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Blockchain-based multi-layered federated extreme learning networks in connected vehicles
Get PDFIntelligent and networked vehicles help build an efficient
vehicular network’s infrastructure. The widespread use of
electronic software exposes these networks to cyber-attacks.
Intrusion detection systems (IDS) are useful for preventing
vehicle network assaults. IDS have been customized using
machine and deep learning networks for greater real-time
performance. Current learning-based intrusion detection
systems demand substantial processing capabilities to train
and update intricate training models in vehicular devices, resulting in decreased efficiency and ability to defend against
assaults. This study presents Blockchain-based Multi-Layer
Federated Extreme Learning Machines (MLFEM) enabled
IDS (BEF-IDS) for safe data transfers. The proposed IDS
leverages federated learning to generate Multi-Layered Extreme Learning Machines, which are offloaded to dispersed
vehicular edge devices such as Road-Side Units (RSU) and
connected vehicles. This federated strategy decreases resource use without sacrificing security. Blockchain technology records and shares training models, assuring network security. Using real-time data sets, the suggested algorithm’s performance under different attack scenarios were
extensively tested. The suggested method obtained 98 %
accuracy and Recall, 97.9% Precision, and 97.9% F1 Score
performance, which suggests it’s incredibly secure and costs very little to transmit
E-commerce website usability analysis using the association rule mining and machine learning algorithm
Get PDFThe overall effectiveness of a website as an e-commerce platform is influenced by how usable it is. This study aimed to find out if advanced web metrics, derived from Google Analytics software, could be used to evaluate the overall usability of e-commerce sites and identify potential usability issues. It is simple to gather web indicators, but processing and interpretation take time. This data is produced through several digital channels, including mobile. Big data has proven to be very helpful in a variety of online platforms, including social networking and e-commerce websites, etc. The sheer amount of data that needs to be processed and assessed to be useful is one of the main issues with e-commerce today as a result of the digital revolution. Additionally, on social media a crucial growth strategy for e-commerce is the usage of BDA capabilities as a guideline to boost sales and draw clients for suppliers. In this paper, we have used the KMP algorithm-based multivariate pruning method for web-based web index searching and different web analytics algorithm with machine learning classifiers to achieve patterns from transactional data gathered from e-commerce websites. Moreover, through the use of log-based transactional data, the research presented in this paper suggests a new machine learning-based evaluation method for evaluating the usability of e-commerce websites. To identify the underlying relationship between the overall usability of the eLearning system and its predictor factors, three machine learning techniques and multiple linear regressions are used to create prediction models. This strategy will lead the e-commerce industry to an economically profitable stage. This capability can assist a vendor in keeping track of customers and items they have viewed, as well as categorizing how customers use their e-commerce emporium so the vendor can cater to their specific needs. It has been proposed that machine learning models, by offering trustworthy prognoses, can aid in excellent usability. Such models might be incorporated into an online prognostic calculator or tool to help with treatment selection and possibly increase visibility. However, none of these models have been recommended for use in reusability because of concerns about the deployment of machine learning in e-commerce and technical issues. One problem with machine learning science that needs to be solved is explainability. For instance, let us say B is 10 and all the people in our population are even. The hash function’s behavior is not random since only buckets 0, 2, 4, 6, and 8 can be the value of h(x). However, if B = 11, we would find that 1/11th of the even integers is transmitted to each of the 11 buckets. The hash function would work well in this situation
To Hellingly and back: two autoethnographic accounts of life in a mental hospital
Get PDFThis article discusses life in one asylum, Hellingly, near Eastbourne in Sussex. Where
once the majority of mental health professionals worked in asylums, their gradual run
down and closure saw most staff, as well as patients, transfer into new community
services. The two main protagonists in this paper both found themselves at Hellingly
Hospital in the 1970s. One was a charge nurse who ran the therapeutic community ward
in the hospital. The other was an inmate, who was to begin his alternative mental health
career as a ‘revolving door’ patient. Both start by giving their respective memories of
the hospital and its impact on their lives. They then reflect on what happened to them
after they left the hospital. Now both in their 70s, they have each achieved a sense of
contentment with their respective careers in mental health, but via completely different
routes. The lessons we can learn from both accounts are drawn out in the discussion
section. The fact that the accounts feature a professional and a patient show how far
mental health nursing has come over the ensuing 50 years. Patients are partners, and
lived experience narratives are indispensable to understand the phenomenology of
mental health problems
Tensions in managing the online network development of autoethnographers
Get PDFAlthough literature exists on the methodological development of autoethnographers in the classroom context, little has been written about achieving such development in online networks of dispersed individuals, and the social psychological difficulties between senior members of such networks that might ensue. This conversational autoethnography developed after Alec Grant, the first author, angrily withdrew by email from the South Coast Autoethnography Network (SCAN). Since its inception in 2013, the hub, or centre of operating activity of SCAN has historically been mostly shared between a small number of academics working in, or associated with, Sussex University and the University of Brighton in the south coast of England. With around 65 participants, SCAN aims to facilitate the development of autoethnographers, with many of its members inexperienced in the approach to differing degrees. In their conversational exchange, the authors explore, respond to, and try to make sense of and resolve, the tensions that developed in the group before and after Alec’s withdrawal from it. The authors believe that this article captures many of the interpersonal difficulties that might inevitably arise between senior members, in autoethnographic networks internationally. They therefore hope that it will serve as a useful resource for individual readers and network groups
Critical commentary. Understanding the effects of subtle abuse in intimate relationships: contributions to counselling psychology.
