Miracle-dz/UniFAR-FTUs huggingface dataset:
Eye Templates based Driver Fatigue Detection using Mathematical Morphology

Fatigue is defined as a " state in which performance capabilities are temporarily impaired by continual activity demands which exceed the ongoing capacity to restore performance capabilities. " Driver fatigue is the key factor of heavy traffic accidents in the world. Fatigue affects mental alertness, decreasing an individual's ability to operate a vehicle safely and increasing the risk of human error that could lead to fatalities and injuries. To make a valid assessment or relatively reliable estimate of a driver's fatigue level and provide a timely recommendation for action to be taken before a dangerous situation arises, represents a significant challenge. In this paper, Eyes status is detected in a digital face image using some image processing skills such as segmentation and morphological processing. Through color segmentation the non-skin part is eliminated. By initially narrowing the detection field to areas representing human skin, segmentation saves valuable time and increases the success rate. After skin color segmentation, various morphological image processing method are used to refine the image, like eliminate noise. Then the next step includes eye detection and tracking in which the technique of template matching is used to create the eye templates and using these templates the location of eyes in next consecutive frames is tracked. Study of eye region reveals the open and close status of eyes. The status in consecutive frame reveals fatigueness. If eyes remain close in next 7-8 consecutive frames then driver is drowsy. I. Introduction Human error is known to be a causal factor in many accidents. Human error is explained by shortcomings in perception, interpretation of information, decision-making, information recall and direct performance of an action. Driver fatigue is the key factor of heavy traffic accidents in the world. It has been widely recognized as critical safety issues that cut across all modes in the transportation industry, because it is difficult to determine the degree to which fatigue plays a role in crashes. Fatigue, however, can be managed, and effectively managing fatigue will result in a significant reduction in related risk and improved safety. In this paper fatigue detection will be done by using the concept of eye tracking. In recent years image processing on human faces has been used in many applications, such as face recognition, face analysis [4], eye detection [6], gaze tracking [9], etc. Among all of these researches, the first step is usually to locate faces. Recently, the human …
CP-TDMA: Coloring- and Probability-Based TDMA Scheduling for Wireless Ad Hoc Networks

This paper addresses the issue of transmission scheduling in wireless ad hoc networks. We propose a Time Division Multiple Access (TDMA) scheduling scheme based on edge coloring and probabilistic assignment, called CP-TDMA. We categorize the conflicts suffered by wireless links into two types: explicit conflicts and implicit conflicts, and utilize two different strategies to deal with them. Explicit conflicts are avoided completely by a simple distributed edge-coloring algorithm μ-M, and implicit conflicts are minimized by applying probabilistic time slot assignments to links. We evaluate CP-TDMA analytically and numerically, and find that CP-TDMA, which requires only local information exhibits a better performance than previous work.
Expression and Activity of Acid-Sensing Ion Channels in the Mouse Anterior Pituitary

Acid sensing ion channels (ASICs) are proton-gated cation channels that are expressed in the nervous system and play an important role in fear learning and memory. The function of ASICs in the pituitary, an endocrine gland that contributes to emotions, is unknown. We sought to investigate which ASIC subunits were present in the pituitary and found mRNA expression for all ASIC isoforms, including ASIC1a, ASIC1b, ASIC2a, ASIC2b, ASIC3 and ASIC4. We also observed acid-evoked ASIC-like currents in isolated anterior pituitary cells that were absent in mice lacking ASIC1a. The biophysical properties and the responses to PcTx1, amiloride, Ca2+ and Zn2+ suggested that ASIC currents were mediated predominantly by heteromultimeric channels that contained ASIC1a and ASIC2a or ASIC2b. ASIC currents were also sensitive to FMRFamide (Phe-Met-Arg-Phe amide), suggesting that FMRFamide-like compounds might endogenously regulate pituitary ASICs. To determine whether ASICs might regulate pituitary cell function, we applied low pH and found that it increased the intracellular Ca2+ concentration. These data suggest that ASIC channels are present and functionally active in anterior pituitary cells and may therefore influence their function.
Customer Appeasement Scheduling

