Search

  • Select Article Type
  • Abstract Supplements
  • Blood Group Review
  • Call to Arms
  • Communications
  • Hypothesis
  • In Memoriam
  • Interview
  • Introduction
  • Letter to the Editor
  • Short Report
  • abstract
  • Abstracts
  • Article
  • book-review
  • case-report
  • case-study
  • Clinical Practice
  • Commentary
  • Conference Presentation
  • conference-report
  • congress-report
  • Correction
  • critical-appraisal
  • Editorial
  • Editorial Comment
  • Erratum
  • Events
  • in-memomoriam
  • Letter
  • Letter to Editor
  • mini-review
  • minireview
  • News
  • non-scientific
  • Obituary
  • original-paper
  • original-report
  • Original Research
  • Pictorial Review
  • Position Paper
  • Practice Report
  • Preface
  • Preliminary report
  • Product Review
  • rapid-communication
  • Report
  • research-article
  • Research Communicate
  • research-paper
  • Research Report
  • Review
  • review -article
  • review-article
  • review-paper
  • Review Paper
  • Sampling Methods
  • Scientific Commentary
  • serologic-method-review
  • short-communication
  • short-report
  • Student Essay
  • Varia
  • Welome
  • Select Journal
  • In Jour Smart Sensing And Intelligent Systems
  • International Journal Of Orientation And Mobility
  • Journal Of Educational Leadership Policy And Pract
  • International Journal Advanced Network Monitoring Controls
  • Architecture Civil Engineering Environment
  • Transport Problems
  • Journal Of Ultrasonography
  • Acta Neurobiologiae Experimentalis
  • Connections
  • Apex
  • Statistics In Transition

 

Article | 07-May-2018

Advanced Dynamic Autonomous Knowledge Learning Method for Distance Learning

As the manufacturing of vast amount of information transmits at an unprecedented rate, traditional learning is no way to meet the needs of open learning and lifelong learning, how can distance learning be used to help us study become a problem to think about. Distance learning requires improvement of interactivity and initiative to achieve their aptitude. Using a variety of formats data, learners master the initiative in the learning process, it is not easy to lead to deviation from the

Yanfang Fu, Xing Li, Xueyao Feng, Jing Ma

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 2, 33–39

Article | 09-June-2019

New spaces – new pedagogies: Implementing personalised learning in primary school innovative learning environments

The New Zealand Ministry of Education is requiring that all primary school “new builds” and renovations be Innovative Learning Environments (ILEs), and within these spaces there is an expectation that personalised learning is to be implemented. This qualitative study involved an investigation of practice in three Auckland primary schools where an innovative learning environment existed and personalised learning was being implemented. In each setting, a school leader and a teacher

Carol Cardno, Emma Tolmie, Jo Howse

Journal of Educational Leadership, Policy and Practice, Volume 33 , ISSUE 1, 111–124

Article | 14-October-2020

Hierarchical Image Object Search Based on Deep Reinforcement Learning

information transmitted to us by vision, and only part of the information in these visual images is what human need. Therefore, by extracting the important information, positioning and identifying them accurately, human can greatly reduce the amount of data that the computer needs to process and improve the efficiency of data processing. Reinforcement learning is an important field in machine learning. It constructs a Markov Decision Process and simulates human thinking to teach agents how to make actions

Wei Zhang, Hongge Yao, Yuxing Tan

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 3, 65–72

Article | 07-May-2018

An Ensemble Learning Method for Text Classification Based on Heterogeneous Classifiers

Ensemble learning can improve the accuracy of the classification algorithm and it has been widely used. Traditional ensemble learning methods include bagging, boosting and other methods, both of which are ensemble learning methods based on homogenous base classifiers, and obtain a diversity of base classifiers only through sample perturbation. However, heterogenous base classifiers tend to be more diverse, and multi-angle disturbances tend to obtain a variety of base classifiers. This paper

Fan Huimin, Li Pengpeng, Zhao Yingze, Li Danyang

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 1, 130–134

Review | 06-February-2018

Functional organization of the human amygdala in appetitive learning

The amygdala is a small subcortical structure located bilaterally in medial temporal lobes. It is a key region for emotional processes and some forms of associative learning. In particular, the role of the amygdala in processing of negative emotions and aversive learning has been shown in numerous studies. However, involvement of this structure in processing of positive affect and appetitive learning is not fully understood. Previous experiments in animals are not consistent. While some authors

Emilia Kolada, Krzysztof Bielski, Marcel Falkiewicz, Iwona Szatkowska

Acta Neurobiologiae Experimentalis, Volume 77 , ISSUE 2, 118–127

Article | 11-April-2018

Intrusion Detection Based on Self-adaptive Differential Evolutionary Extreme Learning Machine

Nowadays with the rapid development of network-based services and users of the internet in everyday life, intrusion detection becomes a promising area of research in the domain of security. Intrusion detection system (IDS) can detect the intrusions of someone who is not authorized to the present computer system automatically, so intrusion detection system has emerged as an essential component and an important technique for network security. Extreme learning machine (ELM) is an interested area

Junhua Ku, Bing Zheng, Dawei Yun

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 54–60

Article | 01-June-2015

DESIGN OF COMPLICATED DUPLICATE IMAGE REPRESENTATION APPROACH BASED ON DESCRIPTOR LEARNING

In order to solve the low discrimination of image representations in complicated duplicate image detection, this paper presents a complicated duplicate image representation approach based on descriptor learning. This approach firstly formulates objective function as minimizing empirical error on the labeled data. Then the tag matrix and the classification matrix of training dataset are brought into the objective function to ensure semantic similarity. Finally, by relaxing the constraints, we

Yongjiao Wang, Xiaojie Du, Lei Liang

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 2, 992–1010

research-article | 31-August-2021

Deep Learning in Product Manufacturing Record System

packaging, provides comprehensive analysis of product production data, and establishes a production record system that focuses on the production process. In the intelligent manufacturing mode, the operator uses the code scanning gun to enter the relevant data of the product. It greatly improves the efficiency of production data collection and facilitates the improvement of product production efficiency. Deep learning has taken off in recent years, making major breakthroughs not only in medical research

Wenjing Wang, Li Zhao

International Journal of Advanced Network, Monitoring and Controls, Volume 6 , ISSUE 3, 59–65

Article | 07-April-2018

Behavior Control Algorithm for Mobile Robot Based on Q-Learning

In order to adapt to navigation in unknown environment, the mobile robot must have intelligent abilities, such as environment cognition, behavior decision and learning. The navigation control algorithm is researched based on Q learning method in this paper. Firstly, the corresponding environment state space is divided. The action sets mapping with states are set. And the reward function is designed which combines discrete reward returns and continuous reward. The feasibility of this algorithm

Shiqiang Yang, Congxiao Li

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 1, 108–114

research-article | 30-November-2019

Concept Drift Evolution In Machine Learning Approaches: A Systematic Literature Review

Big Data (BD) is participating in the current computing revolution immensely. Industries and organizations are utilizing their insights for Business Intelligence using Machine Learning (ML) models. However, BD’s dynamic characteristics introduce many critical issues for ML models, such as the Concept Drift (CD) issue. The issue of CD is observed when the statistical properties of data vary at a different time step. For example, a set of class examples has legitimate class labels at one time

Manzoor Ahmed Hashmani, Syed Muslim Jameel, Mobashar Rehman, Atsushi Inoue

International Journal on Smart Sensing and Intelligent Systems, Volume 13 , ISSUE 1, 1–16

Article | 11-April-2018

Self-adaptive Differential Evolutionary Extreme Learning Machine and Its Application in Facial Age Estimation

In this paper, Self-adaptive Differential Evolutionary Extreme Learning Machine (SaDE-ELM) was proposed as a new class of learning algorithm for single-hidden layer feed forward neural network (SLFN). In order to achieve good generalization performance, SaDE-ELM calculates the error on a subset of testing data for parameter optimization. Since SaDE-ELM employs extra data for validation to avoid the over fitting problem, more samples are needed for model training. In this paper, the cross

Junhua Ku, Kongduo Xing

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 72–77

Article | 09-June-2019

What do teachers and leaders have to say about co-teaching in flexible learning spaces?

