Miracle-dz/UniFAR-FTUs huggingface dataset:
IOT Based Audio Video Surveillance

: Fast paced technological growth in the field of IoT has made surveillance a very promising application area. With great extent of smartness over the things that are controlled by internet security is one of the applications that everyone needs to be controlled remotely. This paper presents an IoT application for live video and audio streaming that can be used for surveillance from anywhere and at anytime. This system provides the IP address based live streaming using a Raspberry Pi module with Fast forward moving picture expert group (FFMPEG). A MIC and loud speaker for audio connectivity is also provided in addition to a USB Camera for video connectivity.
Latency-Adjustable Cloud/Fog Computing Architecture for Time-Sensitive Environmental Monitoring in Olive Groves

The emerging and vast adoption of the Internet of Things (IoT) has sprung a plethora of research works regarding the potential benefits in smart agriculture. A popular implementation involves the deployment of Wireless Sensor Networks (WSNs), which embed low energy consumption sensory nodes to capture the critical environmental parameters prevailing on the farms. However, to manage the ever-increasing volumes of raw data successfully, new approaches must be explored. Under this scope, current work reports on the design and development of an IoT system, having in mind the case of olive groves, which are considered the dominant sector for agricultural activity in the Mediterranean Basin. The system incorporates the cloud/fog computing paradigm to equip the olive growers with a low-cost solution for accurate, reliable, and almost real-time monitoring of their crops. Its core is based on a three-layered network architecture, capable of dynamically balancing the generated load, by pushing cloud-elastic resources to the underlying fog network. As such, the premise of the approach lies in the conforming character of the system that allows for targeted alterations to its operational functionality to meet stringent latency and traffic load environmental monitoring constraints. To evaluate the performance of the proposed architecture, a demo prototype is developed and deployed in the facilities of the Ionian University. Experimental results illustrate the efficiency, flexibility, and scalability of the approach in terms of latency, achieving response time reduction across all platforms, a subject of the utmost importance when it comes to precision agriculture of the future. Moreover, it is shown that the system is capable of dynamic functionality adaptation, to meet network traffic load constraints, achieving high throughput (on average 95%) and addressing potential environmental dangers to olive oil production.
University Teachers' Pedagogical Practices in Using Technology-Enhanced Learning: strategies to integrate haptic technologies into undergraduate teaching.

Previous research into the uptake of ICT by teachers in schools has shown that there is often a tension between teachers’ traditional practices and the approaches to incorporating new technologies (TEL) within a conventional course (Webb and Cox, 2004). In higher education, the adoption of TEL is often even more constrained because of the requirements to cover many degree topics, teach large student cohorts, meet strict deadlines and for university teachers to keep up with their research as well as teaching commitments. Although there have been many initiatives in HE to adopt TEL since the mid 1970s and to research its effects on the HE curriculum, (e.g. Cox and Lewis, 1978, Laurillard, 1993, Reynolds et al., 2007) there have been relatively few which have focused on the impact on the curriculum delivery itself, its impact on university teachers’ practices and how these interrelate with the technology development, the research methods and theories used. The purpose of the curriculum strand of the hapTEl project, funded by the ESRC/EPSRC’s Teaching and Learning Research Programme’s Technology Enhanced Learning Phase (see http://www.tlrp.org/tel/), involves developing and refining the dental curriculum and associated teaching strategies through a blended learning approach and identifying the pedagogies and pedagogical strategies which can incorporate TEL methods into undergraduate and post-graduate programmes in Dentistry. This paper reports on the results of the first main phase of the project and how the pedagogical strategies and attitudes of the clinical teachers have influenced the methods in which TEL (haptics) is used and the conventional teaching is adapted.
Inflammation Promotes Pneumococcal Colonization of the Respiratory Tract