Almost all of the current process scheduling algorithms which are used in modern operating systems (OS) have their roots in the classical scheduling paradigms which were developed during the 1970's. But modern computers have different types of software loads and user demands. We think it is important to run what the user wants at the current moment. A user can be a human, sitting in front of a desktop machine, or it can be another machine sending a request to a server through a network connection. We think that OS should become intelligent to distinguish between different processes and allocate resources, including CPU, to those processes which need them most. In this work, as a first step to make the OS aware of the current state of the system, we consider process dependencies and interprocess communications. We are developing a model, which considers the need to satisfy interactive users and other possible remote users or customers, by making scheduling decisions based on process dependencies and interprocess communications. Our simple proof of concept implementation and experiments show the effectiveness of this approach in the real world applications. Our implementation does not require any change in the software applications nor any special kind of configuration in the system, Moreover, it does not require any additional information about CPU needs of applications nor other resource requirements. Our experiments show significant performance improvement for real world applications. For example, almost constant average response time for Mysql data base server and constant frame rate for mplayer under different simulated load values.
Rejection In The Job Selection Process: The Effects Of Information & Sensitivity

Most people will experience rejection in the job selection process. Rejection from job opportunities is often issued via a letter from a hiring manager. These letters elicit reactions from applicants who may, in turn, have less favorable self perceptions and less favorable perceptions of the organization from which the applicant was rejected. Numerous research articles have been published that deal with delivering notification of selection and/or rejection to applicants in the job selection process. However, relatively few use a realistic laboratory design to obtain results. This study examined the effects of sensitivity and information in notifications of rejection when applicants are rejected in the job selection process. A more realistic laboratory design was used to increase the psychological fidelity of the job selection situation. One hundred forty undergraduate students participated in this study. Participants were told to imagine that they were graduate school applicants. Then, the participants completed a fake graduate school admissions test and received notification of rejection from a fake graduate school. Participants were assigned to conditions (letters varying in sensitivity and information type) randomly and the participants completed a post-notification of rejection survey that captured their self and organizational perceptions. Additionally, moderating variables were explored.
Wave Leader Election Protocol for Wireless Sensor Networks

In this paper we present and analyze a wireless wave leader election protocol (WWLE) for wireless mobile ad hoc sensor networks. We present also a mathematical model for the energy consumption within a sensor node. The capabilities of a node being a leader (like available resources such as battery energy, network capabilities, etc.) are integrated in the algorithm. The simulation results show that this algorithm is efficient in number of rounds and number of messages.
Polanyi through the lens of Epistemologies of the South and Postcolonial Feminist Economics: different glances at the concept of disembeddedness

This paper debates the concept of disembeddeness in the context of the feminisms of the South. Departing from a feminist rereading of Polanyi’s work, proposed by Waller and Jennings (1991), I intend to discuss the Polanyian concept of disembeddedness within market societies, by interacting with the points of disagreement they presented regarding the limits of Polanyi’s criticism on formalist economics. Given Polanyi was described as being epistemologically complacent with the formalist model to describe capitalist economies and that they argued the formalist perspective has deepened the abyss between family and economy domains, I discuss to what extent modern gender meanings related to this split still remain in case of non-western perspectives of gender. Waller and Jennings have argued that the formalist analysis reinforces the invisibility of non market social arrangements, equally indispensable to provide an accurate picture of the provisioning dynamics which caracterizes, first and foremost, the actual economies. Despite all the promising convergence between Polanyi’s theoretical perspective and a feminist reinterpretation of Economics, Polanyi is assumed as having emphasised the inadequacy of formalist analysis for understanding non market societies and doing so underestimated the relevance of non market social arrangements within market societies.
Semi-Supervised Discriminative Language Modeling with Out-of-Domain Text Data

One way to improve the accuracy of automatic speech recognition (ASR) is to use discriminative language modeling (DLM), which enhances discrimination by learning where the ASR hypotheses deviate from the uttered sentences. However, DLM requires large amounts of ASR output to train. Instead, we can simulate the output of an ASR system, in which case the training becomes semisupervised. The advantage of using simulated hypotheses is that we can generate as many hypotheses as we want provided that we have enough text material. In typical scenarios, transcribed in-domain data is limited but large amounts of out-of-domain (OOD) data is available. In this study, we investigate how semi-supervised training performs with OOD data. We find out that OOD data can yield improvements comparable to in-domain data.
A system for an anticipative front human following robot

Human following of mobile robots has been popularized in the scientific field of the service-oriented robots research. However, the behavior of such robots is passive in the most of cases. Compared to a passive following robot, a framework for an anticipative front following robot is proposed which is based on the technology of Kinect camera and the identification of human sensing and motion system. The real-time data is collected by Kinect and applied into the human walking model after median filtering. The human walking model is designed for identifying four basic human walking behaviors accurately. Then a human walking behavior is predicted using the optimized Kalman filtering algorithm proposed specially for the human walking model to predict the next behavior and provide more precise data for the system of robot control, which both could raise the success rate of accurate tracking. The system performance is assessed through experimental comparison of two specific human following behaviors: anticipative front following and passive front following. The results show that the success rate of predicting human walking behavior and following in front achieves 95.2%.
Targeted transgene integration overcomes variability of position effects in zebrafish

