Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching Resiliency

Both adults and children who experience feelings of pessimism could often be susceptible to depression . They do worse at school than optimistic children, they feel less motivated and they attribute the cause of situations to causes external to them which they are not able to control . Besides, optimists lead healthier lives and have a longer life-span. As Dr. Seligman suggests, by the age of 8, the majority of the children have already developed and/or established an explanatory style. A child can either be optimistic and have a high sense of self-esteem and empowerment or not. However, according to research conducted by Dr. Seligman and his students at University of Pennsylvania, explanatory styles can be modified. Optimism is something that can be taught even if the pessimists among them and it can bring with it permanent changes in children’s lives. Recent research suggests that the percentages of depression incidents among students and especially among teenagers are on the increase. However, even if psychological conditions are absent, feelings of happiness and a sense of purpose are not guaranteed. Positive Psychology is here to fill this gap. The enhancement of the positive traits and of the positive emotions in order for individuals to reach their full potential is Positive Psychology’s main goal. Besides, isn’t that an indispensable part of education? Yes, according to parents who perceive the promotion of children’s resilience and well-being as a basic part of education [1]. Most interventions currently underway are re-active and are aiming at the therapeutic potential of Positive Psychology. On the contrary, in my opinion, a more proactive and preventive approach needs to be initiated as Young Learners are the future teenagers, hence they are the audience that needs to be targeted. Teaching optimism could result in what preventionists call the development of “protective factors”, about building resiliency in youth so as not to be involved in deviant behaviors such as alcohol and drug abuse, teen pregnancy, delinquency, gangs and dropping out of school [13]. Gibbs and Bennett [14]advocating the process suggesting that we should “turn the situation around by translating negative risk factors into positive action strategies”, namely protective factors which enable the children adolescent and later on adults to change or even reverse predictions of negative outcomes and make people to overcome life stressors [15]. Children who demonstrate resiliency are more responsive and produce more positive outcomes and predictions than other children, display far more activeness, flexibility and adaptability even as infants. Moreover, resilient kids have a tendency to produce comic relief and find different ways to perceive situations based on humor and on the ability to laugh at them and make light of embarrassing moments [15]. Consequently, resilient children are more likely to form more positive relationships with their classmates, peers and people of the opposite sex[18]. Besides ,resiliency brings with it the ability to deal with social and cognitive problems in a more adaptable, flexible way.
Balancing Control of a Humanoid Robot in the Presence of Unknown External Forces

When a humanoid robot carries an object or is applied by unknown external forces, the reference point of the Center of Mass (CoM) and Zero Moment Point (ZMP) will be changed in order to keep balanced. In this paper, we propose the method for keeping the statical balance with or without unknown external forces. And the CoM is modified for positioning the real ZMP to the desired ZMP. The proposed method is verified by experiments. Keywords— Zero Moment Point(ZMP), Balancing Control, Humanoid robot
A Receiver / Antenna Co-Design for a 1 . 5 mJ per Fix Fully-Integrated 10 x 10 x 6 mm 3 GPS Logger

This paper presents an ultra-low-power (ULP) GPS logger system that features a custom miniaturized antenna co-designed with a GPS analog front-end (AFE) optimized for heavy duty-cycling and a 10x10x6mm3 form-factor. The complete system includes a GPS AFE, processor, two custom 8Mb flash memory chips, custom antenna, and a 12mAh polymer Li-ion battery. An electrically small differential loop antenna (ka value of 0.24) is designed and all components are integrated on the top and bottom of the antenna in close proximity without degrading the antenna efficiency. In the sleep mode, the processor and the timer consume 50nW and in active mode it draws 12.5mW from a 1.2V supply. The AFE achieves a maximum conversion gain of 72dB, a noise figure of 2.2dB, and P1dB of -46dB. The blocker level that desensitizes the gain by 1dB is -6.1dBm at 1710MHz, one of the closest blockers near the GPS bands. The GPS logger achieves a 10dB SNR after correlation at an input power level of -125dBm. The logger is capable of storing data for 37 position fixes by streaming 10ms of received signal per fix to dual flash memories for later egress and post-processing.
Haptic Support for Avoiding Static and Dynamic Obstacles in UAV Tele-Operation

