為「台灣期刊論文索引系統」、「華藝資料庫」，以企業諮商、員工協助方案、職場心理健康等關鍵字進行資料搜尋，迄2022年4月止，符合本研究目的的論文共51筆。研究結果顯示：(一) 研究類別依序為諮商輔導與教育心理類 (73％)、管理與勞工安全類 (20%)、醫療與健康類（8%）。(二) 研究方法依序為文獻回顧（35%）、實務應用 (27%)、質性 (22%)、量化 (12%)、質量混合 (4%)，研究內容包含企業員工諮商對員工工作效率影響、職場心理健康等。(三) 論文發表以2016-2021年期間發表量占總論文數量之42%為最高。(四) 51篇論文中僅有8篇量化研究，且多著重在壓力來源的探討與員工諮商使用意願調查，未將員工諮商與員工請假或生產力變化做連結；13篇質性研究中有5篇均提及企業諮商師的倫理觀點由單一案主轉移至雙重案主，最大的挑戰在於如何兼顧個案守密倫理原則與提供企業主諮商效益的數據化分析。(五) 在台灣，企業員工諮商與心理健康實證研究多以質性訪談為主，較少量化分析，且分析結果多與員工主觀滿意感受相關，未與員工請假時數或生產力等客觀數字作關聯分析。本研究除了將51筆企業員工諮商與心理健康文獻做描述性統計之分析外，同時整理了其中8篇量化研究（包含2篇質量混合研究）之量化研究方法及研究結果提供未來研究之參考。</p> <p> </p><p>Applying the theories and methods of counseling psychology in an enterprise is the core of workplace counseling and mental health. Reviewing related research on workplace counseling and mental health can facilitate understanding the development of workplace counseling and mental health research in Taiwan. This study adopted the literature review to understand the research results of workplace counseling and mental health in Taiwan. The key words of workplace counseling, employee assistance programs, and workplace mental health were used to conduct the search in the " Index to Taiwan Periodical Literature System" and "Airiti Library". Up until April 2022, there were 51 papers that matched the purpose of the study and were thus selected and analyzed. The results indicated that: (1) The research categories are counseling and education (73%), management and labor safety (20%), medical care and health (8%). (2) The research methods are literature review (35%), practical application (27%), qualitative research (22%), quantitative research (12%), and mixed methods research (4%). The contents of workplace counseling involved employee work efficiency, mental health, etc. (3) The papers on workplace counseling and mental health with the period of 2016 to 2021 accounting for 42% of all 51 papers. (4) Among the 51 papers, there are only 8 quantitative studies, and most of them focus on the discussion of the source of stress and the survey of employees’ willingness to use counseling. They do not link employee counseling with employees’ leave or productivity changes, 5 of the 13 qualitative studies mentioned that the ethical viewpoint of business counselors has shifted from a single client to dual client. The biggest challenge for workplace counselors were how to balance the ethical principles of client confidentiality and the benefits of counseling for business owners. (5) In Taiwan, most of the empirical researches on workplace counseling and mental health were based more on qualitative interviews than on quantitative analysis, the analysis results were based on personal feelings of employees’ satisfaction, and no analysis was conducted concerning objective factors such as employee absent hours or productivity. In addition to the descriptive statistical analysis of 51 corporate consultation documents, this study also sorted out the quantitative research methods and research results of 8 quantitative studies (including 2 qualitative mixed studies) to provide reference for future research. According to these findings, detailed results and suggestions for further research were discussed.</p> <p> </p>

F-FNC: Privacy concerned efficient federated approach for fake news classification

Fake news and manipulated information affect the social, economic and emotional growth of the world's population.For the identification of fake news, several classification systems are available, but no such system was found fast, secure and reliable as per the need of the hour. In this work, an efficient framework based on the federated architecture for the classification of fake news was proposed, while maintaining the data privacy constraints for sensitive text news datasets. The proposed federated-Fake New Classification (f-FNC) framework utilized the distributed client–server architecture with data privacy of all client or connected edge devices. For the testing and evaluation of the proposed f-FNC framework, the non-identical data was gathered from several online resources and was disseminated in a pre-processed format. To test the validity of federated deep learning models, the experiments were performed under various scenarios such as traditional learning, federated learning single client, and federated learning multi-clients. The performance of f-FNC framework was evaluated through various computational parameters such as accuracy and loss validation along with available resource parameters including CPU and RAM utilization. It was observed from the resultant outcome that the proposed f-FNC framework worked significantly well in both single-client and multi-client (N-clients) scenarios in comparison to traditional distributed deep learning based classifiers. The additional features of low cost and data-privacy of edge devices with limited resources made this proposed framework unique and the best alternative to existing fake news classifier tools.

