Client Learning Research Articles

Distributed Learning Mechanisms for Anomaly Detection in Privacy-Aware Energy Grid Management Systems

Smart grids have become an emerging topic due to net-zero emissions and the rapid development of artificial intelligence (AI) technology focused on achieving targeted energy distribution and maintaining operating reserves. In order to prevent cyber-physical attacks, issues related to the security and privacy of grid systems are receiving much attention from researchers. In this paper, privacy-aware energy grid management systems with anomaly detection networks and distributed learning mechanisms are proposed. The anomaly detection network consists of a server and a client learning network, which collaboratively learn patterns without sharing data, and periodically train and exchange knowledge. We also develop learning mechanisms with federated, distributed, and split learning to improve privacy and use Q-learning for decision-making to facilitate interpretability. To demonstrate the effectiveness and robustness of the proposed schemes, extensive simulations are conducted in different energy grid environments with different target distributions, ORRs, and attack scenarios. The experimental results show that the proposed schemes not only improve management performance but also enhance privacy and security levels. We also compare the management performance and privacy level of the different learning machines and provide usage recommendations.

Federated Noisy Client Learning.

Federated learning (FL) collaboratively trains a shared global model depending on multiple local clients, while keeping the training data decentralized to preserve data privacy. However, standard FL methods ignore the noisy client issue, which may harm the overall performance of the shared model. We first investigate the critical issue caused by noisy clients in FL and quantify the negative impact of the noisy clients in terms of the representations learned by different layers. We have the following two key observations: 1) the noisy clients can severely impact the convergence and performance of the global model in FL and 2) the noisy clients can induce greater bias in the deeper layers than the former layers of the global model. Based on the above observations, we propose federated noisy client learning (Fed-NCL), a framework that conducts robust FL with noisy clients. Specifically, Fed-NCL first identifies the noisy clients through well estimating the data quality and model divergence. Then robust layerwise aggregation is proposed to adaptively aggregate the local models of each client to deal with the data heterogeneity caused by the noisy clients. We further perform label correction on the noisy clients to improve the generalization of the global model. Experimental results on various datasets demonstrate that our algorithm boosts the performances of different state-of-the-art systems with noisy clients. Our code is available at https://github.com/TKH666/Fed-NCL.

Impact of federated deep learning on vehicle-based speed control in mixed traffic flows

This study investigates the application of Federated Learning (FL) in an environment of mixed traffic flow with Connected and Automated Vehicles (CAVs). The focus of this study is set on the CAV cruise control speed adjustment which is enforced by the Intelligent Speed Adaptation (ISA) system. It is modelled as an Actor-Critic-based learning architecture with the goal of computing the vehicle speed based on the data of the nearby vehicles. Some CAVs achieve poor travel time performance in comparison to others. Thus, the proposed FL framework selects periodically best-performing CAVs which are local clients in the context of FL. The updated global model is computed based on the weighted averaging of the best-performing models of clients. The use case environment is modelled as a simulation of a synthetic motorway with an induced capacity drop in the form of a work-zone under moderate and high traffic demand. It is shown that the FL framework can stabilise the individual client learning convergence and reduce their travel time compared to the local learning approach. The overall motorway throughput is also increased by the proposed FL framework. This indicates that the global model of FL can utilise the optimal ratio between generalisation and bias towards the most effective control policy of individual speed control. Results show that those effects are more prominent under moderate traffic demand.

Manipulating vulnerability: Poisoning attacks and countermeasures in federated cloud–edge–client​ learning for image classification

The cloud–edge–client hierarchical computing architecture takes into account the dual advantages of cloud and edge computing. However, in realistic scenarios, the explosive increase of distributed data promotes the widespread application of the cloud–edge–client architecture, but also brings a variety of security threats. Relying on the advantages of federated learning technology, this has led to a growing interest in federated learning as the intersection of machine learning and cloud–edge–client fields. However, recent studies found that federated learning is potentially vulnerable to data poisoning attacks. Existing explorations of federated learning poisoning attacks and defense techniques in the cloud–edge–client environment are largely attack capabilities-specific and privacy protection-based: they are designed but fail to consider the characteristics of federated learning vulnerability and the difference in attack intensity, and lack flexibility. Yet few different attack capabilities and general defense strategies have been developed. To address these concerns, we introduce federated cloud–edge–client learning collaborative framework. Based on this architecture, a client-launched multi-label flipping attack method is discussed, which exhibits different attack capabilities. Further, we propose SPAD, a Server-based Parameter Adaptive Defense method in response to different attack intensities, to identify malicious attackers and benign participants, thereby improving the security of the federated learning image classification task. The results on image classification tasks demonstrate that in cloud–edge–client scenario, the multi-label flipping attack method presents different degrees of poisoning effect, and SPAD method has strong feasibility and effectiveness against poisoning attacks, which verify the significant advantages of the proposed method.

