Utility of Diffusion Modeling of Cogstate Brief Battery Test Performance in Detecting Mild Cognitive Impairment

Cognitive testing data are essential to the diagnosis of mild cognitive impairment (MCI), and computerized cognitive testing, such as the Cogstate Brief Battery, has proven helpful in efficiently identifying harbingers of dementia. This study provides a side-by-side comparison of traditional Cogstate outcomes and diffusion modeling of these outcomes in predicting MCI diagnosis. Participants included 257 older adults (160 = normal cognition; 97 = MCI). Results showed that both traditional Cogstate and diffusion modeling analyses predicted MCI diagnosis with acceptable accuracy. Cogstate measures of recognition learning and working memory accuracy and diffusion modeling variable of decision-making efficiency (drift rate) and nondecisional time were most predictive of MCI. While participants with normal cognition demonstrated a change in response caution (boundary separation) when transitioning tasks, participants with MCI did not evidence this change.

Mobile Robot Obstacle Avoidance Based on Neural Network with a Standardization Technique

Reactive algorithm in an unknown environment is very useful to deal with dynamic obstacles that may change unexpectantly and quickly because the workspace is dynamic in real-life applications, and this work is focusing on the dynamic and unknown environment by online updating data in each step toward a specific goal; sensing and avoiding the obstacles coming across its way toward the target by training to take the corrective action for every possible offset is one of the most challenging problems in the field of robotics. This problem is solved by proposing an Artificial Intelligence System (AIS), which works on the behaviour of Intelligent Autonomous Vehicles (IAVs) like humans in recognition, learning, decision making, and action. First, the use of the AIS and some navigation methods based on Artificial Neural Networks (ANNs) to training datasets provided high Mean Square Error (MSE) from training on MATLAB Simulink tool. Standardization techniques were used to improve the performance of results from the training network on MATLAB Simulink. When it comes to knowledge-based systems, ANNs can be well adapted in an appropriate form. The adaption is related to the learning capacity since the network can consider and respond to new constraints and data related to the external environment.

Reward Management Strategies and Employee Satisfaction in the Colleges of Kathmandu Valley

Background: Educational institutions set up a reward management system with the hope that it makes the employees perform their activities to the satisfaction of all concerned stakeholders. However, there are many contradictions and complaints about the performance of employees in colleges, compelling the undertaking the studies. Objectives: This study aims to examine the impact of reward management strategies on employee satisfaction in colleges of Kathmandu valley. Methods: This paper uses a questionnaire survey method of 300 respondentsof different 30 colleges/campuses of Kathmandu valley and descriptive statistics and multiple regression models are used to analyze the data. Results: The beta coefficients are positive and significant for promotion, compensation, recognition, learning opportunities, and career development opportunity with employee satisfaction which indicates these variables have a positive impact on employee satisfaction. Conclusion: It is found that reward management is positively related to employee satisfaction and it is a powerful motivational factor that leads to job satisfaction. Implications: College management including universities may focus on identifying better reward management strategies to motivate the employees to enhance better productivity.

Reward Management Strategies and Employee Satisfaction in the Colleges of Kathmandu Valley

Background: Educational institutions set up a reward management system with the hope that it makes the employees perform their activities to the satisfaction of all concerned stakeholders. However, there are many contradictions and complaints about the performance of employees in colleges, compelling the undertaking the studies. Objectives: This study aims to examine the impact of reward management strategies on employee satisfaction in colleges of Kathmandu valley. Methods: This paper uses a questionnaire survey method of 300 respondents of different 30 colleges/campuses of Kathmandu valley and descriptive statistics and multiple regression models are used to analyze the data. Results: The beta coefficients are positive and significant for promotion, compensation, recognition, learning opportunities, and career development opportunity with employee satisfaction which indicates these variables have a positive impact on employee satisfaction. Conclusion: It is found that reward management is positively related to employee satisfaction and it is a powerful motivational factor that leads to job satisfaction. Implications: College management including universities may focus on identifying better reward management strategies to motivate the employees to enhance better productivity.