Federated Learning Based Fault Diagnosis Driven by Intra-Client Imbalance Degree.

Federated learning is an effective means to combine model information from different clients to achieve joint optimization when the model of a single client is insufficient. In the case when there is an inter-client data imbalance, it is significant to design an imbalanced federation aggregation strategy to aggregate model information so that each client can benefit from the federation global model. However, the existing method has failed to achieve an efficient federation strategy in the case when there is an imbalance mode mismatch between clients. This paper aims to design a federated learning method guided by intra-client imbalance degree to ensure that each client can receive the maximum benefit from the federation model. The degree of intra-client imbalance, measured by gain of a class-by-class model update on the federation model based on a small balanced dataset, is used to guide the designing of federation strategy. An experimental validation for the benchmark dataset of rolling bearing shows that a 23.33% improvement of fault diagnosis accuracy can be achieved in the case when the degree of imbalance mode mismatch between clients is prominent.

The goods (and bads) of self‐employment

The goods (and bads) of <scp>self‐employment</scp>

An Asynchronous Federated Learning Arbitration Model for Low-Rate DDoS Attack Detection

Low-rate Distributed Denial of Service (LDDoS) attacks have been one of the most notorious network security threats, which use periodic slight multi-variate time series pulse flows to degrade network quality. Limited by the poor data in a single client, a powerful and satisfactory LDDoS attack detection model is hard to be trained. Federated Learning (FL) is a promising paradigm offering joint learning through multiple clients. We propose an asynchronous federated learning arbitration framework based on bidirectional LSTM (bi-LSTM) and attention mechanism (AsyncFL-bLAM). In the AsyncFL-bLAM, the leader node election algorithm is proposed for constructing the framework of asynchronous federated learning. The proposed bLAM model composed of feature extracter and arbitrator takes on the responsibility of LDDoS detection locally. Furthermore, the novel AsyncFL framework helps to upload and aggregate the bLAM models’ parameters asynchronously between leader node and client nodes. Experimental results show that the AsyncFL-bLAM outperforms the state-of-the-art models in accuracy, and reduces the overall communication rounds.

FedBERT: When Federated Learning Meets Pre-training

The fast growth ofpre-trained models(PTMs) has brought natural language processing to a new era, which has become a dominant technique for variousnatural language processing(NLP) applications. Every user can download the weights of PTMs, then fine-tune the weights for a task on the local side. However, the pre-training of a model relies heavily on accessing a large-scale of training data and requires a vast amount of computing resources. These strict requirements make it impossible for any single client to pre-train such a model. To grant clients with limited computing capability to participate in pre-training a large model, we propose a new learning approach,FedBERT, that takes advantage of the federated learning and split learning approaches, resorting to pre-training BERT in a federated way.FedBERTcan prevent sharing the raw data information and obtain excellent performance. Extensive experiments on seven GLUE tasks demonstrate thatFedBERTcan maintain its effectiveness without communicating to the sensitive local data of clients.