Impoverished sensory input makes tele-operation of Unmanned Autonomous Vehicles a diffcult task. Automation support can provide assistance to the operator, but may also produce automation surprise and a risk of loss of situation awareness, when the human operator fails to notice the actions of automation in high-workload situations. Previous work applied haptic feedback based on an artifcial risk feld to assist in avoidance of static obstacles with a small helicopter UAV. An off-line analysis of that solution shows that it would not be suffciently effective for the avoidance of dynamic, moving obstacles. A new haptic assist algorithm, based on velocity obstacle theory was developed. This algorithm was frst tested in off-line analyses, in scenarios with only static obstacles and in scenarios with a dynamic obstacle added. The off-line analysis showed the feasibility of the algorithm. The algorithm was then ported to a real-time environment and evaluated in pilot-in-the loop simulations, to verify the solutions and investigate the acceptability of the haptic feedback. Results indicate that the velocity obstacle approach works for both stationary and moving obstacles, in most, but not all scenarios.
A Parellel two Stage Classifier for Breast Cancer Prediction and Comparison with Various Ensemble Techniques

Life is a blessing but some diseases snatch human life away before even they are being diagnosed. One such horrifying disease is cancer. Among cancer, the most leading and common type is breast cancer. The actual problem lies in the fact that it is very hard and time consuming for even the most experienced medical specialist to detect the disease with high accuracy but the machines and modern computer science techniques have increased the accuracy and reduced the amount of time taken to diagnose cancer. In the subject paper, a new parallel machine learning technique called the two-stage classifier for identifying breast cancer is presented and compared with various existing techniques in terms of accuracy and percentage error reduction. The proposed technique turns out to be better not only in terms of parallelism but also in terms of the evaluated metrics and reduced the error percentage to almost 50% in one of the cases.
Generalized Linear Models Research Paper Modeling Bounded Outcome Scores Using The Binomial-Logit-Normal Distribution

Bounded outcome scores are often encountered in health-related survey studies. Such scores are usually bounded and discrete and are often treated as categorical or ordinal data, which is not satisfactory in some scenarios. The binomial-logit-normal distribution, as a parametric model, is a useful alternative for the bounded outcome scores. The proposed model converges to the continuous logit-normal model and hence bridges the gap between discrete modeling and continuous modeling. This result is useful when the score is dense and smooth within its bounded support. A quality of life data is shown as an application.
Adequate level of vitamin D is essential for maintaining good health

Problem niedoboru witaminy D wynika z niedostatecznej syntezy tego związku w skórze oraz małej zawartości w pokarmie. Stężenie zawartego w osoczu 25-hydroksycholekalcyferolu [25(OH)D3] jest uznanym wskaźnikiem poziomu witaminy D w organizmie. Związek ten jest metabolizowany z udziałem 1a-hydroksylazy do aktywnego biologicznie 1,25 dihydroksycholekalcyferolu (kalcytriol), który może regulować transkrypcję określonych genów bądź też oddziaływać na organy docelowe poprzez układy transdukcji sygnału. Znakomita większość, bo aż 90% znajdującego się we krwi 25(OH)D3 pochodzi z cholekalcyferolu syntetyzowanego w skórze pod wpływem promieni UVB. Tylko niewielka część 25(OH)D3 (około 10%), ma swoje źródło w spożywanych produktach. Doniesienia epidemiologiczne wskazują na istotną zależność między niedoborem witaminy D (wartość stężenia 25(OH)D3 poniżej 50 nmol/L) i wzrostem ryzyka wystąpienia chorób przewlekłych o odmiennej etiologii. Obecnie sądzi się, że utrzymanie stężenia 25(OH)D3 na poziomie 80 nmol/L, lub wyższym działa prewencyjnie w stosunku do takich schorzeń jak osteoporoza, choroby układu sercowo-naczyniowego, różne postaci chorób autoimmunizacyjnych oraz nowotworowych. Umiarkowane korzystanie z kąpieli słonecznych, odpowiednia dieta i suplementy witaminowe pozwalają utrzymać stężenie 25(OH)D3 na odpowiednim poziomie. Celem artykułu jest przedstawienie aktualnego stanu wiedzy na temat globalnego problemu niedoboru witaminy D i wynikających z tego konsekwencji.
The Evolution of Okun’s Law and of Cyclical Productivity Fluctuations in the United States and in the EU-15