PENGEMBANGAN MEDIA PEMBELAJARAN UNTUK PENGENALAN HURUF PADA ANAK USIA DINI BERBASIS AUGMENTED REALITY

ABSTRAKPenelitian ini bertujuan untuk menghasilkan suatu produk berupa media pembelajaran pengenalan huruf berbasis Augmented Reality (AR) pada anak usia 4-5 tahun. Dikarenakan belum adanya media pembelajaran pengenalan huruf berbasis AR, yang mana pembelajaran tersebut dapat memfokuskan dalam pembelajaran pengenalan, pengejaan serta menirukan suara huruf pada media. Metode yang digunakan pada penelitian ini adalah metode penelitian R&D (Research and Development) dengan model pengembangan ADDIE. dengan lima tahap yaitu analisis, desain, pengembangan, implementasi dan evaluasi. Media pembelajaran berbasis Augmented Reality ini telah di validasi oleh beberapa pakar yaitu pakar media, pakar bahasa dan pakar materi. Hasil validasi oleh pakar media rata-rata sebesar 86% dengan kategori sangat valid, hasil validasi oleh pakar bahasa rata-rata sebesar 78% dengan kategori valid dan hasil validasi oleh pakar materi rata-rata sebesar 89% dengan kategori sangat valid. Selain divalidasi oleh beberapa ahli, media pembelajaran ini juga telah di uji coba kepada guru dan orangtua. Hasil uji coba terhadap guru TK Kartika X-12 sebesar 90,6% dengan kategori sangat valid dan orangtua dengan hasil rata-rata skala kecil dan skala besar sebesar 95,5% dengan kategori sangat valid. Dari hasil tersebut, maka dapat disimpulkan bahwa media pembelajaran pengenalan huruf pada anak usia 4-5 tahun berbasis Augmented Reality dapat dikategorikan valid dan layak digunakan serta bisa dikembangkan.Kata kunci: Augmented Reality, Media Pembelajaran, Pengenalan Huruf ABSTRACTThis study aims to produce a product in the form of Augmented Reality-based letter recognition learning media for children aged 4-5 years. Because there is no AR-based letter recognition learning media, which learning can focus on learning recognition, spelling and imitating the sound of letters on the media. This research method uses the R&D (Research and Development) research method with the ADDIE. This Augmented Reality-based learning media has been validated by several experts, namely media experts, linguists and material experts. The average validation result by media experts is 86% in the very valid category, the average validation result by linguists is 78% in the valid category and the validation results by material experts are on average 00% in the valid category. Besides being validated by several experts, this learning media has also been tested on teachers and parents. The test results on TK Kartika X-12 Kindergarten teachers were 90.6% with a very valid category and parents with an average result of a small scale and a large scale of 95.5% with a very valid category. From these results, it can be concluded that the learning media for recognizing letters in children aged 4-5 years based on Augmented Reality can be categorized as valid and feasible to use and can be developed.keywords: Augmented Reality, Learning Media, Letter Recognition

The mitochondrial Na+/Ca2+ exchanger, NCLX, mediates PDE2 dependent neuronal survival and learning

Impaired phosphodiesterase (PDE) function and mitochondrial Ca2+ - [Ca2+]m signaling leads to cardiac failure, ischemic damage and dysfunctional learning and memory. Yet, a causative link between these pathways is unknown. Here, we fluorescently monitored [Ca2+]m transients in hippocampal neurons evoked by caffeine followed by depolarization. [Ca2+]m efflux was apparent in WT but diminished in neurons deficient in the mitochondrial Na+/Ca2+ exchanger NCLX. Surprisingly, neuronal depolarization-induced Ca2+ transients alone failed to evoke strong [Ca2+]m efflux in WT neurons. Caffeine is also a PDE inhibitor. Pretreatment with the PDE2 inhibitor Bay 60-7550 rescued [Ca2+]m efflux triggered by neuronal depolarization. Inhibition of PDE2 acted by diminishing the Ca2+ dependent reduction of mitochondrial cAMP, thereby promoting NCLX phosphorylation. Selective PDE2 inhibition also enhanced [Ca2+]m efflux triggered by neuromodulators. We found that protection of neurons against excitotoxic insults, conferred by PDE2 inhibition, was diminished in NCLX KO neurons, thus is NCLX dependent. Finally, administration of Bay 60-7550 enhanced new object recognition learning in WT but not in NCLX KO mice. Our results identify a long-sought link between PDE and [Ca2+]m signaling thereby providing new therapeutic targets.

ANDROID-BASED APPLICATIONS FOR CHILDREN'S LEAF RECOGNITION LEARNING

Indosesia is a country with abundant natural wealth. Almost all types of plants can be grown in the territory of Indonesia. Most have been used in the past to treat various diseases. Therefore, the author wants to design and build a leaf recognition learning application in android-based children that aims to make the younger generation know the diversity of plant leaves in the surrounding environment, in order to make the younger generation understand the need to care for and maintain the natural environment and knowledge about plants that are very important for human life, especially for human health, among others, traditional medicine that is now beginning to fade. This application has ease of use because it has an easy to understand design and a menu that is easy to understand by all people in accessing this application. In this study the author used waterfall method as the process or flow of the research to be done. The test results of the application that has been created get the result that all features and functions of the system can run according to what has been designed. In addition, the author also conducted tests using the UAT method to get a result of a percentage value of 96% so that it can be concluded that this application can be accepted by users.