Zebrafish transgenesis is increasingly popular owing to the optical transparency and external development of embryos, which provide a scalable vertebrate model for in vivo experimentation. The ability to express transgenes in a tightly controlled spatio-temporal pattern is an important prerequisite for exploitation of zebrafish in a wide range of biomedical applications. However, conventional transgenesis methods are plagued by position effects: the regulatory environment of genomic integration sites leads to variation of expression patterns of transgenes driven by engineered cis-regulatory modules. This limitation represents a bottleneck when studying the precise function of cis-regulatory modules and their subtle variants or when various effector proteins are to be expressed for labelling and manipulation of defined sets of cells. Here, we provide evidence for the efficient elimination of variability of position effects by developing a PhiC31 integrase-based targeting method. To detect targeted integration events, a simple phenotype scoring of colour change in the lens of larvae is used. We compared PhiC31-based integration and Tol2 transgenesis in the analysis of the activity of a novel conserved enhancer from the developmentally regulated neural-specific esrrga gene. Reporter expression was highly variable among independent lines generated with Tol2, whereas all lines generated with PhiC31 into a single integration site displayed nearly identical, enhancer-specific reporter expression in brain nuclei. Moreover, we demonstrate that a modified integrase system can also be used for the detection of enhancer activity in transient transgenesis. These results demonstrate the power of the PhiC31-based transgene integration for the annotation and fine analysis of transcriptional regulatory elements and it promises to be a generally desirable tool for a range of applications, which rely on highly reproducible patterns of transgene activity in zebrafish.
Reappraisal of the Trophic Ecology of One of the World’s Most Threatened Spheniscids, the African Penguin

Many species of seabirds, including the only penguin species breeding on the African continent, are threatened with extinction. The world population of the endangered African penguin Spheniscus demersus has decreased from more than 1.5 million individuals in the early 1900s to c.a. 23 000 pairs in 2013. Determining the trophic interactions of species, especially those of conservation concern, is important when declining numbers are thought to be driven by food limitation. By and large, African penguin dietary studies have relied on the identification of prey remains from stomach contents. Despite all the advantages of this method, it has well known biases. We therefore assessed the African penguin’s diet, using stable isotopes, at two colonies in Algoa Bay (south-east coast of South Africa). These represent over 50% of the world population. Various samples (blood, feathers, egg membranes) were collected for carbon and nitrogen stable isotope analyses. Results indicate that the trophic ecology of African penguins is influenced by colony, season and age class, but not adult sex. Isotopic niches identified by standard Bayesian ellipse areas and convex hulls, highlighted differences among groups and variability among individual penguins. Using Bayesian mixing models it was for the first time shown that adults target chokka squid Loligo reynaudii for self-provisioning during particular stages of their annual cycle, while concurrently feeding their chicks primarily with small pelagic fish. This has important ramifications and means that not only pelagic fish, but also squid stocks, need to be carefully managed in order to allow population recovery of African penguin.
Cognitive Neuroscience of Attention From brain mechanisms to individual differences in efficiency

Aspects of activation, selection and control have been related to attention from early to more recent theoretical models. In this review paper, we present information about different levels of analysis of all three aspects involved in this central function of cognition. Studies in the field of Cognitive Psychology have provided information about the cognitive operations associated with each function as well as experimental tasks to measure them. Using these methods, neuroimaging studies have revealed the circuitry and chronometry of brain reactions while individuals perform marker tasks, aside from neuromodulators involved in each network. Information on the anatomy and circuitry of attention is key to research approaching the neural mechanisms involved in individual differences in efficiency, and how they relate to maturational and genetic/environmental influences. Also, understanding the neural mechanisms related to attention networks provides a way to examine the impact of interventions designed to improve attention skills. In the last section of the paper, we emphasize the importance of the neuroscience approach in order to connect cognition and behavior to underpinning biological and molecular mechanisms providing a framework that is informative to many central aspects of cognition, such as development, psychopathology and intervention.
Survival by AIDS defining condition in rural Uganda

