Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching and Learning in the Digital Age

Throughout history, each new advance in communication technology has brought innovative art forms, startling social arrangements, unanticipated consequences — and dire warnings about the value of what is being lost. It is a pattern of change that dates back to the advent of writing itself. The digital revolution is no exception to this tradition. Recent paradigm-changing innovations such as e-mail and the Internet, universal mobile telephony, text messaging and smart phones are profoundly reshaping how and when we work, communicate, and entertain ourselves. But they have also brought a sense of unease over how pervasive these new technologies have become in all aspects of our lives. A recent national New York Times telephone survey reported that 40 percent of Americans check their work e-mail after hours or on vacation; studies have shown that people consume three times as much information a day as they did in 1960.1 They do this by the new — but now ubiquitous — skill of ‘multitasking. ’ Computer users at work change windows or check e-mail or other programs nearly 37 times an hour. In the 21st century a universe of information is only a click away — and we can’t seem to stop looking.
Rotation Face Detection Based on Three-Window Convolutional Neural Networks

In some family photos or special scene pictures, we can find some rotated faces. Most existing methods are based on increasing the features of rotated faces or changing the directions of pictures to augment the training data. However, these methods have their own limitations and can not detect rotated faces accurately. We propose a method based on three-window convolutional neural networks designed by ourselves. We extract the features of faces and change the feature matrices of faces by clockwise rotation and anticlockwise rotation through three-window convolutional layer in order to increase the face features. We retain parameters of the model after training, and convolutional layer replace fully connected layer. According to the heatmap of the sample, our method can predict face region. We carry out the experiments on FDDB and LFW datasets. The experiments on LFW show that our model achieves AUC of 0.9240, and recall of 0.9367 and the experiments on FDDB show that our model achieves recall of 0.9541.
A Wavelet Based Watermarking Approach in Concatenated Square Block Image for High Security

: Watermarking in digital contents has gained the more attraction in research community. In this approach copy-right information is concealed in to the concatenated square region of an image under wavelet domain, initially original image is undergoing an alternative pixel sharing approach and one of the shares undergo the circular column shift further, concatenates those shares. Next, square region is obtained by capturing the half of the row value in the last part of first share and the first part of second share which forms a square image. To enrich the robustness of the technique, watermarking is under consideration only in the folded square under wavelet. Further, the reverse process is carried out to generate the watermarked image. To show ownership, original and watermarked image have undergone the same operation and acquire the copyright information. Experimental results indicate that the proposed approach is robust against image processing attacks.
An investigation of viral fitness using statistical and computer models of Equine Infectious Anemia Virus infection

Simulation or statistically based models are often used to explore the outcomes and dynamics of physical systems or scientific experiments. In this work, we consider the use of a mixed effects differential equations model and the use of a stochastic agent based model to model data from competition infection experiments of Equine Infectious Anemia Virus (EIAV). EIAV is a retrovirus that presents with a lifelong persistent infection. Vaccine development for this and other retroviruses has been impeded due to the genetic variation that the virus exhibits in the presence of host immune pressure. To assess if genetic variation has an impact on replicative capacity, variants of EIAV that differ phenotypically were competed in dual infection assays. Data from these experiments were used to develop models that are aimed at being able to detect if there are differences in replicative capacity among the variants. We first consider a mixed effects model of data from an in vivo competition assay. Parameters of the model are estimated through the use of Markov Chain Monte Carlo (MCMC) methods. In vitro competition experiments were also conducted. These experiments offer more controlled experimental conditions than the in vivo assays. We then propose an agent based computer model that is able to simulate cell free and cell associated virus spread to model the data from the in vitro competition assays. To estimate the parameters of the agent based model, a surrogate Gaussian process model is used. Finally, we propose an extension of the Gaussian process model to account for the additional variance present in stochastic computer models.
Survey on Encryption Schemes used in Clouds

— Cloud computing, is an emerging computer technology that provides users to remotely store their data in a server and provide services on-demand. Since remote data storage is here, data security and privacy is the most critical issues. Users can read, write and store data to cloud. To protect the confidentiality of the data stored, the data must be encrypted using some encryption algorithms. Attribute based encryption (ABE) method is a well-known encryption algorithm used to encrypt data stored in clouds. In this paper, we are going to analyze different variations of encryption schemes used to store data in cloud.
TDMA Device Identification Using Continuity of Carrier Phase