PECULIARITIES OF USING ERP- AND CRM-SYSTEMS FOR AUTOMATION OF ENTERPRISE MANAGEMENT

This publication is devoted to the problem of informatization and automation of management at the enterprise. The study found that the use of innovative systems is becoming increasingly popular in the Ukrainian market. Automation plays a crucial role in ensuring the growth of efficiency indicators of economic activity, but among domestic enterprises, there is a problem in choosing the use of a particular information system. This article describes the main advantages and disadvantages of ERP and CRM systems. Approaches to definitions are defined, and the concepts of ERP and CRM as methodologies of effective resource planning and system of automation of interaction with clients are revealed. A comparative analysis of ERP and CRM systems is carried out. The main functions of CRM systems are studied, among which: are the formation of a single information client base; working time management; optimization of communications within the company; sales planning. The place of the customer in the customer relationship management system is determined. The main modules of the ERP system are analyzed, namely: finance, personnel, sales, procurement, production, logistics, service, research and development, and assets. A detailed description of the functional solution when using the resource management system is given. The main tools of ERP and CRM systems are identified. As a result of the analysis of the modern market of information systems the main suppliers of software products and their weight in the given market segment are defined. A number of software products of ERP and CRM systems popular in Ukraine have been studied. The level of implementation of CRM systems by industry structure is determined. It is established that the maximum result from the implementation of CRM systems is possible only when they are implemented together with the integrated internal ERP system.

‘A Real Gap’: Consequences of Removing Reintegration Support in Tasmania, Australia

As Australian imprisonment and recidivism rates continue to rise, it is increasingly important to better understand how to support “returning citizens” to adequately prepare them for post-release life. Using a case study approach focused on service provider perspectives, this article examines the consequences of removing a transitional accommodation support service on service providers and returning citizens. Participants highlighted significant consequences, such as: gaps in services; lack of support and housing; persons remaining in the system unnecessarily; persons being released without transitional support or accommodation; health implications; loss of relationships and trust; and suicide of returned citizens. Drawing on critical criminological theory, we argue that the most significant consequence was the loss of “floating support”—which involves a case worker who brokers support between agencies working with a single client—that was integrated into the program. Study findings suggest serious consequences of government decisions to defund programs in this sector.

OAuth 2.0 : Architectural design augmentation for mitigation of common security vulnerabilities

OAuth 2.0 is a widely used authorization protocol for cloud based web services and is used by many big firms such as Google, Facebook, Microsoft for granting limited access to the data. OAuth 2.0 has a flexible design and can be implemented and configured in a number of ways according to the use case. However, each of these implementation decisions and configuration choices come with their respective security implications. In our research, we carry out a simulation of the OAuth 2.0 protocol and suggest additional features which can augment the architectural design and enhance overall security effectiveness of the protocol. The protocol classifies third-party client apps based on their ability to maintain the confidentiality of the secret keys and the method used by them to register with the authorization servers. The protocol further offers various options to send access tokens to third-party client apps. In our research, we suggest converging these different third-party client app types and implementation options into a single uniform client app type and operational flow, thereby reducing the complexity in decision making, implementation, security misconfigurations and maintenance of different codebases. We also propose incorporating 2FA (Two Factor Authentication) as a feature for authentication of third-party client apps in addition to the existing mechanism of basic authentication through client secret. We also advocate measures to utilize digital signatures and cryptography to mitigate the common risks and vulnerabilities associated with misuse of tokens, which are issued and exchanged at various stages of the OAuth process including access to protected resources.

General ChatBot for Medical Applications

Applications for chat bots (and voice bots) are being used more frequently in customer care or e-commerce as a direct line of communication between businesses and customers. A software programm known as a bot executes automated, repetitive, and pre-defined tasks. For people, it would be nearly impossible to respond to every single client question. The benefit of employing the notion of a bot is that it eliminates the laborious process of manually responding to customer requests. A bot handles everything automatically. Artificial intelligence is a concept that chatbots employ to communicate with people. It has security features like the ability to deactivate accounts that are sending unsolicited messages. We introduce the bot framework in this paper. Bot is a runtime engine that launches the chatbot programme automatically. and controls security. Bot is freely accessible and open source online.