Federation based joint client and server side Machine Learning for 5G and beyond Wireless Channel Estimation

In this paper, we propose a Machine Learning (ML) based approach to address Wireless Channel Estimation (WCE) problem for 5G and beyond wireless networks. Accurate wireless channel estimation plays a crucial role for provision of high quality of service to billions of wireless devices in current and future wireless networks. Our proposed approach uses contemporary ML technique, Federated Learning (FL), in conjunction with the Stochastic Gradient Descent (SGD) algorithm to optimise the WCE problem. Our proposed approach leverages the local user wireless channel information to locally optimise the objective at users and then uses this locally optimised information at the server to optimise the global objective function. The proposed approach is referred to as joint Federated Server Learning and Federated Client Learning (j-FSL-FCL) in the paper. We formulate the WCE problem with a novel loss function to be used for the optimisation problem. To evaluate the performance of our proposed j-FSL-FCL approach (with and without SGD), we consider a Down Link (DL) wireless channel model with Multiple-Input Multiple-Output (MIMO) setting that mimic closely to the wireless channel for 5G and beyond wireless channel models. The performance measuring parameters for j-FSL-FCL are to minimise the difference between actual and estimated wireless channel parameters (channel strength and direction). We compare the results of our proposed approach with the other techniques in the literature based on Least Squares (LS), Linear Regression (LR) and Mean Square Error (MSE). It is shown that the proposed algorithm converges to the optimal solution quickly when used with SGD compared to other existing techniques. It is also shown that the efficiency of the proposed approach for WCE problem is much higher compared to other LS and MSE based techniques. Finally, we present some interesting futuristic applications of FL in the context of 5G and beyond wireless networks.

Strategies for graded motor imagery for clients with phantom limb pain and cognitive impairment.

Individuals with amputations often experience phantom limb pain (PLP) that can limit their participation in rehabilitation, prosthesis training, desired activities, and roles. One nonpharmacological rehabilitation intervention for PLP is graded motor imagery (GMI). There are several components to GMI, including right/left discrimination or laterality, motor imagery, sensory retraining, and mirror therapy. Successful implementation of GMI requires a range of cognitive skills, such as attention span, working memory, abstract reasoning, and planning. For individuals with PLP who concurrently display cognitive impairments, GMI protocols can be adapted using strategies derived from clinical practice. The purpose of this technical clinical report was to discuss the application of clinically implemented cognitive compensation techniques to GMI instruction. Not applicable. Clinical expert opinion to explore adaptations for GMI. Graded motor imagery can be an effective tool for pain treatment; however, some clients may need greater clinician support due to existing cognitive difficulties. For clients to be successful, active engagement in learning about and implementing GMI techniques is necessary. When serving the lifetime amputation care needs of patients with cognitive deficits, we find that targeted learning strategies and accommodations can be helpful when introducing GMI concepts and skill development. Enhanced patient education techniques support client learning.

Introducing Acceptance and Commitment Therapy into the Bonny Method of Guided Imagery and Music

The Bonny method guided imagery and music (GIM) is a depth approach to therapy that uses music to support letting go of cognitive control to explore different levels of consciousness. Acceptance and commitment therapy (ACT) is a third-wave behavior therapy focusing on using mindfulness, acceptance, and spirituality to support clients in increasing psychological flexibility. While on the surface the two approaches may appear very different, when used in conjunction, they can synergistically work together to amplify the other’s effects. This paper provides background information on both modalities as well as a case study illustrating how ACT was used to guide the GIM process of a male client learning how to let go of control.

Developing the Foundations for a Learning-Based Humanistic Therapy

This study addressed the possibility of integrating learning theory into humanistic counseling. We consider that such an approach may enable client self-counseling either between sessions or after therapy has finished. Carl Rogers was a keen advocate of person-centered learning facilitation in the classroom and his principles of learning provide a natural start-point for a humanistic therapy based on learning theory. A variety of other learning processes also lend themselves to a learning based therapy such as establishing client learning goals based on self-efficacy, enabling the client to understand their own learning processes and blocks to learning, encouraging the client to access their own learning resources, and then enabling long-term learning. A case study was therefore designed to test some of these processes in a therapeutic setting. A White, British, middle-aged female was recruited for the case study. During the course of six sessions, the content of which was analyzed using thematic analysis, a selection of learning processes were applied to the humanistic therapeutic process. In summary, it was established that facilitated learning processes could provide a practically acceptable basis for humanistic counseling, and these processes are offered here as the foundation to a model of “therapeutic learning.”

