The Relationship between Learning Styles and Students’ Identity Styles

The aim of this study was to investigate the relationship between learning styles and identity styles Students. The study consisted of all high school students and community solidarity (second period) in the 2014-2015 school year resident of the city of Sabzevar that 100 people were selected by multistage random cluster sampling. Kolb’s Learning Styles Inventory Tool questionnaire identity styles Bennion-Adams used the results showed that successful identity styles between style concrete experience, reflective observation, abstract conceptualization and active experimentation students have a significant relationship. Among the components of a successful style only concrete experience, reflective observation and active experimentation to predict and successful identity and disoriented style of abstract conceptualization learning style to predict. Also a significant relationship between the identities of the student field does not exist. Among the students, there is significant gender identity style making.

Cyberspace Security Using Adversarial Learning and Conformal Prediction

This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent, and tactical offensive threats. Conformal prediction is the principled and unified adaptive and learning framework used to design, develop, and deploy a multi-faceted?self-managing defensive shield to detect, disrupt, and deny intrusive attacks, hostile and malicious behavior, and subterfuge. Conformal prediction leverages apparent relationships between immunity and intrusion detection using non-conformity measures characteristic of affinity, a typicality, and surprise, to recognize patterns and messages as friend or foe and to respond to them accordingly. The solutions proffered throughout are built around active learning, meta-reasoning, randomness, distributed semantics and stratification, and most important and above all around adaptive Oracles. The motivation for using conformal prediction and its immediate off-spring, those of semi-supervised learning and transduction, comes from them first and foremost supporting discriminative and non-parametric methods characteristic of principled demarcation using cohorts and sensitivity analysis to hedge on the prediction outcomes including negative selection, on one side, and providing credibility and confidence indices that assist meta-reasoning and information fusion.

Semantic model and optimization of creative processes at mathematical knowledge formation

The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.

The Evil of ‘Reciting’

First of all it is necessary to point out that 'reciting' is the wrong term for what Chinese students are often asked to do when they are learning English. The correct terms are, 'learning by heart' or 'rote learning'. In this article the term 'rote learning' will be used.……

Chinese Students' Learning Styles & Strategies in the IELTS“Speaking& Writing”Preparation

The IELTS(International English Language Testing System)exam has enjoyed its popularity in China for over 30years;still the number of the Chinese candidates is increasing.Undoubtedly,the stability and the scientificity of this testing system are acknowledged internationally.When it comes to sitting for the IELTS exam,however,the Chinese students often find it very difficult to achieve a band 7 in speaking and writing.The question is,however,why is getting a band 7 such a painful journey for many Chinese IELTS candidates?This report will explore some of the underlying causes and propose possible solutions.Most importantly,the author will share some of his own teaching experience in the preparation of speaking and writing sections for Chinese IELTS candidates in terms of their learning styles and strategies in the IELTS study.

An Empirical Study on Learning Styles of Ethnic Minorities' Third Language Learners

Much research has focused on learners' individual differences from cognitive and affective perspectives on Second Language Acquisition,while relatively little research has been conducted to survey the role of learning styles empirically.As for third language learners' learning styles,fewer researchers have examined the differences.Using the Index of Learning Styles(ILS) developed by Felder and Soloman,this paper investigates the general distribution of different learning styles among various ethnic minorities' third language learners,and explores the correlation between learning styles and gender,nationalities.In the end,it presents several pedagogical suggestions,especially for third language learning and teaching.

An Analysis of Foreign Language Learning Styles from the Cognitive Perspective

From the 1970s,learning styles began to enter the domain of foreign language learning researches.Foreign language learning style is often regarded as a significant factor attributing to individual differences among language learners.Nowadays,many researchers begin studying individual learners'characteristics and exploring how different learners interact with external factors from cognitive perspective.The field-independence/dependence construct became a focus.Based on previous studies,the paper is committed to analyzing the nature of FID learners.It is expected that this research can establish a well-grounded basis for following studies.

Exploring the Relationship between Learning Styles and Proficiency in Verbal Communication

In the light of need to use learning styles to enhance verbal proficiency,this paper will explore the interconnectedness of learning styles and proficiency in verbal communication.It will first introduce the background of the study.This will be followed by an overview of the research on related literature and studies in the field.Lastly the paper concludes that foreign language teachers should give attention to the styles for languages learning and verbal proficiency since they are closely correlated.

On Gender Differences in Language Learning Styles

Language learning style, serving as one of the elements of individual differences in foreign language learning, has substantial significance of research for EFL teaching. Males' and females' language learning styles are quite different. This paper illustrates the gender differences in language learning styles from sensory, cognitive and personality perspectives, and offers some suggestions for EFL teaching.

Rethinking on Matching Teachers' Teaching Styles with Students' Learning Styles in ESL/EFL Classrooms

Teaching styles and learning styles play important parts in ESL/EFL classrooms. However, is it necessary for language teachers to match their teaching styles with their students' learning styles?Is it feasible for the teachers to match their teaching styles to every individual student's learning styles?Because of the incompatible learning and teaching styles, suggestions on how to deal with the difficulties in the matching of these two styles will be given.