Schools in New Zealand and parts of Australia are rapidly transitioning from traditional classrooms to coteaching in flexible learning spaces provisioned for 50 to 180 children and two to six teachers in a single space. In New Zealand, this transition is driven by the Ministry of Education who have specific guidelines for designing new schools and re-builds. School leaders and teachers must reconceptualise teaching and learning from private autonomous learning environments to co-teaching in

Julie Mackey, Neil O'Reilly, Jo Fletcher, Chris Jansen

Journal of Educational Leadership, Policy and Practice, Volume 33 , ISSUE 2, 97–110

Article | 09-June-2019

Teacher leadership report: How student-led pedagogy in modern learning environments (MLEs) can improve literacy learning

Our teacher leadership story comes from two schools collaborating on a New Zealand Teacher Led Innovation Fund (TLIF) project exploring the effect of student-led learning practices on literacy achievement within modern learning environments (MLEs).  Our rationale is that learning which is individualised for all learners leads to more equitable outcomes for all. It also enables student ownership of learning, which in turn increases success for all learners, measured through improved student

Ann R Briggs, Bek Gabites, Scott Mackenzie, Julie McIntosh, Josh Shelley, Peter Verstappen

Journal of Educational Leadership, Policy and Practice, Volume 32 , ISSUE 1, 62–69

Article | 09-June-2019

Collaborative teaching in flexible learning spaces: Capabilities of beginning teachers

Increasingly, New Zealand primary and intermediate schools are adopting the concept of flexible learning spaces and promoting team teaching approaches. Such open spaces and pedagogy can be challenging for even experienced teachers to adapt to. Is it realistic, therefore, to expect novices to work successfully in these challenging spaces from the onset of their teaching careers? Initial Teacher Education (ITE) programmes in New Zealand equip graduates with the knowledge and skills to plan, teach

Barbara Whyte

Journal of Educational Leadership, Policy and Practice, Volume 32 , ISSUE 1, 84–96

Article | 01-March-2015

RECOMMENDER ALGORITHMS BASED ON BOOSTING ENSEMBLE LEARNING

This article introduces ensemble learning algorithms in recommender systems, and in boosting algorithm framework of this article, shows how to filter the basic recommendation algorithm according to the characteristics of boosting algorithm. By comparing the rational choice of the two recommended boosting algorithm is applied to the frame. And then it determines the main parameters of the algorithm through the experiments, ultimately to obtain a more effective integration of the recommendation

Cheng Lili

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 368–386

Article | 21-April-2019

The “state of play” concerning New Zealand’s transition to innovative learning environments: Preliminary results from phase one of the ILETC project

Driven by international trends and government policy, it is a requirement for all newly built schools in New Zealand to be designed as innovative learning environments (ILEs) with flexible learning spaces. These environments, celebrated by some for the “transformational” educational opportunities they may provide, also raise questions about whether the anticipated pedagogical value of these “non-traditional” spaces is based on idealised visions of teaching and learning

Chris Bradbeer, Marian Mahat, Terry Byers, Ben Cleveland, Thomas Kvan, Wesley Imms

Journal of Educational Leadership, Policy and Practice, Volume 32 , ISSUE 1, 22–38

Research Article | 08-February-2019

SPACE FOR UNIVERSITY STUDENTS: SPECIFIC REQUIREMENTS FOR “SELF-LEARNING” ENVIRONMENT – THEORETICAL APPROACH

Abstract The paper presents a humanistic approach in investigation of people-environment relations within university buildings. Architecture of the university buildings is considered to be a learning environment from the position of “critical pedagogy of place”. It emphasizes the importance of the place itself expressed by the specific link between building and its location understood mainly in environmental terms – not only as a functional node but also as a vital element of cultural and also

Angelika LASIEWICZ-SYCH

Architecture, Civil Engineering, Environment, Volume 11 , ISSUE 4, 31–40

research-article | 30-November-2019

The Discriminant Analysis Approach for Evaluating Effectiveness of Learning in an Instructor-Led Virtual Classroom

Educational psychology affords many academic values to be applied in the growth and evaluation of computer-assisted instructional technology. Milheim and Martin (1991) identified learner control as a significant variable in increasing the pedagogy of software in studying learner control motivation, attribution, and informational processing theory. It is advantageous for making best use of learner control as it enhances the relevance of learning, expectations for success, and general contentment

D. Magdalene Delighta Angeline, P. Ramasubramanian, I. Samuel Peter James

International Journal on Smart Sensing and Intelligent Systems, Volume 13 , ISSUE 1, 1–15

Article | 01-June-2015

OPPOSITION-BASED LEARNING PARTICLE SWARM OPTIMIZATION OF RUNNING GAIT FOR HUMANOID ROBOT

This paper investigates the problem of running gait optimization for humanoid robot. In order to reduce energy consumption and guarantee the dynamic balance including both horizontal and vertical stability, a novel running gait generation based on opposition-based learning particle swarm optimization (PSO) is proposed which aims at high energy efficiency with better stability. In the proposed scheme of running gait generation, a population initiation policy based on domain knowledge is employed

Liang Yang, Song Xijia, Chunjian Deng

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 2, 1162–1179

Article | 09-June-2019

A New Zealand case study: What is happening to lead changes to effective co-teaching in flexible learning spaces?

team who changed the school culture from traditional one teacher per classroom settings to four to five teachers with approximately 105 students in flexible learning spaces. The principal and three members of the governing Board of Trustees of the school were interviewed. The study found that the leadership team had invested considerable time into sustained professional development in ways to effectively develop collaborative teaching communities within flexible learning spaces. The professional

Jo Fletcher, Julie Mackey, Letitia Fickel

Journal of Educational Leadership, Policy and Practice, Volume 32 , ISSUE 1, 70–83

research-article | 30-November-2019

Serotonin and noradrenaline content and release in the dorsal hippocampus during learning and spatial memory in prenatally stressed rats

INTRODUCTION In rodents, maternal stress during pregnancy can cause psychopathologies in the offspring, such as anxiety and depressive-like behaviors, as well as cognitive deficits (Weinstock, 2017). Also, alterations in development and maturation of brain structures, such as the hippocampus, have been reported (Fujioka et al., 2006). The dorsal hippocampus is involved in spatial learning and memory processes in rats and primates (Bannerman et al., 2004; Tanti and Belzung, 2013; Grigoryan and

Diana Méndez Guerrero, Felipe de Jesús Jiménez Vásquez, Moisés Rubio Osornio, María del Carmen Rubio Osornio, Sandra Orozco Suárez, Socorro Retana-Márquez

Acta Neurobiologiae Experimentalis, Volume 80 , ISSUE 4, 400–410

Article | 01-December-2014

A SCENE RECOGNITION ALGORITHM BASED ON MULTI-INSTANCE LEARNING

. Considering the traditional classification method based on Bag of Words model is vulnerable to the background, block and scalar variance of an image, we propose in this article a multiple visual words learning method for image classification, which is based on the concept of visual phrases combined with Multiple Instance Learning. The final classification model is able to show the spatial features of image classes. Experiments performed on standard image testing sets, Caltech 101 and Scene 15, show the

Tao Wang, Wenqing Chen, Bailing Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 4, 1470–1492

research-article | 30-November-2020

Regular aerobic exercise increased VEGF levels in both soleus and gastrocnemius muscles correlated with hippocampal learning and VEGF levels