Marketing research: Innovation, experiential learning, and student engagement

The following article outlines the importance of classroom engagement through use of innovative group projects within a marketing research class. Project findings address learning engagement, student loyalty, and enhanced learning using an experiential learning based project designed to help students produce a marketing research project. The learning by design project details the course structure, segmented project sections, learning goals, and approach used to ensure student engagement with professor, client, and active learning within the course project. Study implications focus on student success and methods to address engagement factors.

Governance and learning in global, regional, and local value chains: The IT enabled services industry in South Africa

Abstract Global value chain (GVC) participation is generally seen as an important avenue for developing countries to access new markets and diversify exports, to add value to local industries and to increase employment. For developing country firms it provides opportunities to access knowledge to enhance learning and capability building. However, many firms in developing countries do not directly integrate into GVCs but rather into regional value chains (RVCs) or local value chains (LVCs), as these have become increasingly important due to the emergence of “Southern”-end markets and increased South-South trade. In this paper we examine and compare the role of involvement in these different types of value chains in stimulating supplier learning in the context of the IT-enabled service (ITES) industry. We distinguish between different types of learning and argue that learning outcomes depend crucially on value chain governance: the power balance and interactions between the lead firms and suppliers. We draw on a survey among the population of ITES providers in South Africa. These novel firm level data allow for a study of learning mechanisms in value chains at the firm level, going beyond prior studies of aggregate level relationships. In a multivariate analysis, we find that service providers in GVCs learn via interactions with their client firms. Yet, GVC participation is not the only avenue for client learning and capability building; we similarly observe learning in LVCs and RVCs. Learning is generally and strongly enhanced by trust-based governance of the client-supplier relationship, while in GVCs, control-based governance additionally promotes learning specifically in the IT domain. These findings provide a better understanding of how firms in developing countries can build capabilities in local, regional and global value chains of services, a topic that has gained interest among development practitioners.

Career counselling with life design in a collectivist cultural context: An action research study

Large-scale macro forces are restructuring forms of work in urban India creating the need for alternative methods of career counselling. This research explores the application of a US-based approach to constructing careers i.e. Life-Design Career Counseling (i. e., LDC) with two mid-career professionals in India. Data consisted of client responses to different narrative career counselling exercises such as a lifeline activity, a career construction interview and semi-structured feedback interviews. Action research's focus on reflexivity helped integrate theory with practice to contribute to knowledge production and meaningful innovations within practice. Findings from this research underscored the importance of relationship, reflection and sense-making and the need for India to utilise a culturally resonant career intervention. The study holds value for career professionals, in India and beyond where LDC is still unexplored. Moreover, LDC practitioners in non-Western countries and collectivist societies will benefit from a contextual adaptation that encourages focus on client learning.

Improved fuzzy weighted‐iterative association rule based ontology postprocessing in data mining for query recommendation applications

AbstractThe usage of association rules is playing a vital role in the field of knowledge data discovery. Numerous rules have to be processed and plot based on the ranges on the schema. The step in this process depends on the user's queries. Previously, several projects have been proposed to reduce work and improve filtration processes. However, they have some limitations in preprocessing time and filtration rate. In this article, an improved fuzzy weighted‐iterative concept is introduced to overcome the limitation based on the user request and visualization of discovering rules. The initial step includes the mix of client learning with posthandling to use the semantics. The above advance was trailed by surrounding rule schemas to fulfill and anticipate unpredictable guidelines dependent on client desires. Preparing the above developments can be imagined by the use of yet another clever method of study. Standards on guidelines are recognized by the average learning professionals.