Translating Interdisciplinary Research on Language Learning into Identifying Specific Learning Disabilities in Verbally Gifted and Average Children and Youth

The current research was grounded in prior interdisciplinary research that showed cognitive ability (verbal ability for translating cognitions into oral language) and multiple-working memory endophenotypes (behavioral markers of genetic or brain bases of language learning) predict reading and writing achievement in students with and without specific learning disabilities in written language (SLDs-WL). Results largely replicated prior findings that verbally gifted with dyslexia score higher on reading and writing achievement than those with average verbal ability but not on endophenotypes. The current study extended that research by comparing those with and without SLDs-WL with assessed verbal ability held constant. The verbally gifted without SLDs-WL (n = 14) scored higher than the verbally gifted with SLDs-WL (n = 27) on six language skills (oral sentence construction, best and fastest handwriting in copying, single real word oral reading accuracy, oral pseudoword reading accuracy and rate) and four endophenotypes (orthographic and morphological coding, orthographic loop, and switching attention). The verbally average without SLDs-WL (n = 6) scored higher than the verbally average with SLDs-WL (n = 22) on four language skills (best and fastest hand-writing in copying, oral pseudoword reading accuracy and rate) and two endophenotypes (orthographic coding and orthographic loop). Implications of results for translating interdisciplinary research into flexible definitions for assessment and instruction to serve students with varying verbal abilities and language learning and endophenotype profiles are discussed along with directions for future research.

English Learning Styles and English Achievements of Students Majoring in P.E.,Art and Music

Learning styles are considered as an important individual difference of affecting learning efficiency and English achievements.This research focuses on the sophomores whose majors are Physical Education (P.E.),Art and Music (P.A.M.students) in Yangtze Normal University to investigate into total learning styles,the relationships concerning major,English achievement respectively with learning styles.The results show that participants prefer group learning style rather than auditory learning style;there is no possible links between learning styles and their majors,and English achievements.

Machine learning applications in healthcare clinical practice and research

Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.

Transthyretin—A Key Gene Involved in Regulating Learning and Memory in Brain, and Providing Neuroprotection in Alzheimer Disease via Neuronal Synthesis of Transthyretin Protein

Transthyretin (TTR), a carrier protein present in the liver and choroid plexus of the brain, has been shown to be responsible for binding thyroid hormone thyroxin (T4) and retinol in plasma and cerebrospinal fluid (CSF). TTR aids in sequestering of beta-amyloid peptides Aβ deposition, and protects the brain from trauma, ischemic stroke and Alzheimer disease (AD). Accordingly, hippocampal gene expression of TTR plays a significant role in learning and memory as well as in simulation of spatial memory tasks. TTR via interacting with transcription factor CREB regulates this process and decreased expression leads to memory deficits. By different signaling pathways, like MAPK, AKT, and ERK via Src, TTR provides tropical support through megalin receptor by promoting neurite outgrowth and protecting the neurons from traumatic brain injury. TTR is also responsible for the transient rise in intracellular Ca2+ via NMDA receptor, playing a dominant role under excitotoxic conditions. In this review, we tried to shed light on how TTR is involved in maintaining normal cognitive processes, its role in learning and memory, under memory deficit conditions;by which mechanisms it promotes neurite outgrowth;and how it protects the brain from Alzheimer disease (AD).

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

Preliminary Network Centric Therapy for Machine Learning Classification of Deep Brain Stimulation Status for the Treatment of Parkinson’s Disease with a Conformal Wearable and Wireless Inertial Sensor

The concept of Network Centric Therapy represents an amalgamation of wearable and wireless inertial sensor systems and machine learning with access to a Cloud computing environment. The advent of Network Centric Therapy is highly relevant to the treatment of Parkinson’s disease through deep brain stimulation. Originally wearable and wireless systems for quantifying Parkinson’s disease involved the use a smartphone to quantify hand tremor. Although originally novel, the smartphone has notable issues as a wearable application for quantifying movement disorder tremor. The smartphone has evolved in a pathway that has made the smartphone progressively more cumbersome to mount about the dorsum of the hand. Furthermore, the smartphone utilizes an inertial sensor package that is not certified for medical analysis, and the trial data access a provisional Cloud computing environment through an email account. These concerns are resolved with the recent development of a conformal wearable and wireless inertial sensor system. This conformal wearable and wireless system mounts to the hand with the profile of a bandage by adhesive and accesses a secure Cloud computing environment through a segmented wireless connectivity strategy involving a smartphone and tablet. Additionally, the conformal wearable and wireless system is certified by the FDA of the United States of America for ascertaining medical grade inertial sensor data. These characteristics make the conformal wearable and wireless system uniquely suited for the quantification of Parkinson’s disease treatment through deep brain stimulation. Preliminary evaluation of the conformal wearable and wireless system is demonstrated through the differentiation of deep brain stimulation set to “On” and “Off” status. Based on the robustness of the acceleration signal, this signal was selected to quantify hand tremor for the prescribed deep brain stimulation settings. Machine learning classification using the Waikato Environment for Knowledge Analysis (WEKA) was applied using the multilayer perceptron neural network. The multilayer perceptron neural network achieved considerable classification accuracy for distinguishing between the deep brain stimulation system set to “On” and “Off” status through the quantified acceleration signal data obtained by this recently developed conformal wearable and wireless system. The research achievement establishes a progressive pathway to the future objective of achieving deep brain stimulation capabilities that promote closed-loop acquisition of configuration parameters that are uniquely optimized to the individual through extrinsic means of a highly conformal wearable and wireless inertial sensor system and machine learning with access to Cloud computing resources.