INTRODUCTION Many aspects of the health benefits of exercise are known, such as those in endocrine and cardiovascular systems, as well as metabolic and developmental functions (Hughes et al., 1993; Ostergard et al., 2006; Labonte-Lemoyne et al., 2017; Lin and Lee, 2018). In recent years, scientific research has focused on the effects of exercise on the neurocognitive process. Exercise has been shown to improve learning and memory function by increasing neurogenesis and angiogenesis in the

Asli Karakilic, Oguz Yuksel, Servet Kizildag, Ferda Hosgorler, Birsu Topcugil, Rabia Ilgin, Hikmet Gumus, Guven Guvendi, Basar Koc, Sevim Kandis, Mehmet Ates, Nazan Uysal

Acta Neurobiologiae Experimentalis, Volume 81 , ISSUE 1, 1–9

Research Article | 20-February-2013

ADAPTIVE ESTIMATION AND PI LEARNING SPRING-RELAXATION TECHNIQUE FOR LOCATION ESTIMATION IN WIRELESS SENSOR NETWORKS

In order to reduce the location estimation error in Wireless Sensor Network(WSN). A localization algorithm is proposed combining adaptive estimation, PI-learning and spring-relaxation techniques for wireless sensor networks in this paper. Our proposed method takes the advantages of the spring-relaxation technique, thus it inherits its simplicity. The overall accuracy of the location estimations is improved by introducing adaptive estimation and PI-learning. Moreover, it requires only a few

Li Haiyan, Hu Yun-an, Zhu Min

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 1, 317–332

research-article | 30-November-2020

Development of a computer-based simple pendulum experiment set for teaching and learning physics

. Moreover, these methods do not provide adequate opportunities for the students to think critically to solve a problem (Adams et al., 2006; Schauer et al., 2009; Wieman and Perkins, 2005). Along with the conventional teaching method, laboratory activities are essential as it allows the students to get involved in the learning process. Students start thinking critically while conducting laboratory works. Self-explored experience from laboratory activities helps the students understand and recognize laws

Warawut Sukmak, Panjit Musik

International Journal on Smart Sensing and Intelligent Systems, Volume 14 , ISSUE 1, 1–8

research-article | 15-October-2020

Subchronic effects of ligands of cannabinoid receptors on learning and memory processes of olfactory bulbectomized rats

INTRODUCTION Endocannabinoid system (ECS) plays role in many physiological processes, including mood, learning and memory. It is also involved in the pathogenesis of anxiety and mood disorders, as well as neurodegenerative disorders (Hill and Gorzalka, 2009; Ranieri et al., 2016). ECS consists of the endogenous cannabinoids (endocannabinoids), cannabinoid receptors and the enzymes that synthesize and degrade endocannabinoids. The cannabinoid receptors (CB1 and CB2) belong to the class of G

Margarita Velikova, Dobrinka Doncheva, Roman Tashev

Acta Neurobiologiae Experimentalis, Volume 80 , ISSUE 3, 286–296

Research Article | 01-September-2017

LEARNING TO RANK AND CLASSIFICATION OF BUG REPORTS USING SVM AND FEATURE EVALUATION

descriptions of library components, the bug-fixing history, the code change history, and the file dependency graph. Given a bug report, the ranking score of each source file is computed as a weighted combination of an array of features, where the weights are trained automatically on previously solved bug reports using a learning-to-rank technique. I applied SVM (Support Virtual Machine) to classify the bug reports to identify, which category the bug belongs to. It helps to fix the critical defects early

S. Rajeswari, S. Sharavanan, R. Vijai, RM. Balajee

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 311–329

Article | 01-December-2016

THE IMPLEMENTATION OF A CLOUD SYSTEM FOR ELECTRONICS LEARNING IN A MOROCCAN PUBLIC UNIVERSITY

Educational laboratories are places for realizing experimentations and they are important for modern engineering education. The problem is what if there are simply not enough devices or time for conducting experimentation in a local lab? Other factors that prevent the use of local lab devices directly by students are inaccessible or dangerous phenomena, or polluting chemical reactions. The new technologies bring additional strategies of learning and teaching, so it becomes a challenge to

Khalid Ghoulam, Belaid Bouikhalene, Zakaria Harmouch, Hicham Mouncif

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 4, 2051–2068

research-paper | 30-November-2020

Brain-derived neurotrophic factor and nitric oxide contribute to protective effects of rosiglitazone on learning and memory in hypothyroid rats

alterations, which lead to behavioral abnormalities, including learning and memory impairment (Ahmed et al., 2008; Ritchie and Yeap, 2015). These hormones regulate the growth factor expression and synaptogenesis in learning and memory-related brain areas, including the hippocampus and cortex (Forrest and Vennström, 2000; Parent et al., 2011). The hippocampus appears to be more sensitive than the cortex to thyroid hormone depletion (Zhang et al., 2009; Parent et al., 2011). The exact mechanism of cognitive

Yousef Baghcheghi, Farimah Beheshti, Hossein Salmani, Mahmoud Hosseini

Acta Neurobiologiae Experimentalis, Volume 81 , ISSUE 3, 218–232

Research paper | 15-January-2019

Detrimental effects of chia (Salvia hispanica L.) seeds on learning and memory in aluminum chloride-induced experimental Alzheimer’s disease

established (i.e., treatment). A battery of behavioral and cognitive tests were performed, including open-field, elevated plus maze, Porsolt’s forced swim, and Morris’ water maze, to evaluate anxietyand depression-like behaviors, and learning and memory. Results showed that chia supplementation was ineffective against Alzheimer’s-related anxiety, whereas depression-like behaviors were attenuated with both pretreatment and treatment. There was no improvement in learning and memory with chia treatment

Yasemin Bilgic, Enver Ahmet Demir, Nilufer Bilgic, Hatice Dogan, Okan Tutuk, Cemil Tumer

Acta Neurobiologiae Experimentalis, Volume 78 , ISSUE 4, 322–331

research-article | 30-November-2020

Deep brain stimulation effects on learning, memory and glutamate and GABAA receptor subunit gene expression in kindled rats

al., 1994; Gilbert et al., 2000). Learning and memory are highly complex processes. Each is accompanied by changes in brain activity, including synaptic plasticity in the form of long-term potentiation (LTP) and LTD (Kemp and Manahan-Vaughan, 2007). Previous studies showed that NMDARs play an important role in synaptic plasticity (Hunt and Castillo, 2012), learning and memory (Li and Tsien, 2009), and epileptogenesis (Frasca et al., 2011). Changes in the NR2A to NR2B subunits ratio affect the

Mona Faraz, Nastaran Kosarmadar, Mahmoud Rezaei, Meysam Zare, Mohammad Javan, Victoria Barkley, Amir Shojaei, Javad Mirnajafi-Zadeh

Acta Neurobiologiae Experimentalis, Volume 81 , ISSUE 1, 43–57

Research Article | 06-July-2018

Asessment for Learning with Young Gifted Children

This paper argues that assessment practices used by teachers in schools and early childhood services, including narrative approaches, provide accessible, authentic, low-cost, and easily administered assessment. Assessment for learning embeds assessment within teaching and learning and supports teachers to work in collaboration with parents and children to deepen understanding of children’s strengths and interests, and to support relationships. Further, assessment for learning provides an

Valerie Margrain

Apex, Volume 16 , ISSUE 1, 37–48

Article | 01-June-2015

IMMERSIVE LEARNING SUPPORT SYSTEM BASED ON KINECT SENSOR FOR CHILDREN TO LEARN ABOUT PALEONTOLOGICAL ENVIRONMENTS

This paper proposes a simulation-based environmental learning support system, based on Kinect sensors, which is currently under development. Our system animates paleontological animals and their habitats on a display in synchronization with learners’ actions, immersing learners in a real-life paleontological environment. We evaluated the system by recording real-time measurements of learners’ movements, and controlled the animation based on sensor output. Participants were subsequently