The point of departure is Okun’s Law, a rough prediction that a cyclical deviation of output from trend would be divided between a 2/3 procyclical response of aggregate hours and a 1/3 procyclical response of productivity. The main conclusion of the paper is that the procyclical productivity response of Okun’s Law is obsolete in U. S. data since the mid‐1980s. These results cast doubt not only on Okun’s original law, but also on the convention in modern macroeconomic theory of assuming that unexplained procyclical productivity shocks drive part or all of business cycle fluctuations. The results are strengthened by a parallel econometric analysis of the EU‐15, which shows that over time the cyclical response has shifted toward a greater response of productivity in Europe and a smaller response of labor input, the opposite of the shift in the U. S. response. Hypotheses are developed to explain this disparity, based on a range of differences in institutional arrangements and customs across the Atlantic, sometimes summarized as “American Exceptionalism. ” These differences include the much greater increase of income inequality in the U. S. than in the EU‐15 since the 1970s and the related shift of power to management from labor as the influence of U. S. labor unions has waned. The explanation of why European responses have moved in the opposite direction from those of the U.S. begins with the contrasting time‐series behavior of income inequality in the U.S. and Europe. In Europe, there has been no parallel shift towards maximizing shareholder value as the prime decision criterion of executives. Perhaps more important is a history of employment protection legislation that raises the cost of layoffs and firing of workers (which is essentially costless in the U. S.), and a complex set of work‐sharing institutions involving both government subsidies and union‐firm negotiations that represents an explicit attempt to minimize employment responses to output fluctuations. Perhaps the most important implication of this paper is for the evolution of modern macroeconomics, which since the initial invention of the real‐business cycle model has treated productivity fluctuations as exogenous processes that implicitly and vaguely reflect random technological changes. This paper shows that cyclical productivity fluctuations have little to do with technology, and much to do with the evolution of labor‐market institutions, customs, and practices. Robert J. Gordon, Northwestern University rjg@northwestern.edu http://faculty‐web.at. northwestern.edu/economics/gordon/indexmsie.html Okun’s Law and Productivity Fluctuations in the US and EU, Page 1
System Resilience-SEBoK

According to the Oxford English Dictionary on Historical Principles (1973), resilience is “the act of rebounding or springing back. ” This definition most directly fits the situation of materials which return to their original shape after deformation. For human-made, or engineered systems the definition of resilience can be extended to include the ability to maintain capability in the face of a disruption. The US government definition for resilient infrastructure systems is the "ability of systems, infrastructures, government, business, communities, and individuals to resist, tolerate, absorb, recover from, prepare for, or adapt to an adverse occurrence that causes harm, destruction, or loss of national significance” (DHS 2010). The name Resilience Engineering was coined in the book Resilience Engineering: Concepts and Precepts (Hollnagel et al 2006). The authors make clear in this book that Resilience Engineering has to do with the resilience of the organizations that design and operate engineered systems and not with the systems themselves. The term System Resilience used in this article is primarily concerned with the techniques used to consider the resilience of engineered systems directly. To fully achieve this, SE also needs to consider the resilience of those organizational and human systems which enable the life cycle of an engineered system. The techniques or design principles used to assess and improve the resilience of engineered systems across their life cycle are elaborated by Jackson and Ferris (2013).
5 The Prediction and Analysis of Inter-and Intra-Species Protein-Protein Interaction