Inflammation is a critical host response to a range of potentially harmful stimuli, but it must be tightly controlled in the respiratory tract to maintain the gas-exchange function of the lungs. Mucosal inflammation in the upper respiratory tract, however, is a common response to multiple types of microbial exposures. Some pathogenic bacteria, such as Streptococcus pneumoniae (the pneumococcus), can colonize and persist in the face of these host responses, and can even promote inflammation, raising the question of whether pneumococci evolved to take advantage of inflammation. Here, we examined the hypothesis that airway inflammation promotes pneumococcal colonization, specifically by accelerating bacterial growth, delaying pneumococcal clearance and enhancing bacterial transmission. To study how inflammation promotes bacterial growth, we developed a novel flow cytometric assay using fluorescence dilution to measure the replication of individual bacteria in vivo. Using a mouse model of influenza-pneumococcal coinfection, we found that the host response to influenza infection includes secretion of mucins, which are heavily decorated with sialic acid, onto the mucosal surface. Pneumococci that could catabolize sialic acid were able to exploit this inflammatory response, as seen by increased bacterial density in the airway and accelerated bacterial replication. Next, we examined whether overly exuberant inflammation altered pneumococcal colonization. We found that infant mice tonically expressed high levels of monocyte chemoattractants in the upper respiratory tract, and could not appropriately upregulate these chemokines during colonization. Infants were unable to recruit monocytes, which differentiate into macrophages, the effector cells of clearance, into the nasopharynx, and therefore could not clear carriage as quickly as adult mice. Ectopic overexpression of one such chemokine, CCL2, rescued the infant defects in macrophage trafficking and pneumococcal clearance. Finally, we studied bacterial transmission in the presence of influenza-mediated inflammation in infant mice. Transmission required influenza infection, and was increased in the absence of certain host signals that redirected the inflammatory response. Together, these data demonstrated that inflammation alters three key aspects of pneumococcal biology: early growth to establish colonization, immune evasion to avoid clearance and transmission. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Cell & Molecular Biology First Advisor Jeffrey N. Weiser
Effects of core strengthening exercises on dynamic balance and gait speed in stroke survivors

Independent ambulation is the ultimate goal of post-stroke rehabilitation, of which dynamic balance is a primary requirement. Core stability is said to be essential to balance and independent ambulation, however, core strengthening exercises have often been omitted in stroke rehabilitation. The study sought to determine the effects of core strengthening exercises on dynamic balance and gait speed in stroke survivors. A total of 48 stroke survivors participated in this study. A simple random sampling in which participants were consecutively allocated into experimental and control groups was employed. The experimental group received core strengthening exercise in addition to conventional exercise while the control group had conventional exercise only. Dynamic balance was measured by maximum reach distances and gait speed was evaluated using 10-mteres walk test. Assessment of dynamic balance and gait speed was performed before treatment and six weeks after. There was no significant difference in dynamic balance and gait speed between both groups (P>0.05 in each). Significant differences in dynamic balance measures and gait speed were found between pre-test and post-test values of each of experimental and control groups (p<0.05). A holistic approach targeting all the core muscle groups and their corresponding motions should be adopted when executing core strengthening exercise. Keywords: Stroke, Core strengthening, Exercise, Dynamic balance, Gait
A New formulation and Resolution Schemes for Planning Collaborative Human-robot Tasks. (Une formulation nouvelle et des Schemas de Resolution pour la planification de taches collaboratives homme-robot)

When interacting with humans, robotic systems shall behave in compliance to some of our socio-cultural rules, and every component of the robot have to take them into account. When deciding an action to perform and how to perform it, the system then needs to communicate pertinent contextual information to its components so they can plan respecting these rules. It is also essential for such robot to ensure a smooth coordination with its human partners. We humans use many cues for synchronization like gaze, legible motions or speech. We are good at inferring what actions are available to our partner, helping us to get an idea of what others are going to do (or what they should do) to better plan for our own actions. Enabling the robot with such capacities is key in the domain of human-robot interaction.
Fine-Grained Frequency Reuse in Centralized Small Cell Networks