Specific emitter identification provides the capability to distinguish radio emitters with the external features carried by the received waveforms. As existing features are not specific to time-division multiple access (TDMA) devices, it is yet intractable to discern the emitter in the case of low signal-to-noise rates or short durations. In this paper, we propose a novel characteristic based on the continuity of carrier phase and explore its application on TDMA device identification. The characteristic reflects a fact whether adjacent time slots are assigned to the same user terminal, which reveals a potential link between slots even if the protocol is unknown. To apply it to TDMA device identification, we augment the typical SEI scheme with two subsystems, Decision and Correction, in which the recognition results can be corrected to improve the accuracy. Simulation results demonstrate that the characteristic is resilient against the ambient noise, and it evidently improves the recognition accuracy.
Simulation of Power Losses improvement at 5 Bus System with Unified Power Flow Controller (UPFC) Using the NEPLAN Software

This paper represents a simulation of power losses improvement at 5 bus system with Unified Power Flow Controller ( UPFC) using the Software NEPLAN . In electric power system the power flow on transmission lines is a function of the parameter line ( ie: line impedance , voltage magnitude of sending end and receiving end , phase angle between voltage of sending end and receiving end . UPFC as one of the Flexible AC Transmission System Devices ( FACTS-device) can control the third line parameters , either separately or simultaneously . By adjusting the power magnitude in UPF C, voltage magnitude in s eries and shunt converter ( VSE and Vsh ), simulation result of placement of UPFC in the system 5 bus using the Software Neplan , indicating that the voltage on the bus increases, losses in transmission lines has decreased significantly and certainly Loadability and Available Transfer Capability network ( ATC) to be increased. Key word : Unified power flow controller, Power losses, Availability of transfer capability, NEPLAN
Late onset hypogonadism in men

Late onset hypogonadism (LOH) is clinical and biochemical syndrome associated with advancing age and characterized by symptoms and a deficiency in serum testosterone levels and/or action. Its pathogenesis and incidence has not been known up till now. Controversies have grown upon a lack of clear diagnostic criteria, especially non-specific symptoms and not established lower reference limit of testosterone serum level. Because of these diagnosis of LOH was variously determined. Nevertheless, substitution with testosterone in older men was recommended. European Male Aging Study (EMAS), the biggest prospective clinical study, indicated that physical and psychical LOH symptoms, considered yet as certain, do not show relation with fluctuations of testosterone levels dependent on the age. Moreover, it appears that decrease of testosterone with advancing age is lower than was suspected. Between 40 and 79 year of age it comes to –0.4%/ /year for total testosterone and –1.3%/year for free testosterone. It was found also that these changes depend mainly on modified risk factors for health but not specifically on aging. A contemporary definition of LOH is that it is occurrence of three sexual symptoms and decline of serum testosterone level below 11 nmol/L. These symptoms are: absence of morning erections, erectile dysfunction and disappearance of sexual fantasies. (Endokrynol Pol 2012; 63 (education supplement II) 15–19)
An Algorithm of Constructing Certificates Chain Based on the FriendshipPoint Group for P2P Network

The authentication and authorization based on CA is not suitable for P2P network because of its centralized control. DHT is efficient to search a required certificate in P2P network, but it is not fit for constructing the certificate chains including many certificates. This paper proposes an algorithm of constructing the certificate chain based on the friendship group of points in p2p network. Compared with DHT, It is more efficient because it adopts the structural overlay network in the small world to construct the authorization and authentication certificate chain.
Which Criteria to Use to Identify Metabolic Syndrome among Patients with Addictive Disorders? Observations among Patients with Alcohol and Opioid Dependence Syndrome

Sir, I read with interest the distinguished study by Singh et al.[1] published in July–August 2018 issue of Indian Journal of Endocrinology and Metabolism. Singh et al.[1] assessed the prevalence of metabolic syndrome (MetS) in patients with alcohol dependence syndrome (ADS) and opioid dependence syndrome (ODS) using revised National Cholesterol Education Programme Adult Treatment Panel (NCEP ATP-III) criteria and International Diabetes Federation (IDF) criteria. The authors found that among the individuals with ADS, the MetS prevalence was 20.8% and 9.9% according to the revised NCEP ATP-III criteria and IDF criteria, respectively. However, MetS prevalence among the individuals with ODS was found to be 20.3% and 5.1% according to revised NCEP ATP-III criteria IDF criteria, respectively. While there was a good degree of concordance between IDF and modified NCEP ATP-III criteria for MetS for ADS (n = 256) (κ = 0.649, P < 0.001), the concordance was only fair for ODS (κ = 0.333, P < 0.001). [1] The study results supported the recommendation that revised NCEP ATP-III criteria is a better choice than IDF criteria for identification of MetS in individuals having addictive disorders, especially opioid dependence. [1] I presume that these results ought to be taken cautiously. The authors addressed few study limitations that could cast some suspicious on the study results, notably small sample size, only male sample, nonexclusion of nicotine dependence, and not assessing physical activity. I presume that the following methodological limitation related to the MetS definition criteria used in the study might be additionally relevant. Obviously, the used ATP-III[2] and IDF[3] criteria in Singh et al.’s study[1] are both old and no more worthy as they were set more than a decade ago. It is worthy to mention that many national associations have constructed their own MetS definition criteria to precisely estimate MetS prevalence. [4] To my knowledge, the new diagnostic MetS criteria in Indian population have been launched in 2016 to be used in the clinical setting and researches. These criteria include the following components: waist circumference greater than 35′′ in men and greater than 31′′ in women; serum triglycerides equal or greater than 150 mg/dL; serum high-density lipoprotein cholesterol <40 mg/dL for men and <50 mg/dl for women; blood pressure equal or greater than 130/85 mmHg; and fasting blood sugar >100 mg/dL (prediabetes). [5] I wonder why Singh et al.[1] did not refer to the Indian-specific MetS criteria in their study. I presume that using these criteria instead of NCEP ATP-III and IDF criteria could yield more accurate results. Financial support and sponsorship Nil.
Virtual decomposition controller for flexible-joint robot manipulators with non-full-state feedback