T. Nakayama, R. Yoshida, T. Nakadai, T. Ogitsu, H. Mizoguchi, K. Izuishi, F. Kusunoki, K. Muratsu, R. Egusa, S. Inagaki

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 2, 1050–1062

Research Article | 03-September-2018

A Context-aware Smart Classroom for Enhanced Learning Environment

Research on smart spaces represents one of the most innovative work being done recently. One of the interesting applications of smart spaces is the smart classroom. It aims at using new technologies and tools to provide adaptive, comfortable and personalized learning which supports and facilitates the learning operation. Often instructors waste a precious time of theirs courses on tasks not directly related to the course content especially adjusting several times both the light system of the

Moeiz Miraoui

International Journal on Smart Sensing and Intelligent Systems, Volume 11 , ISSUE 1, 1–8

Research paper | 18-May-2018

Possible role of hippocampal GPR55 in spatial learning and memory in rats

Endocannabinoids (eCBs) are involved in the hippocampal mechanisms of spatial learning and memory in rats. Although eCBs exert many of their actions on spatial learning and memory via CB1 receptors, the putative cannabinoid receptor GPR55 (expressed in the hippocampus, cortex, forebrain, cerebellum and striatum) seems to be also involved. To investigate the potential role of GPR55 in spatial learning and memory, Wistar rats received bilateral infusions of lysophosphatidylinositol (LPI, GPR55

Bruno A. Marichal-Cancino, Alfonso Fajardo-Valdez, Alejandra E. Ruiz-Contreras, Mónica Méndez-Díaz, Oscar Prospéro-García

Acta Neurobiologiae Experimentalis, Volume 78 , ISSUE 1, 41–50

Article | 02-April-2019

Data- and research-informed improvement work in ECE

The article describes an approach to data- and research-informed improvement work in Early Childhood Education and Care (ECEC) that is used by the Laboratory for Research-based School Development (LSP) at Aalborg University, Denmark. The approach includes collaboration between research, policy and practice and it incorporates two current policy priorities in the field of Danish education: evidence-informed decision making and the continuous improvement of the learning environment. The approach

Line Skov Hansen

Journal of Educational Leadership, Policy and Practice, Volume 33 , ISSUE 1, 70–81

Article | 30-November-2018

Street View House Number Identification Based on Deep Learning

designed manually (such as SIFT, SURF, HOG, etc.), and the features of the artificial design are well interpreted. However, in the face of complex backgrounds, changing fonts and various deformations, it is rather troublesome and difficult to extract more general features[7]. The Convolutional Neural Network (CNN) is a multi-layered supervised learning neural network. Although the training process requires a large amount of data compared with the traditional method, the convolutional neural network can

Haoqi Yang, Hongge Yao

International Journal of Advanced Network, Monitoring and Controls, Volume 4 , ISSUE 3, 47–52

Article | 16-April-2018

Using TTouch to Reduce Stress and Enhance Learning when Training Guide Dogs

Excessive stress impairs learning. The Tellington TTouch method (TTouch) is used to reduce stress and relax animals so they can learn more effectively. It aims at increasing an animal’s body awareness and balance by using a combination of techniques that include specific touches, body wraps, and leading (movement) exercises. This article introduces the TTouch method, its role in sensory enhanced learning, and provides a review of TTouch in the scientific literature and the way this

Janice Lloyd, Elizabeth (Lib) Roe

International Journal of Orientation & Mobility, Volume 6 , ISSUE 1, 8–20

research-article | 25-October-2021

Using explainable deep learning in da Vinci Xi robot for tumor detection

-assisted diagnostics of prostate core needle biopsies (CNBs) by developing an algorithm that takes input as hematoxylin and eosin (H&E) stained slides outputs the result with 0.997 AUC. Deep learning was also used for detecting cancer in animals (Aubreville et al., 2020), agricultural greenhouse detection (Li et al., 2020), analyzing traffic load distribution on a bridge (Ge et al., 2020), airplane detection (Chen et al., 2018), hand gesture recognition (Kharate et al., 2016), automatic vehicle

Rohan Ibn Azad, Subhas Mukhopadhyay, Mohsen Asadnia

International Journal on Smart Sensing and Intelligent Systems, Volume 14 , ISSUE 1, 1–16

Article | 21-April-2019

Assessment within ILP: A journey of collaborative inquiry

Innovative Learning Pedagogies (ILPs) have given rise to much focus on the pedagogical changes required to ensure students work collaboratively, apply knowledge, create outcomes and communicate these outcomes effectively. One key element that has had much less focus is how students are assessed when working in an Innovative Learning Environment (ILE) and how this assessment information might be communicated to all stakeholders. As a school, we commenced our collaborative inquiry using action

Linda Harvie, Steve Harper-Travers, Amanda Jaeger

Journal of Educational Leadership, Policy and Practice, Volume 32 , ISSUE 1, 133–139

research-article | 07-July-2020

Effects of sex steroid hormones on memory

, gonadal hormones are also assumed to have an influence on many cerebral function. Finally, even though much of the evidence on gonadal-induced neuroplasticity, related to learning and memory processes, centers on the effect of estrogens, data related to neurotrophic actions of androgens also exist (Colciago et al., 2015). Role of estrogens in memory processes Many studies have suggested that estrogens have a role on many cognitive functions, including learning and memory (Gasbarri et al., 2008a

Assunta Pompili, Carla Iorio, Antonella Gasbarri

Acta Neurobiologiae Experimentalis, Volume 80 , ISSUE 2, 117–128

Review | 25-July-2017

Behavioral verification of associative learning in whisker-related fear conditioning in mice

Fear-conditioning is one of the most widely used paradigms in attempts to unravel the processes and mechanisms underlying learning and plasticity. In most Pavlovian conditioning paradigms an auditory stimulus is used as the conditioned stimulus (CS), but conditioning to a tactile CS can also be accomplished. The whisker-to-barrel tactile system in mice offers a convenient way to investigate the brain pathways and mechanisms of learning and plasticity of the cerebral cortex. To support the claim

Anita Cybulska-Kłosowicz

Acta Neurobiologiae Experimentalis, Volume 76 , ISSUE 2, 87–97

Article | 01-September-2014

UNMANNED AERIAL VEHICLE PATH PLANNING BASED ON TLBO ALGORITHM

Path planning of unmanned aerial vehicle (UAV) is an optimal problem in the complex combat field environment. Teaching-Learning-Based Optimization (TLBO) algorithm is presented under the inspiration of the teaching-learning behavior in a classroom. In this paper, this algorithm is applied to design a path by the search angle and distance, by which a better path at higher convergence speed and shorter route can be found. Finally experimental comparison results show that TLBO algorithm is a

Guolin Yu, Hui Song, Jie Gao

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 3, 1310–1325

research-paper | 30-November-2020

Role of NR2B/ERK signaling in the neuroprotective effect of dexmedetomidine against sevoflurane induced neurological dysfunction in the developing rat brain

clinical concentrations can lead to neuronal apoptosis and impair the learning ability and cognitive function in neonatal and aged rodents (Kodama et al., 2011; Li XM et al., 2014; Sun et al., 2016). Previous retrospective studies have reported that the application of anesthesia in children may influence the progression of behavior and cognitive function, especially children younger than 3 years old (DiMaggio et al., 2009; Wilder et al., 2009; Servick, 2014). Because of the common use of sevoflurane in

Guohua Li, Fang Cao, Yanwu Jin, Yu Wang, Dawei Wang, Limin Zhou

Acta Neurobiologiae Experimentalis, Volume 81 , ISSUE 3, 271–278

Article | 01-December-2016

HYPERSPECTRAL DATA FEATURE EXTRACTION USING DEEP BELIEF NETWORK

Hyperspectral data has rich spectrum information, strong correlation between bands and high data redundancy. Feature band extraction of hyperspectral data is a prerequisite and an important basis for the subsequent study of classification and target recognition. Deep belief network is a kind of deep learning model, the paper proposed a deep belief network to realize the characteristics band extraction of hyperspectral data, and use the advantages of unsupervised and supervised learning of deep