Supportive Expressive Therapy for Generalized Anxiety Disorder in Client with Burst Fractures Frankle - C

This article presents a case study of a client with burst fracture frankle-C. This client also has generalized anxiety disorder. Supportive expressive therapy was used as therapeutic intervention. A burst fracture is a type of traumatic spinal injury in which a vertebra breaks from a high-energy axial load. The psychological problems often experienced by persons with body disabilities, such as burst fracture francle-C. This is a quantitative research with a single client. While collecting the data, used interview methods (autoanamnesa and alloanamnesa), observation, and psychological tests (DAP, BAUM, BAI, and Sack’s Sentence Completion Test). The result before the practitioner gives the Beck Anxiety Inventory, the client’s anxiety is 20 (moderate anxiety), after intervention 15 (mild anxiety), and follow up 11 (mild anxiety). In addition, the client is also better able to understand his condition and the problems being faced. The catharsis process that has happened so far makes the client able to express what he feels and thinks so as to make the client feel the perceived burden is reduced. Clients can begin to open up to family members at home and conduct simple chats when parents are at home to reduce the habit of repression that was previously done. The technique and also the process of the therapeutic process along the therapy session will be discussed in detail.

Applying the Healthy Eating Index-2015 in a Sample of Choice-Based Minnesota Food Pantries to Test Associations Between Food Pantry Inventory, Client Food Selection, and Client Diet

BackgroundFood pantry clients are at a high risk for diet-related chronic disease and suboptimal diet. Relatively little research has examined diet quality measures in choice-based food pantries where clients can choose their own food. ObjectiveThis study tested whether the diet quality scores for food at the pantry were associated with client food selection scores, and whether client food selection scores at the pantry were associated with client diet intake scores. DesignThis cross-sectional regression analysis, part of a larger evaluation study (SuperShelf), used baseline data from client and food pantry surveys, food pantry inventories, assessments of client food selections (“client carts”), and single 24-hour client dietary recalls. Participants/settingThe analysis includes 316 clients who completed a survey (282 of whom completed a dietary recall measure) from one of 16 choice-based Minnesota food pantries during 2018-2019. Adult English, Spanish, or Somali-speaking clients were eligible in the case that they had selected food on the day of recruitment at their food pantry visit. Main outcome measuresA Healthy Eating Index-2015 (HEI-2015) Total score and 13 subcomponent scores were calculated for: pantry food inventories of food available on the shelf, client carts, and a 24-hour client dietary recall. Statistical analysisDescriptive statistics were generated for client and food pantry characteristics, and for HEI-2015 Total score and subcomponent scores. Linear regression models tested the association between HEI-2015 Total score and subcomponent scores for food pantry inventory and client carts, and for client carts and dietary recalls, adjusted for covariates. ResultsFood pantry inventory HEI-2015 Total score averaged 65.1, client cart Total score averaged 60.8, and dietary recall Total score averaged 50.9. The diet quality scores for inventory were not associated with client cart scores, except for Added Sugars (P = .005). Client cart HEI-2015 Total score was positively associated with client diet HEI-2015 Total score (P = .002) and associations for Total Fruits, Whole Fruits, Total Vegetables, Greens and Beans, Whole Grains, Seafood and Plant Proteins, and Added Sugars subcomponents were statistically significant. ConclusionsIn choice-based Minnesota food pantries, the diet quality of food selected by clients was positively associated with client diet quality.

The Perceived Impact and Usability of a Care Management and Coordination System in Delivering Services to Vulnerable Populations: Mixed Methods Study

BackgroundPeople with complex needs, such as those experiencing homelessness, require concurrent, seamless support from multiple social service agencies. Sonoma County, California has one of the nation’s largest homeless populations among largely suburban communities. To support client-centered care, the county deployed a Care Management and Coordination System (CMCS). This system comprised the Watson Care Manager (WCM), a front-end system, and Connect 360, which is an integrated data hub that aggregates information from various systems into a single client record.ObjectiveThe aim of this study is to evaluate the perceived impact and usability of WCM in delivering services to the homeless population in Sonoma County.MethodsA mixed methods study was conducted to identify ways in which WCM helps to coordinate care. Interviews, observations, and surveys were conducted, and transcripts and field notes were thematically analyzed and directed by a grounded theory approach. Responses to the Technology Acceptance Model survey were analyzed.ResultsA total of 16 participants were interviewed, including WCM users (n=8) and department leadership members (n=8). In total, 3 interdisciplinary team meetings were observed, and 8 WCM users were surveyed. WCM provided a central shared platform where client-related, up-to-date, comprehensive, and reliable information from participating agencies was consolidated. Factors that facilitated WCM use were users’ enthusiasm regarding the tool functionalities, scalability, and agency collaboration. Constraining factors included the suboptimal awareness of care delivery goals and functionality of the system among the community, sensitivities about data sharing and legal requirements, and constrained funding from government and nongovernment organizations. Overall, users found WCM to be a useful tool that was easy to use and helped to enhance performance.ConclusionsWCM supports the delivery of care to individuals with complex needs. Integration of data and information in a CMCS can facilitate coordinated care. Future research should examine WCM and similar CMCSs in diverse populations and settings.