In this article, a tracking controller for flexible-joint robot manipulators with non-full-state feedback is investigated based on virtual decomposition control (VDC) theory. First, virtual decomposition principle is applied to decouple the entire system of flexible-joint robot manipulator into rigid-link subsystems and flexible-joint subsystems; then, subcontrollers are designed correspondingly for each link or joint subsystem. Importantly, to realize the closed-loop tracking control without state measurements on the link side, an extended Kalman filter is designed to achieve the proposed VDC approach via non-full-state feedback. In addition, strict stability analysis of the control system is given according to the theory of virtual stability and Lyapunov stability. Finally, validation example is provided to verify the proposed control approach.
Self-emulsifying drug delivery system: An approach to enhance solubility

Self-emulsifying drug delivery systems (SEDDSs) have gained exposure for their ability to increase solubility and bioavailability of poorly soluble drugs. SEDDSs are mixtures of oils, surfactants, and cosurfactants, which are emulsified in aqueous media under conditions of gentle stirring and digestive motility that are encountered in the gastrointestinal (GI) tract. We found that SEDDSs could efficiently improve oral absorption of the sparingly soluble drugs by rapid self-emulsification and, subsequently, dispersion in the absorption sites. SEDDSs possess unparalleled potential in improving oral bioavailability of poorly water soluble drugs. Following their oral administration, these systems rapidly disperse in GI fluids, yielding micro-or nanoemulsions containing the solubilized drug. Owing to its miniscule globule size, the micro/nanoemulsifed drug can easily be absorbed through lymphatic pathways, bypassing the hepatic first-pass effect.
A MPTCP Path Selection Strategy Based on Improved Grey Relational Analysis

Multipath Transmission Control Protocol (MPTCP), a transport layer protocol, proposed by the IETF working group in 2009, can provide multipath communication end to end. It also can improve the utilization of network resources and network transmission reliability. However, that how to select multiple paths to improve the end to end overall throughput, and how to avoid the throughput declining by the performance difference, become the focus of this study. We propose a path selection strategy based on improved gray relational analysis, and set the optimal values of the QoS parameters for the selected paths as the reference sequence. According to the value of improved grey relational degree (IGRD) which is compared with reference sequence, we select the paths with better performance, smaller difference for transmission.
Asymptotically Optimal Size-Interval Task Assignments

Size-based routing provides robust strategies to improve the performance of computer and communication systems with highly variable workloads because it is able to isolate small jobs from large ones in a static manner. The basic idea is that each server is assigned all jobs whose sizes belong to a distinct and continuous interval. In the literature, dispatching rules of this type are referred to as SITA (Size Interval Task Assignment) policies. Though their evident benefits, the problem of finding a SITA policy that minimizes the overall mean (steady-state) waiting time is known to be intractable. In particular it is not clear when it is preferable to balance or unbalance server loads and, in the latter case, how. In this paper, we provide an answer to these questions in the celebrated limiting regime where the system capacity grows linearly with the system demand to infinity. Within this framework, we prove that the minimum mean waiting time achievable by a SITA policy necessarily converges to the mean waiting time achieved by SITA-E, the SITA policy that equalizes server loads, provided that servers are homogeneous. However, within the set of SITA policies we also show that SITA-E can perform arbitrarily bad if servers are heterogeneous. In this case we prove that there exist exactly $C! $C! asymptotically optimal policies, where $C$C denotes the number of server types, and all of them are linked to the solution of a single strictly convex optimization problem. It turns out that the mean waiting time achieved by any of such asymptotically optimal policies does not depend on how job-size intervals are mapped to servers. Our theoretical results are validated by numerical simulations with respect to realistic parameters and suggest that the above insights are also accurate in small systems composed of a few servers, i.e., ten.
Design, Evaluation and Co-optimization of Emerging Devices and Circuits