Jiang Xinhua, Xue Heru, Zhang Lina, Zhou Yanqing

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 4, 1991–2009

research-article | 31-August-2021

A Review of Lane Detection Based on Semantic Segmentation

-spline model uses multiple control points to fit the lane lines, also based on parallel perspective technology, and the algorithm is highly accurate but has poor real-time performance; moreover, the method divides the lane lines into multiple areas for separate detection, especially in the presence of false lane lines or lane wear, and the accuracy of the algorithm is not guaranteed, and the lane line jump is serious. B. Deep learning methods Research on lane detection based on deep learning neural

Jiaqi Shi, Li Zhao

International Journal of Advanced Network, Monitoring and Controls, Volume 6 , ISSUE 3, 1–8

Research Article | 06-July-2018

Personalising Learning in Secondary Schools: Gifted Education Leading the Way

gifted and talented education. The ways in which the programme meets holistic needs of students, in partnership with their families, leads the way to greater personalisation of learning in secondary education.  

Vivienne Russell, Tracy Riley

Apex, Volume 16 , ISSUE 1, 17–25

Review | 15-January-2019

c-Fos and neuronal plasticity: the aftermath of Kaczmarek’s theory

The development of molecular biology methods in the early 1980s led to a better understanding of the role of transcription factors in mammalian cells. The discovery that some transcription factors are critically important for cells to switch between different functional states was fundamental for modern molecular neurobiology. In the 1980s Leszek Kaczmarek proposed that, analogically to the cell cycle or to cell differentiation, long-term synaptic plasticity, learning, and memory should also

Jacek Jaworski, Katarzyna Kalita, Ewelina Knapska

Acta Neurobiologiae Experimentalis, Volume 78 , ISSUE 4, 287–296

Article | 09-June-2019

You have to start somewhere: Designing, tailoring and tinkering. A reflection on leading a change process

This story of leading change is written by the Principal and Deputy Principal of Thorrington School in Christchurch where the leadership focus has been to shift curriculum design and teaching practices to be more responsive to the needs of learners.  The article considers the shift in the practices of twenty teachers over a three-year time frame. The school does not have purpose built Modern Learning Spaces / Environments (referred to as flexible learning spaces in this article) so

Christine Harris, Chris Panter

Journal of Educational Leadership, Policy and Practice, Volume 32 , ISSUE 1, 125–132

Article | 13-July-2020

Image Inpainting Research Based on Deep Learning

technology and method that can automatically inpainting damaged digital images, so digital image inpainting technology is born. I. INTRODUCTION Image inpainting is one of the most popular areas of deep learning. Its basic principle is to give an image of a damaged or corroded area, and try to use the intact information of the known area of the damaged image to inpainting the damaged area of the image[1-2]. Digital image inpainting methods can be divided into two major categories: traditional image

Zhao Li, Zhao Ruixia

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 2, 23–30

Article | 14-July-2019

MODELING OF PASSENGERS’ CHOICE USING INTELLIGENT AGENTS WITH REINFORCEMENT LEARNING IN SHARED INTERESTS SYSTEMS; A BASIC APPROACH

The purpose of this paper is to build a model for assessing the satisfaction of passenger service by the public transport system. The system is constructed using intelligent agents, whose action is based on self-learning principles. The agents are passengers who depend on transport and can choose between two modes: a car or a bus wherein their choice of transport mode for the next day is based on their level of satisfaction and their neighbors’ satisfaction with the mode they used the day

Sergey VIKHAREV, Maxim LYAPUSTIN, Danil MIRONOV, Irina NIZOVTSEVA, Vladimir SINITSYN

Transport Problems, Volume 14 , ISSUE 2, 43–53

Article | 30-November-2018

Hazard Grading Model of Terrorist Attack Based on Machine Learning

Jun Yu, Tong Xian, Zhiyi Hu, Yutong Liu

International Journal of Advanced Network, Monitoring and Controls, Volume 4 , ISSUE 2, 81–85

Research paper | 22-August-2018

Administration of muscarinic antagonists induce changes in passive avoidance learning and in synaptic transmission in the CA1 area of the hippocampus

Muscarinic acetylcholine receptors (mAChR) are known to be related to learning and memory processes. Inactivation of mAChR by cholinergic antagonists have been shown to produce amnesia in a variety of behavioral tasks. In this study, we investigated the role of M1 and M2 AChR on passive avoidance learning and plasticity of synapses formed by Schaffer collaterals in freely moving rats. Experiments were performed using Wistar male rats. Seven days before testing, a recording electrode was lowered

Yulia V. Dobryakova, Olga Y. Ivanova, Vladimir A. Markevich

Acta Neurobiologiae Experimentalis, Volume 78 , ISSUE 2, 132–139

Article

Effective leadership practices leading to distributed leadership

Aotearoa New Zealand to capture a picture of current perceptions of ECE teachers and positional leaders about distributed leadership for professional learning. Subsequently, leadership practices for distributed leadership in three previously-identified high quality ECE services were investigated through individual and group interviews. The analysis of literature, survey and interview findings from this study led to a framework of effective leadership practice, consisting of: mentoring and coaching

Rachel Denee, Kate Thornton

Journal of Educational Leadership, Policy and Practice, Volume 32 , ISSUE 2, 33–45

Article | 14-October-2020

A Comparative Study of Face Recognition Classification Algorithms

I. INTRODUCTION With the rise of artificial intelligence and machine learning, face recognition technology is widely used in life, such as station security, time and attendance punching, and secure payment [1-3], but different face recognition devices use different algorithms. Therefore, this paper analyzes and compares the commonly used classification algorithms in face recognition. The data set in this paper uses the ORL face data set published by Cambridge University in the United Kingdom

Changyuan Wang, Guang Li, Pengxiang Xue, Qiyou Wu

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 3, 23–29

Article | 30-November-2018

Image Transformation Based on Generative Adversarial Networks

In recent years, with the rapid development of artificial intelligence, machine learning methods represented by statistical machine learning and deep learning are one of the main research directions [1]. Among them, the model of deep learning can be divided into discriminant model and generative model. Because of the invention of Logistic Regression, Support Vector Machine, Conditional Random Field and other algorithms, the discriminant model has developed rapidly. However, the development of

Jie Chen, Li Zhao

International Journal of Advanced Network, Monitoring and Controls, Volume 4 , ISSUE 2, 93–98

Article | 02-April-2019

Making sense of leadership in early childhood education: Tensions and complexities between concepts and practices

plays in providing quality care and education, there was much confusion about what leadership entailed and how leadership differentiated from management in this context. The contextual complexities of the ECE sector were a significant influence on each participant’s opportunity to learn about, and practise leadership. Findings also revealed a need for contextually relevant and progressive approaches to leadership learning to support early childhood leaders and teachers in their leadership work.