GRemote: Cloud rendering on GPU resource pool based on API-forwarding

Traditional GPU resource allocation approaches, widely adopted in today’s data centers as the rise of cloud gaming, only focus on server-side functions while ignoring the client-side, which wastes hardware resources. To solve this problem, cloud-edge integrated architectures are put forward, leaving some workloads to the client-side. However, many cloud-edge integrated frameworks suffer from one big issue: shared-resource interference, stemming from two reasons: (a) GPU resource racing caused by resources overuse for single client, and (b) CPU resource racing caused by resources shortage among clients. This paper presents gRemote, an open-source cloud-rendering system that can address these issues on a GPU resource pool. To mitigate the CPU resource shortage, gRemote improves CPU configuration by expanding CPU resources from server-side to both server- and client-side. To maintain the reasonable GPU usage for individual tasks, gRemote innovates a new resource-sharing mechanism called GPU throttle. Furthermore, remote API-Forwarding brings another type of network bandwidth consumption: command streaming. To optimize the network bandwidth for GPU command transmission, gRemote proposes two methods, command characteristics-oriented (CCO) compression algorithm and command-transmitted methodology. gRemote supports 1,228 OpenGL commands and provides cloud rendering for more than 40 clients with negligible shared-resource interference. With CCO algorithm and command-transmitted methodology, the network bandwidth is saved by more than 90%.

Stacked-Plate Framing

Stacked-Plate Framing takes a projective stance on conventional American construction. By challenging the exclusionary lens of the timeworn axiom “Cheap, Fast, or Good,” a pragmatic and optimistic approach to vernacular building emerges. Stacked-Plate Framing uses off-the-shelf materials and deploys unskilled labor to elaborate an expedient, novel, and simple architectural response to two structures commissioned by a single client. By exercising a reductive approach to fabrication, Stacked-Plate Framing demonstrates a means to achieve work that can leverage the everyday and readily available to generate an economical and sustainable new construction typology.

The perceptions of loan officers and auditors of factors affecting auditor independence: Evidence from Palestine

The study investigates the perceptions of external auditors and loan officers regarding external auditor's independence in Palestine. Data were gathered using a questionnaire developed by the author and include 5 main issues related to the perception of external auditor’s independence. The sampling population identified for this study consists of external auditors working in domestic and international audit firms and financial statement users mainly loan officers in Palestine. The sample included 79 auditors and 76 loan officers. The findings revealed that there are significant differences in the perceptions of external auditors and loan officers in relation to provision of non-audit services, auditor’s economic dependence on a single audit client, and long relationship between an auditor and a client. The results revealed mixed results about the effect of presence of active audit committee on independence of the external auditors. Furthermore, acceptance of significant gifts from the client was considered an important factor that may influence auditor independence by loan officers and external auditor and thus significant differences between the two respondent groups were found in relation to acceptance of significant gifts from the client. These findings can be useful to policy makers and professional auditing bodies in Palestine on setting new regulations or strengthening existing ones to enforce auditor’s independence in Palestine.