Interference management for Small Cell (SC) networks has drawn great attention from both academia and industry due to its importance in Long-Term Evolution (LTE) and emerging 5G networks. Although various approaches have been proposed in the literature, many of them face practical limitations such as showing gains only in specific scenarios, relying on ideal fronthaul, or becoming computationally intractable as the network size increases. In this paper, a novel framework is proposed for interference management in centralized SC networks by jointly utilizing graph theory and optimization theory. It extends the classic center-edge frequency reuse schemes into a more fine-grained scale, thus capturing the complex interference relationships in SC networks. The cell-level resource partition can be semi-statically updated according to the traffic dynamics while existing Medium Access Control (MAC) schedulers can be used for subframe-level resource allocation, not requiring fiber fronthaul. LTE system-level simulation results show that the proposed scheme can significantly improve both cell edge and mean user throughput with practical complexity.
Algorithms in the Real World

A (n, k, n-k+1) code: Consider the polynomial of degree k-1 p(x) = ak-1 xk-1 + L + a1 x + a0 Message: (ak-1, ., a1, a0) Codeword: (p(y0),p(y1), . , p(yn-1)) for distinct y0,. ,yn-1 To keep the p(yi) fixed size, we use yi, ai ∈ GF(pr) To make the yi distinct, n < pr Unisolvence Theorem: Any subset of size k of (p(y1), p(y2), . , p(yn)) is enough to (uniquely) reconstruct p(x) using polynomial interpolation, e.g., LaGrange’s Formula.
Posttraumatic Stress and Hazardous Alcohol Use in College Students: The Moderating Role of Alcohol Protective Behavioral Strategies

ii ACKNOWLEDGMENTS . iii DEDICATION . iv LIST OF TABLES . vii CHAPTER I INTRODUCTION . 1 Mental Health and Harmful Alcohol Use in College Students . 2 Traumatic Stress and Harmful Alcohol Use . 4 Protective Behavioral Strategies . 5 Mental Health and Al-PBS . 9 Present Study . 11 CHAPTER II METHOD . 16 Participants and Procedures . 16 Instruments . 17 Demographics . 17 Posttraumatic Stress Disorder Checklist (PCL-5). 17 Protective Behavioral Strategies Scale-20 (PBSS-20) . 18 Alcohol Use Disorders Identification Test-United States-C (AUDIT-US-C) . 19 Brief Young Adult Alcohol Consequences Questionnaire (BYAACQ). 20 CHAPTER III RESULTS . 21 vi Hazardous Drinking . 22 Alcohol-Related Negative Consequences . 27 CHAPTER IV – DISCUSSION. 30 APPENDIX A – Electronic Informed Consent . 38 APPENDIX B Demographics . 40 APPENDIX C Posttraumatic Stress Disorder Checklist (PCL-5) . 41 APPENDIX D Protective Behavioral Strategies Scale – 20 (PBSS-20). 42 APPENDIX E Alcohol Use Disorders Identification Test – United States – Consumption (AUDIT-US-C) . 43 APPENDIX F Brief Young Adult Alcohol Consequences Questionnaire (BYAACQ) . 44 APPENDIX G – IRB Approval Letter . 45 REFERENCES . 46
HDR Image Tone Mapping Histogram Adjustment with Using An Optimized Contrast Parameter

This paper proposes a Tone Mapping (TM) approach converting a High Dynamic Range (HDR) image into a Low Dynamic Range (LDR) image while preserving as much information of the HDR image as possible to ensure a good LDR image visual quality. Multiresolution approach with approximation and details are separated, and weighted by entropy, and used an optimized contrast parameter. The parameter relies on all accounts of luminance average themselves in order to enhance contrast as much as possible. Then, the pixel's distribution of the coarse reconstructed LDR image is then adjusted according to a perceptual quantizer with respect to the human visual system using a piecewise linear function. Simulation results provide good results, both in terms of visual quality and TMQI metric, compared to existing competitive TM approaches.
Smartphone-Based Activity Recognition Model (SBARM)