Nicki Klevering, Rachel McNae

Journal of Educational Leadership, Policy and Practice, Volume 33 , ISSUE 1, 5–17

Article | 16-December-2013

Electrocardiogram for Biometrics by using Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ): Integrating Feature Extraction and Classification

Electrocardiogram (ECG) signal for human identity recognition is a new area on biometrics research. The ECG is a vital signal of human body, unique, robustness to attack, universality and permanence, difference to others traditional biometrics technic. This study also proposes Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ), that integrating feature extraction and classification method. The experiments shown that AMGLVQ can improve the accuracy of classification better

Elly Matul Imah, Wisnu Jatmiko, T. Basaruddin

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 5, 1891–1917

Article | 30-November-2020

Deep Periocular Recognition Method via Multi-Angle Data Augmentation

I. INTRODUCTION Identity identification is a basic problem in social life [1], which is not only closely related to the interests of individuals, but also affected national security and social stability. This paper studies the periocular recognition technology based on deep learning, which is to use the image of the eye area to identify the identity of people. Due to the high precision, high ease of use and high security of the eye circumference [2], it is easy to obtain eye images, analyze

Bo Liu, Songze Lei, Yonggang Li, Aokui Shan, Baihua Dong

International Journal of Advanced Network, Monitoring and Controls, Volume 6 , ISSUE 1, 11–17

Editorial | 30-November-2019

Learning to scan for approaching vehicles efficiently with a visual impairment

approaching vehicles with enough warning when looking steadily in their direction, they are unlikely to see them reliably when looking from side to side. To enable students to visually detect vehicles as soon as possible when looking steadily toward them, students with central scotomas may benefit from learning to view with the most intact part of their vision (eccentric viewing using peripheral vision). Students with severely restricted visual fields may benefit from addressing glare and lighting issues

Dona Sauerburger, Eugene Bourquin

International Journal of Orientation & Mobility, Volume 11 , ISSUE 1, 35–40

Article

EXTREME GRADIENT BOOSTING METHOD IN THE PREDICTION OF COMPANY BANKRUPTCY

Machine learning methods are increasingly being used to predict company bankruptcy. Comparative studies carried out on selected methods to determine their suitability for predicting company bankruptcy have demonstrated high levels of prediction accuracy for the extreme gradient boosting method in this area. This method is resistant to outliers and relieves the researcher from the burden of having to provide missing data. The aim of this study is to assess how the elimination of outliers from

Barbara Pawełek

Statistics in Transition New Series, Volume 20 , ISSUE 2, 155–171

Research paper | 06-February-2018

Further pharmacological characterization of eltoprazine: focus on its anxiolytic, anorexic, and adverse-effect potential

from 1 mg/kg. At similar doses it also increased locomotion in the open field. However, eltoprazine failed to affect acquisition in context fear conditioning paradigm, which may indicate lack of its detrimental effect on learning at the doses tested (i.e., up to 5 mg/kg). In summary, effects of eltoprazine in different anxiety tests were equivocal while its effect on body weight seems robust and requires further investigation. It is to be determined whether these effects can be expected at the

Andreas Gravius, Andrzej Dekundy, Anita Vanaga, Lutz Franke, Wojciech Danysz

Acta Neurobiologiae Experimentalis, Volume 77 , ISSUE 1, 77–85

Research Article | 01-September-2017

DYNAMIC FACE RECOGNITION AND TRACKING SYSTEM USING MACHINE LEARNING IN MATLAB AND BIGDATA

are trained into the databases using machine learning algorithm. The tracking of individuals can be achieved by capturing their images while on the move and comparing them with the values stored in the databases. The detection of facial structure is done with Viola-Jones algorithm which though older is easy and efficient to use and Kanade-Lucas-Tomasi(KLT) algorithm is used for feature extraction . The HOG (Histogram of Oriented Gradients) features are extracted for training.

P.J Leo Evenss, Jennings Mcenroe .S, A.Prabhu Chakkaravarthy

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 163–173

Research Article | 06-July-2018

Students’ Perceptions of Learning, Post-school Options and Status in Two Elite Athlete Programmes

; learning, enjoyment, physical skill improvement and post-school options in the talent development environment. A small survey from a New Zealand pilot study on student participation was used for two purposefully selected case sites. Non-parametric statistical tests were used to test for differences within and between the two case sites. Results indicated that the talent development environment exerts a small effect on student athletes’ perceptions of physical skill improvement and that these

Seth Brown, Philippa Butler, Ra Jarden Osborne

Apex, Volume 18 , ISSUE 1, 59–74

Research Article | 15-February-2020

Novel Application of Kinect Sensor for Children to Learn Paleontological Environment

The authors are developing a simulation-based environmental learning support system using Kinect sensors. Obviously, it is impossible for learners to experience the actual paleontological environment, and it is therefore difficult for them to learn about the environments and lives. Then, we proposed an immersive animation display system using Kinect sensors and their human skeleton-tracking function. The system animates paleontological animals and their environment on the screen and displays

Tomohiro Nakayama, Takahiro Nakadai, Ryuichi Yoshida, Takeki Ogitsu, Hiroshi Takemura, Hiroshi Mizoguchi, Kaori Izuishi, Fusako Kusunoki, Keita Muratsu, Shigenori Inagaki

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 5, 1–4

Article | 01-March-2016

HIGH PRECISION TARGET LOCALIZATION METHOD BASED ON COMPENSATION OF ATTITUDE ANGLE ERRORS

The attitude angles of UAV, as the input parameters of the target localization process, influence the accuracy of geo-targeting. In order to improve the accuracy of target localization, this paper compensates the attitude angle errors of the UAV based on learning prediction compensation. Firstly, considering the airborne equipment and the metadata provided by the UAV, we combine rear intersection with GPS/INS to calculate the error of each platform and aircraft attitude angle. Then the error

Jialiang LIU, Wenrui Ding, Hongguang Li

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 1, 169–190

Review | 06-August-2019

MULTI-VARIABLE OPTIMIZATION MODELS FOR BUILDING ENVELOPE DESIGN USING ENERGYPLUS SIMULATION AND METAHEURISTIC ALGORITHMS

the authors. The multi-objective design optimization model to minimize life cycle cost and life cycle emission, and maximize occupant satisfaction level in a typical commercial building was developed. 3. METHOD Multi-variable optimizations by coupling the building performance simulation program with optimization environment using genetic algorithms (GA) or particle swarm optimizer (PSO) or teaching-learning-based optimization (TLBO) were performed to determine the best path to minimize life

Krzysztof GRYGIEREK, Joanna FERDYN-GRYGIEREK

Architecture, Civil Engineering, Environment, Volume 12 , ISSUE 2, 81–90

Research Article | 01-December-2017

Dwipa Ontology III: Implementation of Ontology Method Enrichment on Tourism Domain

This article summarizes some research results related to ontology enrichment specific to tourism domains from 2014 to 2017. Currently, some ontology enrichment approaches can use learning machinery such as support vector machine (SVM), Conditional Random Field (CRF) and kNN. Several studies have also been successful in evaluating ontology enrichment results with several parameters such as precision, recall and F-Measure. In addition, our research can enrich Dwipa Ontology II which has been

Guson Prasamuarso Kuntarto, Irwan Prasetya Gunawan, Fahmi L. Moechtar, Yudhiansyah Ahmadin, Berkah I. Santoso

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 4, 903–919

Research Article | 06-July-2018

Real Engagement in Active Problem Solving (REAPS): An evidence-based model that meets content, process, product, and learning environment principles recommended for gifted students

In this article, we begin with a short discussion of teaching and learning models, then describe what we believe is an exciting new model that can be used effectively in the teaching of gifted students. The main focus of this article is on the evidence showing that it is comprehensive (i.e., it is a way to implement all the curriculum principles important in teaching gifted students), flexible (i.e., can be used with a variety of ages of students, in a variety of settings, in many cultural

June Maker, Robert Zimmerman, Abdulnasser Alhusaini, Randal Pease

Apex, Volume 19 , ISSUE 1, 7–30

research-article | 30-November-2019

Embarked on social processes (the rivers) in dynamic and multilevel networks (the boats)

Embarked on social processes in the organizational society The main social processes in which sociology has been interested since the nineteenth century are solidarity and exclusion; deviance, control and conflict resolution; regulation and institutionalization; and learning and socialization. To say that these processes are social is to say that much of their deployment is always problematic and beyond our individual control. Even when we can influence one of their episodes or components, we