Rational emotive behavior therapy from a new perspective

The aim of this study is to give a different dimension to the Rational Emotional Behavioral Therapy (REBT) Approach. For this purpose, by using the induction method; Growth has been reached. By adding G to the ABCDEF process at the end of the study; a final dimension. Theory and applications of REBT relies on the A-B-C model. According to this model, A (Activating Event) is a phenomenon or the existence of an event or a person’s behavior. In other words, A is the activating event. According to the A-B-C model, C (emotive or behavioral consequence) is the individual’s emotive or behavioral reaction or consequence that follows it. A (the actual event) does not cause C. what plays the primary role in the formation of C is the persons belief about A, and that is B. A-B and C comes D (disputing). D is the questioning of irrational and dysfunctional beliefs. Although REBT makes use of some other cognitive, emotive, and behavioral components in order to help reduce irrational beliefs of clients to a minimum, it emphasizes this disputing process (D) both during therapy and in daily life. Clients eventually reach E, namely, effective behavior or life philosophy, which has a practical side. E (effects) provides the effects of cognitively re-thinking in a more rational behavior mode. In an interview conducted with Ellis in 2005, Ellis suggested F which forces people to obey new rational beliefs in order to strengthen E, which has an influence on dispute. It can be said that F is basically Functional Feeling and Behavior which ensures the continuity of rational beliefs that come out as a result of E (effect) and which makes it easier to evaluate events within their own reality by following these rational beliefs. When REBT is considered with a new perspective, G (growth) can be added to the process after F (functional feeling and behavior), because it takes some time for the rational beliefs formed with the influence of F to set in for the individual. In a psychological counseling which applies a rational emotive behavior approach, the aim is to break this negative spiral. Irrational beliefs (B) of the individual are refuted by disputing them (D). In the new case which came about with the effect (E) of this dispute, functional emotions and behaviors (F) occur. One of the aims in REBT-based psychological counseling is for the client to realize his or her irrational beliefs, distinguish them from rational ones, and to learn to overcome irrational beliefs. The client learning this process and using rational beliefs in the face of new events can be called growth (G). In this respect, the main aim of REBT-based psychological counseling can be said to be enabling growth.

Exploring the delayed effects of leadership coaching: a pilot study

ABSTRACTLittle empirical attention has been directed towards learning as an aspect of the coaching process. Given its deeply reflective nature, it seems likely that learning is not always immediately secured psychologically by clients or successfully translated into behaviour. However, delayed effects have yet to be explicitly studied in coaching outcome research. To examine this, a pilot study was conducted to investigate the prevalence and progression of such effects following participation in a 10-week leadership coaching programme. Semi-structured interviews were conducted with 15 leaders to obtain personal narratives of their coaching experience and narrative enquiry applied to analyse the underlying phenomena. The data confirmed that coaching was immediately beneficial in a variety of ways (e.g. improved communication style), whilst also indicating that some client learning required a period of incubation, or a triggering event(s), before it became manifested in behaviour. Whilst delayed effects were not reported by all participants, initial evidence now exists to show that coachees can require time to clarify, consolidate and enact personal learning facilitated during coaching. In interpreting these results, theories of transformational learning are discussed, along with a modelling of factors that might influence the emergence of delayed effects. Recommendations for future research are also provided.

Facilitating Informed Decision-Making in Financial Service Encounters

While advice-giving encounters form an integral part of banks’ services, clients often buy inappropriate products and face financial consequences. Legislators have started to put banks under pressure to ensure that clients are properly educated. However, the literature describes barriers due to which client education is doomed to fail applying current advice-giving practices. Practicable alternatives to the predominant perfect agent style of advice-giving are dismissed, mainly with the argument of client-side cognitive limitations. This paper challenges this assumption by suggesting a decision-making process that seamlessly integrates educational interventions, thus supporting informed client decision-making. In the spirit of design science research, the authors take a fresh look at the problems of client education in cooperation with a large Swiss retail bank to derive generalizable requirements, and design a novel IT-supported advice-giving process. An evaluation demonstrates the design’s utility in significantly improving client learning, compared to traditional service encounters. This research extends the current discourse on service encounter design, and seeks to help practitioners to design the financial service encounters of tomorrow.