- This research aims to use context awareness data from Android mobile devices in activity recognition. This paper presents about a smart phone-based activity recognition model which can automatically record people’s daily activities. The capability to recognize human activities is useful in different sectors such as healthcare, eldercare, target advertising and in many research platforms. Great deal of researches has been carried out in activity recognition using wearable sensors and mobile devices. But wearing sensors on human body can bring inconvenience and discomfort to the user. To avoid this mobile device can be used as an unobtrusive device in activity recognition. Even there has been several researches done using mobile devices, relatively little practical work has been in the area of applications. With this motivation, this project investigates the ability to recognize activities of a smart phone user such as Idling or phone-not-on-person, walking, running, jogging, climbing up stairs, climbing down stairs, travelling or driving and shopping through a smart phone. The data collection of this research has been carried out using the smart phone sensors over a period of 4s time window. Due to the limited memory availability of the smart phone, the collected data was sent to the server which provides the storage and processing. Then it has been pre-processed in order to eliminate noise and redundancy of data and the time domain features Mean, Variance and Standard deviation were extracted. Then the data is split into training set and test set. The training set is used to train the activity recognition algorithm and the test set is used to evaluate the recognition algorithm after training. The extracted features are the input data needed for the Hidden Markov Models (HMM) which is used in order to construct the activity recognition model. The recognized activities can be viewed in android dashboard application integrated with any applications.
Block Form Of Kalman Filter In Processing Images With Low Resolution

The article discusses the issues of preliminary processing and image filtering. One of the problems with image preprocessing is the presence of blurring and noise. The problem of highlighting the background of a moving object. Next, consider the problem of constructing a Kalman filter of block type. When using the Kalman filter to solve the adaptive filtering problem, the monitored process is the vector of optimal filter coefficients. The purpose of applying the Kalman filter is to minimize the variance of the estimate of the vector random process. Noise filtering in the form of a block filter allows to restore damaged areas of images using relative shift
A hybrid Feature Selection Approach for Arabic Handwritten Text Based on Genetic Algorithm and Support Vector Machine

Reducing features dimensionality in Arabic handwritten text recognition is a crucial issue, due to its impact on the overall recognition performance. In this paper, an Arabic handwritten text recognition model based on a hybrid feature-selection approach and Artificial Neural Network (ANN) classifier is proposed. The proposed feature selection approach mainly based on Genetic Algorithm (GA) and Support Vector Machine (SVM). By doing so, we aim to reduce the dimensionality of Arabic handwritten text features and optimize the recognition overall performances. The proposed based on GA-SVM approach was tested using the IFN/ENIT dataset. The results of the proposed features-selection are promising; since they reduce the number of tested features up to 78% by removing the irrelevant and redundant features. Using the ANN classifier, the proposed model reaches a 96.5% recognition rate, which supports its effectiveness in recognizing Arabic handwritten texts.
The Effect of Poor Maternal Nutrition on the Growth and Development of Offspring