Emmanuel Lazega

Connections, Volume 40 , ISSUE 1, 60–76

Research paper | 01-August-2017

Spatial memory formation differentially affects c-Fos expression in retrosplenial areas during place avoidance training in rats

as the experimental rats either without (Control-noUS) or with shocks (Control-US) that were delivered in a random, noncontingent manner for three days. On the first day of place avoidance learning, the experimental group exhibited c-Fos induction in area 29c, similar to both control groups. In area 30, similarly high levels of c-Fos expression were observed in the experimental and Control-US groups. On the third day of training, when the experimental group efficiently avoided c-Fos expression in

Monika Malinowska, Monika Niewiadomska, Malgorzata Wesierska

Acta Neurobiologiae Experimentalis, Volume 76 , ISSUE 3, 244–256

Article | 13-July-2020

Research on the Application of Convolutional Neural Networks in the Image Recognition

I. INTRODUCTION Since the concept of deep learning was proposed by Hinton et al[1]. In 2006, during more than a decade of development, machine learning is closer to the original goal of “artificial intelligence”. Deep learning is a hierarchical machine learning approach that involves multiple levels of nonlinear transformations that learn the inherent laws and representation levels of sample data, and the feature information obtained in the process of learning can help the machine achieve

Gao Zhiyu, Liu Bailin, Gu Hongxian, Mu Jing

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 2, 31–38

rapid-communication | 31-March-2020

Internet-based digital video atlas of sonographic findings for clinical and educational purposes

sufficient level of patient compliance. Many questions can only be answered if the examination is afforded sufficient time and diligence. The US examination technique can be learned in US training courses, which are available in several books, online courses, and in traditional courses as classroom teaching, too. This is a prerequisite for a successful US examination. Learning US technique is also increasingly important in preclinical education(1,2). For localized questions, it has been demonstrated that

Daniel Merkel, Christoph Schneider, Michael Ludwig

Journal of Ultrasonography, Volume 20 , ISSUE 80, e24–e28

Research paper | 06-February-2018

Potential role of dopamine transporter in behavioral flexibility

Behavioral flexibility is subserved by the prefrontal cortex and the basal ganglia. Orbitofrontal cortex (OFC) and dorsomedial striatum (DMS) form a functional frontocorticostriatal circuit crucial for the mediation of flexibility during reversal learning via dopamine (DA) neurotransmission. The regulatory control in maintaining DA homeostasis and function is provided by the dopamine transporter (DAT), which therefore likely plays a significant role in controlling the influence of DA on

Anita Cybulska-Klosowicz, Julia Dabrowska, Sebastian Niedzielec, Renata Zakrzewska, Aleksandra Rozycka

Acta Neurobiologiae Experimentalis, Volume 77 , ISSUE 2, 176–189

research-article | 26-March-2021

Aminoguanidine ameliorates ovariectomy-induced neuronal deficits in rats by inhibiting AGE-mediated Aβ production

INTRODUCTION In 2019 Alzheimer’s disease International (ADI) estimates that there are more than 50 million people are suffering from dementia globally, and the number is predicted soar to 152 million by 2050 (Alzheimer’s Disease International, 2019). Increasing evidence has indicated that the oestrogen decline after menopause may influence learning and cognitive function, thus increasing the risk of Alzheimer’s disease (AD) (Fukuzaki et al., 2008). So far, the characteristic pathogenesis of AD

Dan Di Zhang, Yan Gang Wang, Chun Yan Liu, Ze Hou Wang, Yue Fen Wang

Acta Neurobiologiae Experimentalis, Volume 81 , ISSUE 1, 10–20

Article | 16-April-2018

The Missing Link: A Collaborative Approach to Early Childhood Orientation and Mobility

The current role of the Orientation & Mobility (O&M) instructor routinely involves working with young children (birth to 6 years). The inclusion of this population to the caseload of O&M instructors brings with it unique challenges. Young children’s primary means of learning comes in the form of play, yet O&M traditionally tends to focus on skill specific instruction. For young children who are blind or vision impaired the ability to move out into space independently and

Kylie Wells, Dip. Tchg., Grad. Cert. Ed. Studies, M. Spec. Ed.

International Journal of Orientation & Mobility, Volume 1 , ISSUE 1, 57–61

Research Article | 01-September-2017

UNSUPERVISED LEARNING FOR RIPENESS ESTIMATION FROM GRAPE SEEDS IMAGES

S. Hernández, L. Morales, A. Urrutia

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 3, 594–612

Research paper | 04-May-2018

Effects of different delayed exercise regimens on cognitive performance in fimbria-fornix transected rats

Studies have shown that exercise can positively influence cognitive performance after brain injury. This study investigated the effects of different exercise regimens on allocentric place learning after fimbria-fornix (FF) transection. One hundred and sixteen pre-shaped rats were subjected either to a mechanical transection of the FF or control sham surgery and divided into following groups: i) no exercise (NE), ii) voluntary exercise in a running wheel (RW), iii) forced swimming exercise

Elise Wogensen, Linda Marschner, Marie Gajhede Gram, Siri Mehlsen, Valdemar H. B. Uhre, Pernille Bülow, Jesper Mogensen, Hana Malá

Acta Neurobiologiae Experimentalis, Volume 77 , ISSUE 4, 323–336

Research Article | 06-July-2018

The Forgotten Children

This article provides a description of the author’s learning journey as she makes the commitment to provide for gifted children at the early childhood education service in which she works. The author examines research which highlights the reasons for identifying young gifted children. She includes issues that teachers may be experiencing which impact on the identification of gifted young children not being included in daily practice. Possible solutions are given as suggestions to overcome

Lynette Radue

Apex, Volume 15 , ISSUE 1, 45–55

Research Article | 06-July-2018

See the world through my eyes: Looking into how we can improve provision for gifted visual-spatial learners in our classrooms.

classroom learning. Consequent areas of challenge within traditional academic domains, combined with their exceptional ability being rarely recognised or valued in schools, contribute to gifted visual-spatial learners being an “invisible group” (Gohm, Humphreys & Yao, 1998; Lubinski & Kell, 2013; Mahoney & Seeley, 1982; Seeley, 1987, 2003; Silverman, 1998; von Karolyi, 2013). These findings led to the development of a primary research aim to describe these differences and explore

Sharon Mansfield

Apex, Volume 19 , ISSUE 1, 77–90

Article | 12-April-2018

Learning Better Classification-based Reordering Model for Phrase-based Translation

Li Fuxue, Xiao Tong, Zhu Jingbo

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 145–152

Editorial | 29-June-2020

Survey-Based Learning of Interns in Orientation and Mobility Program

Introduction In medieval times, experiential learning existed in the form of apprenticeship programs (Hindman, 2009). Today experiential learning which includes internships, applied practicums, and academic service learning has emerged as a bridge between school curricula and occupational settings (Miller, 1982). Internships, for example, provide university students opportunities to apply the knowledge, skills, and abilities that they will need in future employment. They also allow students to

Nora Griffin-Shirley, Jaehoon Lee, The Nguyen, Vitalis Othuon, Anita Page

International Journal of Orientation & Mobility, Volume 11 , ISSUE 1, 1–6

Research Article | 08-February-2019

STUDENTS’ ASSESMENT OF ENVIRONMENTAL CONDITIONS IN UNIVERSITY BUILDINGS – THE RESEARCH REPORT

qualitatively with the use of behavioural mapping and space syntax analysis. The research results indicated students’ behavioral and emotional engagement with the places of study, their assessment of the functional performance of these facilities and proposals for improvement of the existing environment (in particular the creation of individual learning space and the “student space” in general), as well as the emotionally-charged and personalized image of individual buildings. Theoretical introduction into

Angelika LASIEWICZ-SYCH

Architecture, Civil Engineering, Environment, Volume 11 , ISSUE 4, 41–53

Article | 07-May-2018

Design of University Resource Website and Security Measures in IPV6

In this paper authors introduced the overall design of learning resource sharing platform in the pure IPv6 environment, including the client and the web server and the back-end database, and the user management, the detailed design of the three aspects of resource management platform and administrator management. Finally authors introduced application of decision tree in this website.