Get PDFThe research area of this study examines the impact of the authors’ contribution to
the field of counselling psychology, specifically in the area of psychological abuse.
Despite its overwhelming prevalence worldwide, psychological abuse has largely
been a neglected area of study, with little understanding surrounding the complexities and mechanisms behind emotionally abusive dynamics. Psychological violence
is estimated to be the most prevalent form of intimate partner violence (IPV) and yet,
there is very little research on the individual impact of psychological abuse on mental health (Dokkedhal et al., 2019). Most victims of psychological abuse often do not
know that they are experiencing abuse, even though there is a strong link between
psychological abuse alone and a range of mental health disorders and physical conditions.
In an effort to address this significant gap in knowledge, the author has written the
book, “If He’s So Great, Why Do I Feel So Bad? Recognizing and Overcoming Subtle Abuse”, which has been translated and published in twelve languages. Primary objectives of the book include:
- Helping women to accurately identify the more covert forms of
psychological abuse.
- Learning personality traits of an abuser and of victims of abuse.
- Characteristics of abusive relationships that are often overlooked.
- How to recover from an abusive relationship.
Additionally, the author has written courses that have been taken by nearly 17,000
students, as well as helping clients through clinical practice. The author’s mission is
to change the field of counselling psychology to accurately identify psychological
abuse and effective intervention strategies, rather than continuing to neglect this
subject and in doing so, reinforcing the problem and causing further traumatization.
In this retrospective analysis, a selective review of the literature on psychological
abuse will examine the effects of psychological abuse on physical and mental
health, why research is lacking, the effects of subtle psychological abuse, and how
to best support patients in clinical practice. This critical commentary will also
demonstrate how the author’s professional practice in counselling psychology has
led to enhanced understanding of the effects of subtle abuse in intimate relationships, subsequently resulting in the book and courses. A final critical reflection highlights the methods used to investigate evidence of this, including the Hayes (1995)
model of countertransference, which serves as a reflective practice to review and
evaluate the validity of the efforts and to explore biases. This work is supported by a
portfolio of evidence, which contains additional work by the author
A secure authentication scheme for industrial IoT network
Get PDFIn recent years, the technological development of Internet of Things
(IoT) has facilitated many practical applications, e.g., smart city and smart
home, industry. The incredible revolution of smart Industry-IoT (IIoT) offers
productive and practical real time monitoring systems. Smart Industry 4.0
is one of the most efficient ways to improve, manage and observe smart machines through the various devices. However, the data generated from these
IoT-based machines are very important, so additional security protection is
required to protect the data from attackers. This paper focuses on designing
a New Lightweight Session Key-based Authentication (LSKA) scheme that
ensures data privacy and secure communication. The proposed LSKA scheme
uses three-factor authentication composed of password, smart-card, and the
biometric identity to preserve patient anonymity in the Industrial IOT (IIoT)
system. This scheme is mathematically proved with Real or Random (ROR)
model and also simulated on the Automated Validation of Internet Security
Protocols and Applications (AVISPA) tool to determine its safety and security
A Novel computer assisted genomic test method to detect breast cancer in reduced cost and time using ensemble technique
Get PDFBreast cancer is the leading cause of death among women around the world. It is a primary malignancy
for which genetic markers have revealed the ability for clinical decision making. It is a genetic disease
that generates due to gene mutations, but the cost of a genetic test is relatively high for a number of
patients in developing nations like India. The results of a genetic test can take a few weeks to determine
cancer. This time duration influences the prognosis of genes since certain patients suffer from a high rate