THE EFFECTS OF THE FIRMS STRATEGIC MARKETING ORIENTATION ON VALUE COCREATION AND RELATIONSHIP PERFORMANCE

The advanced information technology leads to network age, making existing competitive advantages such as differentiation and cost leadership powerless in B2B context. The competitiveness of individual firm plays a significant role in enhancing the competitive advantage of a business network that a firm belongs to. The competitiveness of a business network depends on value co-creation, the interaction among firms in a network. Value co-creation has desirable and risky aspects. The increases in profits, brand reputation, and time and cost efficiency, client and supplier learning, etc. are positive aspects. But role conflicts, role ambiguity, and tension, etc. are negative outcomes.How can the industrial firm succeed in value co-creation with its partners in B2B context? The study focuses on the firm’s strategic marketing orientations as an antecedent of value co-creation. Strategic marketing orientations as the values and beliefs of the firm affect the collaboration with other firms during value co-creation. Previous literature assumes that a firm pursues one single strategic orientation.However, the study assumes that an industrial firm has entrepreneurial orientation, market orientation, long-term orientation, and relationship orientation. The study mostly focused on the relationships among those strategic marketing orientations. Based on these inter-relationships, the study proposed a set of value co-creation activity criteria such as information seeking, information sharing, personal interaction, responsible behavior, feedback, helping, advocacy, tolerance. Value co-creation has been evaluated by relationship performance such as trust and commitment.The study examined the relationships between strategic marketing orientations and value co-creation. Data was collected from 159 Korean manufacturers in B2B context and analyzed through structural equation modeling.The study provides evidence that entrepreneurial orientation affects market orientation positively and market orientation has positive effects on long-term orientation and relationship orientation, and long-term orientation and relationship orientation influence value co-creation directly. Value co-creation has a positive effect on relationship performance.The results of the study provide valuable implications to the mangers of industrial firms in B2B context. To succeed the value co-creation, the firm first has to look at the difference between strategic marketing orientations that the value co-creation partners pursue. In terms of selecting value co-creation partner, industrial firm with long-term orientation and relationship orientation will be more effective. Six activities of interactions during value co-creation play an important role in enhancing trust and commitment.The study contributes to the value co-creation literature by identifying strategic marketing orientations as independent variable influencing the value co-creation in B2B context. The study has several limitations that call for future research.

컨설턴트의 전문지식과 컨설팅 지식이전의 관계에 관한 경험적 연구 : FTA컨설팅을 중심으로

This study empirically examined which factors facilitate or disturb the learning and practical knowledge transfer in consulting and which factors have most powerful influence on the learning and transfer of consulting knowledge. Analysing 160 data collected from FTA origin managers in export companies, the study findings show the ambiguity(-), complexity(+), consulting competences(+), intervention design and delivery(+), self-efficacy(+) and government subsidies(+) significantly affected on Client's learning, while consultant's expertise(+), consulting involvement(+), transfer culture(+) significantly affected on consulting knowledge transfer, respectively. It showed that consulting competence and causal ambiguity have an greater influence on learning while consultant's expertise has a greater influence on consulting knowledge transfer, respectively. The findings implicate that consulting success depends on rather consultant's factors(consultant's expertise and consulting competence) than client's input factors. To succeed in consulting project, it is important that the consultants effectively develop and apply consulting methods & tools as shared interfaces between consultant and client.

Outpatient Clinic for Health Education: Contribution to Self-Management and Self-Care for People With Heart Failure.

To report the experience of an outpatient nursing education clinic caring for people with chronic heart failure. In this service, qualified "listening," recreational educational actions about the disease and its treatment are conducted, based on the interventions from the Nursing Interventions Classification (NIC), as well as the evaluation of self-care behaviors with the outcomes from the Nursing Outcomes Classification (NOC). This article describes the practice of health education activities and the use of NANDA-I-NIC-NOC in a nursing clinic. The outpatient clinic supports client learning about the treatment of disease and stimulates self-control of health behaviors. This experience report will guide nurses in the establishment of outpatient nursing education clinics for different populations of patients with chronic health conditions.

Client and Vendor Learning in Information Technology Outsourcing

This study investigates the factors influencing client and vendor learning and its downstream performance implications in Information Technology Outsourcing (ITO) projects. We propose client system development expertise and vendor project expertise, project’s strategic importance, and expectations of relationship continuity as the antecedents of client and vendor learning, and project success as its outcome. Furthermore, the moderation effects of the expectations of relationship continuity are examined on relationships of the antecedents with client and vendor learning. We test the hypotheses using data collected from 101 ITO project managers. The findings suggest overall positive impacts of the factors on client learning and vendor learning. As for the moderation effects of expectations of relationship continuity, strategic importance has a positive effect on client learning only whereas vendor project expertise has a positive effect on vendor learning only.

Homework in therapy: a case of it ain't what you do, it's the way that you do it?

AbstractIt is argued, illustrated by a case example, that homework quality and end of therapy outcomes can be positively affected when ideas of compassion and attention to individual frames of reference are considered. It is suggested that by exploring the affect experienced when completing tasks and being mindful of client learning (i.e. the zone of proximal development), engagement and emotional connection with homework increase.