Chunmei Li, Peng Cui, Xinke Zhou, Ze Xiao

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 1, 54–57

Research paper | 31-October-2017

COMPUTERISED RECOMMENDATIONS ON E-TRANSACTION FINALISATION BY MEANS OF MACHINE LEARNING

Germanas Budnikas

Statistics in Transition New Series, Volume 16 , ISSUE 2, 309–322

Article | 16-April-2018

Whose Learning is it? Fostering Student Ownership in Orientation & Mobility

Fabiana Perla, Ed.D., COMS.

International Journal of Orientation & Mobility, Volume 5 , ISSUE 1, 28–33

Research paper | 18-May-2018

Long-term behavioral, histological, biochemical and hematological evaluations of amyloid beta-induced Alzheimer’s disease in rat

(surgery without injection Aβ), and experimental group (two-sided intrahippocampal amyloid-beta injection into hippocampus). From each group, three animals were investigated 42 days after injection, and the remaining four animals were studied after one year. All animals were tested for learning abilities and memory. Finally, samples from blood, brain, heart, kidney, liver, colon and spleen were examined. In the experimental group, the size of amyloid plaques were increased significantly after one year

Raheleh Kheirbakhsh, Mahnaz Haddadi, Ahad Muhammadnejad, Alireza Abdollahi, Farshad Shahi, Behzad Amanpour-Gharaei, Azadeh Abrahim-Habibi, Tahereh Barati, Saeid Amanpour

Acta Neurobiologiae Experimentalis, Volume 78 , ISSUE 1, 51–59

research-article | 30-November-2018

Stimulus-seeking in rats is accompanied by increased c-Fos expression in hippocampal CA1 as well as short 22 kHz and flat 50 kHz calls

., 2007). In our experiments, we explored the self-exposure paradigm, a remarkably simple and unique – though recently disregarded – model to investigate emotionality, motivation, and learning in rats. We showed that the ability to control experimental conditions increased the reaction ratio, since the rats, when allowed to turn off the light with a nose-poke, performed more nose-pokes than during the previous session as well as more often than the control animals. The observed goal-directed

Ita Robakiewicz, Monika Polak, Małgorzata Rawska, Dominik Alberski, Rafał Polowy, Kinga Wytrychiewicz, Mateusz Syperek, Jan Matysiak, Robert K. Filipkowski

Acta Neurobiologiae Experimentalis, Volume 79 , ISSUE 3, 310–318

Research Article | 15-February-2020

A Proposal for Classification of Multisensor Time Series Data based on Time Delay Embedding

Multisensor time series data is common in many applications of process industry, medical and health care, biometrics etc.Analysis of multisensor time series data requires analysis of multidimensional time series(MTS) which is challenging as they constitute a huge volume of data of dynamic nature. Traditional machine learning algorithms for classification and clustering developed for static data can not be applied directly to MTS data. Various techniques have been developed to represent MTS data

Basabi Chakraborty

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 5, 1–5

research-article | 11-October-2021

Social-cognition and dog-human interactions: Is there potential for therapeutic-interventions for the disability sector?

, 2004; Shepherd, 2010). Social-skills are developed throughout life through social-interactions (Hogg & Vaughan, 2014), to acquire what has been called by Adolphs (1999; 2001; 2003) a “social brain”. Developing a “social brain” requires understanding the actions of others, predicting their intentions, known as Theory of Mind (ToM), and as a consequence, learning the socially acceptable/unacceptable rules (Csibra & Gergely, 2006). A lack or delay in the development of social skills is associated with

M. Bellio, S. Silveira

International Journal of Orientation & Mobility, Volume 12 , ISSUE 1, 1–14

Book Review | 16-April-2018

The Multisensory Handbook: A Guide for Children and Adults with Sensory Learning Disabilities

Kim T. Zebehazy, Ph.D., COMS, CLVT, TSVI.

International Journal of Orientation & Mobility, Volume 5 , ISSUE 1, 53–55

Book Review | 16-April-2018

The Multisensory Handbook: A Guide for Children and Adults with Sensory Learning Disabilities

Rachel Morgan, B.A., Grad. Dip. O&M, M. Teaching (Primary), Dip. Management

International Journal of Orientation & Mobility, Volume 5 , ISSUE 1, 56–58

research-article | 30-November-2019

A review of privacy-preserving human and human activity recognition

As more and more data is collected and the technology to process it develops, the importance of data is growing. In addition, technology is needed for sensitive data processing to protect privacy. All processes that process data, such as raw data, data being processed, and result data, require privacy. The general approaches to prevent privacy leakage adopted anonymity, access control, and transparency (Haris et al., 2014). With the introduction of machine learning (ML), big data processing is

Im Y. Jung

International Journal on Smart Sensing and Intelligent Systems, Volume 13 , ISSUE 1, 1–13

Article | 02-April-2019

Dispositions of a responsible early childhood education leader: Voices from the field

Gwen Davitt, Debbie Ryder

Journal of Educational Leadership, Policy and Practice, Volume 33 , ISSUE 1, 18–31

Article | 09-June-2019

Social justice and curriculum integration in a New Zealand primary school:  A foundation principal’s view

Barbara Fogarty-Perry

Journal of Educational Leadership, Policy and Practice, Volume 32 , ISSUE 1, 39–47

Article | 30-November-2018

Traveling Route Generation Algorithm Based On LDA and Collaborative Filtering

can’t generate a new route that meets the user’s needs. At the same time, through the learning and researching for collaborative filtering and LDA algorithm, it is found that these algorithms are feasible and applied in this paper. According to that, we will show the method of recommendation and generation of tourist routes based on LDA and collaborative filtering below. II. RELATED WORK The planning of a travel route is a complex and comprehensive process that requires consideration of many

Peng Cui, Yuming Wang, Chunmei Li

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 4, 47–62

Article | 20-December-2020

Modelling bid-ask spread conditional distributions using hierarchical correlation reconstruction

Jarosław Duda, Henryk Gurgul, Robert Syrek

Statistics in Transition New Series, Volume 21 , ISSUE 5, 99–118

Article | 30-November-2020

Motion Blur Image Restoration by Multi-Scale Residual Neural Network

prior, which can save the memory of potential image edge information and iterative support detection algorithm, which can strengthen the correct preservation of the space constraint kernel. parameter.In the study of unblind deblurring, Sun et al. [10] is a method based on deep learning to estimate uneven motion blur. First, CNN is used to predict the probability of different motion kernels for each image patch, and then image rotation is used. The technology expands the candidate motion kernel set

Xu Hexin, Zhao Li, Jiao Yan

International Journal of Advanced Network, Monitoring and Controls, Volume 6 , ISSUE 1, 57–67

research-article | 31-July-2018

Virtual O&M: A far north queensland innovation

Transition to high school, though generally a positive experience, can be a tumultuous experience for many teenagers. According to Suldo and Shaunessy-Dedrick (2013, p. 195), high school incorporates “more difficult coursework, different organizational structures, new peers, more students, and different expectations from teachers”. In addition, for students with vision impairment (SVI) navigating an unfamiliar environment can present significant difficulties. For some SVI, learning about and

Katrina Blake, Helen Kinnane, Melinda Whipp

International Journal of Orientation & Mobility, Volume 9 , ISSUE 1, 1–4

Article | 16-April-2018

Student Portfolios in O&M: A window into the child’s learning experience

Fabiana Perla, Ed.D. COMS, CLVT, Jamie Maffit, M.S., COMS, CLVT

International Journal of Orientation & Mobility, Volume 7 , ISSUE 1, 44–51

No Record Found..
Page Actions