of malignant cell proliferation. Therefore, a computer-assisted genetic test method (CAGT) is proposed
to detect breast cancer. This test method will predict the gene expressions and convert these expressions
in the state of mutation (under-expression (-1), transition (0) overexpression (1)) and afterwards perform
the classification to get the benign and malignant class in reduced time and cost. In the research work,
machine learning techniques are applied to identify the most responsive genes of breast cancer on the
premises of the clinical report of a patient and generated a CAGT. In the research work, the hard voting
ensemble approach is applied to detect breast cancer on the basis of most responsive genes by CAGT
which leads to improving 3.5% accuracy in cancer classification
Comorbidities of combat trauma: unresolved grief and moral injury
Get PDFThis Grounded Theory study explored the effects of complicated grief and moral injury on veterans’ recovery from postcombat trauma. The main finding was that the interaction
between the comorbidities seems to be two-fold: the cumulative anger arising from military life and combat experiences
has a major impact on recovery from any or all of the co-morbidities irrespective of its source; and avoidance of the distressing emotions associated with any one of conditions leads
to veterans avoiding talking about any of them, with obvious
detriment to recovery. These conclusions merit further study
to inform mental health policy and optimize offered therap
Reductive mechanisms for unwanted intrusive thoughts: Exploring affectivity in clinical and non-clinical samples
Get PDFUnwanted intrusive thoughts are a major public health concern (Nock et al., 2008; Bentum et al., 2017), and they are key to the development of a variety of dysregulated behaviours (Jungmann et al., 2016; Bergen et al., 2012). Thus, this study investigates reductive mechanisms for unwanted intrusive thoughts by analysing aspects of affectivity in clinical and non-clinical samples.
Quantitative means of data collection and analysis were used to explore UITs and affectivity. 530 adults took part in this study (236 males, 253 females, and 15 transgenders). Participants consisted of clinical (N=168) and non-clinical samples (N=336) who completed the MIDUS Sense of Control Scale (Lachman and Weaver, 1998), 20-Item Neuroticism Scale (Goldberg, 1999), Self-Compassion Scale (Neff, 2003a), Flourishing Scale (Diener et al., 2009), PANAS-N Scale (Watson et al., 1988), Generalized Anxiety Disorder 7-item (Spitzer et al., 2006), and Repetitive Thinking Questionnaire-10 (McEvoy et al., 2010).
Participants who experienced high levels of psychological flourishing, emotional stability, self-compassion, perceived control, and affective wellbeing were prone to experience minimal UITs. Anxiety was positively related to UITs. These findings suggest that these aspects of affectivity may aid the reduction or management of clinical and non-clinical unwanted intrusive thoughts.
This study has addressed gaps in knowledge and the literature on UITs by demonstrating that psychological flourishing, emotional stability, self-compassion, perceived control, and affective wellbeing as aspects of affectivity can be implemented as a reductive mechanism for UITs, and such implementation may have a high probability of effective reduction or management of clinical and non-clinical unwanted intrusive thoughts
Are changes in vital signs, mobility, and mental status while in hospital measures of the quality of care?
No full textIntroduction Little is known of the changes in patients' health condition while in hospital in low-resource settings. The aim of this exploratory study is to examine dependency of patients on hospital admission and discharge in a low-resource sub-Saharan hospital.
Methods We carried out a retrospective observational study of changes in the health condition, as reflected by their mental status, mobility and vital signs, of 5,888 consecutive patients between hospital admission and discharge.
Results Mental status, mobility and vital signs were normal in 25% of patients on hospital admission and 30% of patients at discharge. Although very few patients with normal mental status, mobility and vital signs on admission died in hospital, the condition of 40% of them deteriorated.
Conclusion No comparative data on changes in health condition between hospital admission and discharge have been published. Our proposed health condition categories identify changes that may matter most to patients and should be considered as a standard metric of hospital care