Author(s): Wang, Shaodi | Advisor(s): Gupta, Puneet | Abstract: The continued push for traditional Silicon technology scaling faces the main challenge of non-scaling power density. Exploring alternative power-efficient technologies is essential for sustaining technology development. Many emerging technologies have been proposed as potential replacement for Silicon technology. However, these emerging technologies need rigorous evaluation in the contexts of circuits and systems to identify their value prior to commercial investment. We have developed evaluation frameworks covering emerging Boolean logic devices, memory devices, memory systems, and integration technologies. The evaluation metrics are in terms of delay, power, and reliability. According to the evaluation results, the development of emerging Boolean logic devices is still far from being able to replace Silicon technology, but magnetic random access memory (MRAM) is a promising memory technology showing benefits in performance and energy-efficiency.As a specific example, we co-optimize MRAM with application circuits and systems. Optimized MRAM write and read design can significantly improve the system performance. We have proposed magnetic tunnel junction (MTJ) based process and temperature variation monitor, which enables variation-aware MRAM write and read optimization. We have also proposed utilizing negative differential resistance (NDR) to enable fast and energy-efficient write and zero-disturbance read for resistive memories including MRAM. In addition, we also design and adapt MRAM technology into low-power stochastic computing system to improve energy-efficiency. To further improve the stochastic computing system, a promising VC-MTJ based true random stochastic bitstream generator is proposed and utilized.
On the Quality of Computer Network Measurements

Due to the complex diversity of contemporary Internet-services, computer network measurements have gained considerable interest during recent years. Since they supply network research, development and operations with data important for network traffic modelling, performance and trend analysis, etc. The quality of these measurements affect the results of these activities and thus the perception of the network and its services. This thesis contains a systematic investigation of computer network measurements and a comprehensive overview of factors influencing the quality of performance parameters obtained from computer network measurements. This is done using a novel network performance framework consisting of four modules: Generation, Measurement, Analysis and Visualization. These modules cover all major aspects controlling the quality of computer network measurements and thus the validity of all kinds of conclusions based on them. One major source of error is the timestamp accuracy obtained from measurement hardware and software. Therefore, a method is presented that estimates the timestamp accuracy obtained from measurement hardware and software. The method has been used to evaluate the timestamp accuracy of some commonly used hardware (Agilent J6800/J6830A and Endace DAG 3.5E) and software (Packet Capture Library). Furthermore, the influence of analysis on the quality of performance parameters is discussed. An example demonstrates how the quality of a performance metric (bitrate) is affected by different measurement tools and analysis methods. The thesis also contains performance evaluations of traffic generators, how accurately application-level measurements describe network behaviour, and of the quality of performance parameters obtained from PING and J-OWAMP. The major conclusion is that measurement systems and tools must be calibrated, verified and validated for the task of interest before using them for computer network measurements. A guideline is presented on how to obtain performance parameters at a desired quality level.
A new technique for video copy-move forgery detection

This thesis describes an algorithm for detecting copy-move falsifications in digital video. The thesis is composed of 5 chapters. In the first chapter there is an introduction to forgery detection for digital images and videos. Chapters 2, 3 and 4 describe in detail the techniques used for the implementation of the detection algorithm. The experimental results are presented in the fifth and last chapter.
Principal Component Analysis (PCA) - An Effective Tool in Machine Learning

Abstract — Machine learning problems involves thousands or even millions of features of each training instance. This makes training in machine learning very slow and much harder to find a good solution. Ability to reduce the number features considerably without losing important information will significantly reduce the number of training data required to resolve tasks. Principal component Analysis (PCA) is the most popular dimensionality reduction algorithm used in machine learning analyses the interrelationships among a large number of variables and to explain these variabilities in terms of a smaller number of variables, called principal components, with a minimum loss of information. In this paper Iris dataset which has 50 instances of 3 types of iris flower species (Iris-setosa, Iris-versicolor and Iris-virginica) with four features (sepal length, sepal width, petal length and petal width) was used to demonstrate PCA. The model was implemented using Anaconda python 3.6 distribution. From the results, PCA clearly classifies the data visually showing their differences.
Human Motion Tracking Based on B-Spline Snake Algorithm

A new method for tracking of moving human objects is presented. The developed algorithm is based on B-spline Snake model. The Snake algorithm accesses the object contour through minimizing the energy; the object contour in each frame is presented through three B-spline curve. This approach gets the change image with double thresholds image segmentation between the neighboring frames, it could detect moving human objects with high quality and locate objects approximately. The contour extracts from the last frame put at the approximate position as the B-spline Snake model initialization. It accomplishes the tracking of moving human objects.