Poor maternal nutrition can have long lasting detrimental effects on offspring growth and development. Specifically, these offspring will exhibit increased carcass adiposity, reduced muscularity and altered growth rates resulting in animals that are less productive and yield a less desirable product for consumers. However, the mechanisms by which poor maternal nutrition alters offspring growth and development are not well understood. We hypothesized that maternal underand over-nutrition will alter the expression of key genes and novel pathways involved in the development of muscle and adipose tissue of lambs at two early postnatal time points. To evaluate these hypotheses, pregnant sheep were fed 100 % [control (CON)], 60 % [restricted (RES)] or 140 % [over-fed (OVER)] of National Research Council requirements based on total digestible nutrients. One lamb from each ewe was necropsied either within 24 hour of birth or 3 months of age. RNA was isolated from adipose and muscle tissue respectively and gene expression quantified using real time RT-PCR. Alternately, transcriptome analysis was performed on isolated RNA using the Ion Torrent Proton sequencer and analyzed using the Cufflinks analysis package. Gene expression of insulin-like growth factor (IGF)-I was increased in the quadriceps muscle tissue of RES lambs at 1 day of age. Expression of β-Catenin, a factor involved in WNT signaling, was greater in the quadriceps muscle tissue of RES and OVER at 1 day compared with CON (P = 0.07). At day 1, the semitendinosus muscle tissue of OVER lambs exhibited increased myostatin (MSTN;P = 0.06) and follistatin (FSTN; P = 0.04) gene expression. Expression of factors involved in the somatotropic axis, IGF-I and insulin-like growth factor binding protein (IGFBP)-3, were also altered in the semitendinosus muscle tissue of lambs born to RES and OVER ewes respectively (P ≤ 0.08). No change in the expression of factors involved in adipogenesis were observed at either time point. As determined by RNA-seq analysis performed on semitendinosus muscle tissue collected from lambs at birth, 35 differentially expressed genes were identified using the bovine reference annotation whereas mapping to the ovine reference yielded 10. The identified genes are involved in various processes including the regulation of metabolism, hypertrophy, nutrient uptake, and muscle protein turnover. In summary, poor maternal nutrition can alter muscle development through several potential mechanisms, including the somatotropic axis and wnt signaling. Additionally, these mechanisms affected by maternal nutrition vary between OVER vs CON and RES vs CON born lambs despite similar alterations to muscle phenotype. Future studies are needed to identify additional factors altered by maternal nutrition as well as determine the effects of poor maternal nutrition on epigenetic mechanisms in offspring.
The Effects of Exercise on Quality of Life and Function in Patients with Leukemia Currently Undergoing Treatment: A Systematic Review of the Literature

Background: Patients undergoing treatment for leukemia often have decreased quality of life and function due to a combination of treatment side effects and the course of the disease. Purpose: The purpose of this systematic review was to identify whether exercise can impact quality of life and function in patients with leukemia currently undergoing treatment. Methods: Twelve studies were identified, results reviewed, and assessed for quality of research. The databases that were searched were PubMed, CINAHL, Google scholar, and Medline. Five search terms were used, which included (1) “effects of exercise during leukemia treatment on QOL,” (2) “effects of exercise during leukemia treatment on function,” (3) “effects of exercise on leukemia patients AND QOL AND function,” (4) “exercise, leukemia, quality of life,” (5) “exercise, leukemia, function. ” Inclusion criteria included full text available, patients currently undergoing treatment, studies that looked at leukemia only, articles from 2003–2013, and studies where patients participated in exercise treatment. Exclusion criteria included duplicate articles, studies that looked at survivors, and those that were not applicable to research area. Results: Study designs ranged from single group pre‐ and posttests with no control group or randomization to randomized control trials. Patients varied in age from pediatrics to geriatrics and received various types of treatments for leukemia. Interventions varied across studies, and included aerobics, resistance, flexibility training, or a combination. Specific outcome measures varied, but all measured quality of life and/or function. The results showed statistically significant improvements or trends towards improvement with no adverse effects from the exercise programs. Conclusions: This systematic review provides evidence that exercise is beneficial in improving function and quality of life for patients undergoing treatment for leukemia.
Classification of Alzheimer’s Disease with Stacked Convolutional Autoencoder

In this paper, a stacked convolutional autoencoder model is proposed in order to classify Alzheimer’s disease with high accuracy in PET/CT images. The proposed model makes use of the latent space representation - which is also called the bottleneck, of the encoder-decoder architecture: The input image is sent through the pipeline and the encoder part, using stacked convolutional filters, extracts the most useful information. This information is in the bottleneck, which then uses Softmax classification operation to classify between Alzheimer’s disease, Mild Cognitive Impairment, and Normal Control. Using the data from Dong-A University, the model performs classification in detecting Alzheimer’s disease up to 98.54% accuracy.