Objectives: To report the initial AIDS defining conditions, CD4 lymphocyte counts around the time of AIDS diagnosis, and survival by AIDS defining condition in a population based cohort in rural Uganda. Methods: Participants in an HIV natural history cohort in rural Uganda were reviewed every 3 months at routine visits and at other times when they were ill. The date and nature of the first AIDS defining condition in participants developing AIDS during follow up between the start of the cohort in 1990 and the end of 1998 were noted. The CD4 count at, or within, 3 months of this time was recorded for those participants who developed AIDS (WHO stage 4) after 1993. Results: The median survival from developing AIDS to death was 9.3 months and the median CD4 lymphocyte count around the time of developing AIDS was 150 cells ×106/l. The most frequent AIDS defining conditions were wasting syndrome, oesophageal candidiasis, and mucocutaneous herpes simplex virus infection (HSV) for more than 1 month. The median survival with wasting syndrome, Kaposi's sarcoma, and oesophageal candidiasis was less than 3.5 months; however, survival with cryptosporidial diarrhoea, chronic HSV, and extrapulmonary tuberculosis was greater than 20 months. There was little relation between CD4 count around the time of development of the AIDS defining condition and the median survival with that condition. Conclusions: The survival for most AIDS defining conditions was generally shorter and the median CD4 lymphocyte count higher than studies reported from developed countries. However, the conditions with the longest survival (cryptosporidial diarrhoea, chronic HSV, and extrapulmonary tuberculosis) had a similar survival to that in developed countries and these conditions have a high background level in this population.
Design of Energy Management Strategy in Hybrid Vehicles by Evolutionary Fuzzy System Part I: Fuzzy Logic Controller Development

In this two-part paper presents an evolutionary fuzzy design method based energy management strategy for parallel hybrid electric vehicles. The proposed method consists of two steps. In the first phase, a fuzzy logic controller was employed to quantify the energy management system behavior. In the second stage, a genetic algorithm was used for fine-tuning the parameters of the fuzzy controller based on a goal of minimizing fuel consumption. We employed a novel method to cope with the difficulty often encountered in designing a fitness function. The simulation study reveals that the proposed "evolutionary fuzzy system" based energy management strategy provide a platform of new energy management system and gives improved performance of a parallel hybrid vehicle. In part I, the basic framework of energy management strategies is discussed and a detailed description of developing a fuzzy logic controller. The second stage work is presented in the second part of this paper
CYBER: A CommunitY-Based sEaRch engine

In this paper, we propose CYBER, a CommunitY Based sEaRch engine, for information retrieval utilizing community feedback information in a DHT network. In CYBER, each user is associated with a set of user profiles that capture his/her interests. Likewise, a document is associated with a set of profiles-one for each indexed term. A document profile is updated by users who query on the term and consider the document as a relevant answer. Thus, the profile acts as a consolidation of users feedback from the same community, and reflects their interests. In this way, as one user finds a document to be relevant, another user in the same community issuing a similar query will benefit from the feedback provided by the earlier user. Hence, the search quality in terms of both precision and recall is improved. We conduct a comprehensive experimental study and the results show the effectiveness of our scheme.
Demographics inference through Wi-Fi network traffic analysis

Although privacy leaking through content analysis of Wi-Fi traffic has received an increased attention, privacy inference through meta-data (e.g. IP, Host) analysis of Wi-Fi traffic represents a potentially more serious threat to user privacy. Firstly, it represents a more efficient and scalable approach to infer users' sensitive information without checking the content of Wi-Fi traffic. Secondly, meta-data based demographics inference can work on both unencrypted and encrypted traffic (e.g., HTTPS traffic). In this study, we present a novel approach to infer user demographic information by exploiting the meta-data of Wi-Fi traffic. We develop a proof-of-concept prototype, Demographic Information Predictor (DIP) system, and evaluate its performance on a real-world dataset, which includes the Wi-Fi access of 28,158 users in 5 months. DIP extracts four kinds of features from real-world Wi-Fi traffic and proposes a novel machine learning based inference technique to predict user demographics. Our analytical results show that, for unencrypted traffic, DIP can predict gender and education level of users with an accuracy of 78% and 74% respectively. It is surprising to show that, even for HTTPS traffic, user demographics can still be predicted at a precision of 67% and 72% respectively, which well demonstrates the practicality of the proposed privacy inference scheme.
Axes-based visualizations with radial layouts

In the analysis of multidimensional data sets questions involving detection of extremal events, correlations, patterns and trends play an increasingly important role in a variety of applications. Axes-based visualizations like Parallel or Star Coordinates are useful tools for the analysis of multidimensional data sets. In this paper, we present several interactive axes, which can be used to analyze data in an intuitive manner. Furthermore, we present two novel radial visual arrangements of such axes - the TimeWheel and the MultiComb. They focus on data sets with one variable of reference. TimeWheel and MultiComb in combination with interactive axes are part of an interactive framework called VisAxes, which can be used for enhanced multidimensional data browsing and analysis.