Юнит-экономика в секторе молодежного предпринимательства: принципы, методы реализации

Basic problem: the Republic of Kazakhstan is a platform for implementing innovative projects in all spheres of the economy, providing the younger generation with resource centers, technological parks, agricultural equipment, industrial technologies and scientific and educational complexes. The main goal of such actions is to activate scientific research, increase the technological potential of the industrial sectors of the national economy, and stimulate the development of innovative activities in the field of research and development. The problems of developing an entrepreneurial culture are a cornerstone issue that combines a combination of motivational principles for generating and promoting ideas, activating youth entrepreneurship as the flagship of the future economy, and a complex epidemiological situation in the world that hinders not only the development of entrepreneurship, but also the course of all socio-economic processes in society. Purpose: The purpose of this study is to identify the problems of youth entrepreneurship and find ways to solve them in accordance with the principles and methods of implementation, including the unit economics. Methods: the research Area focuses on economic modeling techniques that are successfully used in international practice to determine the profitability of business models, taking into account the effect of the production of a unit of goods / services or a single client / customer. The implementation of this approach is facilitated by the use of traditional methods of scientific research, such as analysis, comparison, and a graphical method for visualizing the results obtained; quantification method and parametric method as an evaluation tool that allows formalizing the procedure for evaluating the performance of unit economics models. Results and their significance: when considering business models in relation to youth entrepreneurship, attention is paid to the skills and competencies that students who study the disciplines of the entrepreneurial block in higher education receive. The proposed methods of unit economics are actively used in the development and promotion of startups, as an integral part of business plans. It is concluded that youth business has started to play a crucial role in solving socio-economic problems, such as creating new jobs and reducing the unemployment rate, and training qualified personnel. The set of proposed measures provides additional opportunities and increases the influence of youth entrepreneurship, which becomes the basis for unlocking its potential.

FL-QSAR: a federated learning-based QSAR prototype for collaborative drug discovery.

Quantitative structure-activity relationship (QSAR) analysis is commonly used in drug discovery. Collaborations among pharmaceutical institutions can lead to a better performance in QSAR prediction, however, intellectual property and related financial interests remain substantially hindering inter-institutional collaborations in QSAR modeling for drug discovery. For the first time, we verified the feasibility of applying the horizontal federated learning (HFL), which is a recently developed collaborative and privacy-preserving learning framework to perform QSAR analysis. A prototype platform of federated-learning-based QSAR modeling for collaborative drug discovery, i.e. FL-QSAR, is presented accordingly. We first compared the HFL framework with a classic privacy-preserving computation framework, i.e. secure multiparty computation to indicate its difference from various perspective. Then we compared FL-QSAR with the public collaboration in terms of QSAR modeling. Our extensive experiments demonstrated that (i) collaboration by FL-QSAR outperforms a single client using only its private data, and (ii) collaboration by FL-QSAR achieves almost the same performance as that of collaboration via cleartext learning algorithms using all shared information. Taking together, our results indicate that FL-QSAR under the HFL framework provides an efficient solution to break the barriers between pharmaceutical institutions in QSAR modeling, therefore promote the development of collaborative and privacy-preserving drug discovery with extendable ability to other privacy-related biomedical areas. The source codes of FL-QSAR are available on the GitHub: https://github.com/bm2-lab/FL-QSAR. Supplementary data are available at Bioinformatics online.

Multiple cleaner species provide simultaneous services to coral reef fish clients.

Cleaning symbioses on tropical coral reefs are typically documented between two species: a single client fish and one or more conspecific cleaners. However, multiple cleaner species living sympatrically in the Caribbean have been anecdotally reported to simultaneously clean the same client. Nothing is known about the patterns and processes driving these interactions, which may differ from those involving a single cleaner species. Here, we used remote underwater videography on three reefs in Honduras to record simultaneous cleaning interactions involving Pederson's cleaner shrimp (Ancylomenes pedersoni) and cleaner gobies (Elacatinus spp.). A pilot study on adjacent shrimp and goby stations found interactions were always initiated by shrimp. A larger, multi-year dataset shows cleaner gobies joined 28% of all interactions initiated at A. pedersoni cleaning stations with cleaner gobies residing nearby. Client body size significantly predicted simultaneous cleaning interactions, with 45% of interactions simultaneous for clients greater than 20 cm total body length compared with only 8% for clients less than 20 cm. We also found that simultaneous cleaning interactions lasted over twice as long as shrimp-only interactions. We propose these novel multi-species interactions to be an ideal model system to explore broader questions about coexistence, niche overlap and functional redundancy among sympatric cleaner species.