Instruction and Learning Styles & Strategies in Second Language Acquisition

1. Introduction During the last four decades, a growing realization on the relation of individual differences and language learning has awoken considerable awareness that personal cognitive abilities including intelligence, aptitude as well as emotion, motivation, in many aspects play a part in Second Language Acquisition (SLA).

Machine Learning Technology for Evaluation of Liver Fibrosis, Inflammation Activity and Steatosis (LIVERFASt^TM)

Using the latest available artificial intelligence (AI) technology, an advanced algorithm LIVERFAStTM has been used to evaluate the diagnostic accuracy of machine learning (ML) biomarker algorithms to assess liver damage. Prevalence of NAFLD (Nonalcoholic fatty liver disease) and resulting NASH (nonalcoholic steatohepatitis) are constantly increasing worldwide, creating challenges for screening as the diagnosis for NASH requires invasive liver biopsy. Key issues in NAFLD patients are the differentiation of NASH from simple steatosis and identification of advanced hepatic fibrosis. In this prospective study, the staging of three different lesions of the liver to diagnose fatty liver was analyzed using a proprietary ML algorithm LIVERFAStTM developed with a database of 2862 unique medical assessments of biomarkers, where 1027 assessments were used to train the algorithm and 1835 constituted the validation set. Data of 13,068 patients who underwent the LIVERFAStTM test for evaluation of fatty liver disease were analysed. Data evaluation revealed 11% of the patients exhibited significant fibrosis with fibrosis scores 0.6 - 1.00. Approximately 7% of the population had severe hepatic inflammation. Steatosis was observed in most patients, 63%, whereas severe steatosis S3 was observed in 20%. Using modified SAF (Steatosis, Activity and Fibrosis) scores obtained using the LIVERFAStTM algorithm, NAFLD was detected in 13.41% of the patients (Sx > 0, Ay 0). Approximately 1.91% (Sx > 0, Ay = 2, Fz > 0) of the patients showed NAFLD or NASH scorings while 1.08% had confirmed NASH (Sx > 0, Ay > 2, Fz = 1 - 2) and 1.49% had advanced NASH (Sx > 0, Ay > 2, Fz = 3 - 4). The modified SAF scoring system generated by LIVERFAStTM provides a simple and convenient evaluation of NAFLD and NASH in a cohort of Southeast Asians. This system may lead to the use of noninvasive liver tests in extended populations for more accurate diagnosis of liver pathology, prediction of clinical path of individuals at all stages of liver diseases, and provision of an efficient system for therapeutic interventions.

On the Difference between Learning Styles and Learning Strategies

The importance of individual differences in foreign language learning has been studied by many researchers.Among all the individual differences,learning styles and learning strategies are not that easy to distinguish.Many people feel confused about the two factors.This paper employs literature review method to summarize the difference between the two factors.And the author summarizes that learning styles are a kind of unconscious individual character which is often fixed and used unconsciously.Learning strategies aiming at specific tasks,can be learnt and developed,and are often used consciously.Although they are confusing and different,they are actually interrelated with each other.

Do Learners' Preferred Learning Styles Affect Learning Outcomes and Satisfaction in PLE: A Pilot Study of the Supervised-PLE-IELTS Platform

Personal Learning Environment(PLE)enables a knowledge-based,learner-centered lifelong learning which could be successfully integrated with formal education when taking educators’supervision into consideration.But do learners’preferred Learning Styles matter in PLE?To investigate the relationship among learners’Learning Styles,learning outcomes and satisfaction towards the PLE platform,the study constructed and applied a supervised-PLE-IELTS platform.57 sophomores majored in Business in Wenzhou University took part in a 16-week project.Data were collected by Honey and Mumford’s Learning Styles questionnaire for the Learning Styles,post-test of IELTS reading,listening and vocabulary for the cognitive learning outcomes,and Distance Education Learning Environments Survey(DELES)for the satisfaction towards the PLE platform.The results showed:(1)Learning Styles have positive relationship with the cognitive learning achievements in PLE;(2)Learning Styles had no direct effect on satisfaction,and learners of all Learning Styles enjoyed PLE-IELTS platform;and(3)learners who spent more time on PLE platform achieved better cognitive learning outcomes.The paper shed light on the future construction of supervised-PLEs.