Protein-protein interactions (PPIs) are essential to cellular processes. Recent developments of high-throughput technologies have uncovered vast numbers of PPIs. However, the experimental evidences are mostly for intra-species interactions of model organisms, especially human. Studies of non-human organisms and inter-species PPIs are few. For organisms such as Arabidopsis thaliana, the experimentally detected 5990 PPIs are estimated to be less than 3% of the entire A. thaliana interactome (M. Lin et al., 2011). The accuracy of high-throughput PPI experiments is also doubtful (Mrowka et al., 2001; Sprinzak et al., 2003; von Mering et al., 2002). To resolve the above issues, several computational methods have been developed to evaluate and predict PPIs. This chapter focuses on direct PPIs which involve physical interactions of proteins, provides a brief overview of the reliabilities of high-throughput PPI detection technologies, and discusses the weakness and strength of important PPI computational prediction and evaluation methods. The major repositories which store, evaluate, and analyse both detected and predicted PPIs are also introduced.
On the Edge Realtime Intrusion Prevention System for DoS Attack

Industrial control systems manage critical infrastructures that are immensely diverse and complicated. These highly linked critical infrastructures are made up of networks of industrial control system (ICS) each responsible for controlling critical processes. During its nascent stages the controllers in the ICS were built for robust operation in extreme industrial conditions, but little to no emphasis was placed on safeguarding the system against potential cyberthreats. The industrial networks having legacy controllers are air gapped from the enterprise network hence a centrally deployed NIDS in the same network of the trusted nodes is often used as the last line of defence against intrusions such as malicious activity or policy violation. Most cyber incidents in industrial control systems have witnessed the breach of the air gap and compromised trusted nodes. Hence this paper proposes an on-the-edge Intrusion Prevention System (IPS) that can detect and prevent Denial of Service (DoS) attack on the Programmable Logic Controllers (PLCs) from trusted nodes at real time. A novel attribute of our proposed framework is that it is generic in nature and can be used on any PLC irrespective of the critical infrastructure being controlled by it. A wide range of experimentation has been performed to validate the performance of our proposed IPS.
Leakage Estimation of SRAM cell based on Node Voltage and Current Characterization Leakage estimation of SRAM cell

The leakage current especially gate leakage and subthreshold leakage have been identified as the dominant leakage types below 65nm technology node. This leakage in MOSFET devices act individually in different temperature and circuit conditions. Thus, it is very important to estimate the effect of each one in a given circuit. In this article the leakage element of SRAM cell is characterized based on the spice characterization of the internal node voltage profile in pursuit with the current characterization procedure. The corner models SF, FS and TT are used to analysis the process variability of the cell. Monte Carlo (MC) simulation is run to figure out the leakage current distribution and voltage swing at the storage node in read mode of the cell. The dependency of storage node voltage on supply voltage scaling is also analyzed in read mode using FS and SF corners. Results shows that storage node voltage always scale linearly with supply voltage. In this work, with VDD of 0.6V and 0.4V follows the same 33% reduction in voltage swing at storage node Q for both FS and SF corner. All the device characterizations are performed in 45nm process technology node. Keywords— SRAM cell; Voltage Characterization; Gate Leakage; Subthreshold Leakage; Corner Model; Monte Carlo; Leakage Current Introduction.
A Framework for Intrusion Detection Based on Workflow Mining

Information systems handle large amount of data within enterprises by offering the possibility to collect, treat, keep and make information available. To achieve this, it is crucial to secure data from intrusion that disturb confidentiality, availability, and integrity of data. This integrity must follow the strategic alignment of the considered enterprise. Unfortunately, the goal of attackers is to affect the resources present in the system. Research in intrusion detection field is still in search of proposals to relevant problems. Many solutions exist supporting machine learning and datamining models. Nevertheless, these solutions based on signature and behavior approaches of intrusion detection, are more interested in data and have not a global view of processes. The aim of this paper is to use workflow mining for a Host-based intrusion detection by monitoring workflow event logs related to resources. With workflow mining, process execution are stored in event logs and the detection of intrusion can be realized by their analysis on the basis of a well-defined security policy. To achieve our goal, step by step, we start by the specification of different concepts manipulated. Afterwards, we provide a model of security policy and a model of intrusion detection that enables us to have a low rate of false alerts. Finally, we implement the solution via a prototype to observe how it can work.
Animated text : More than meets the eye ?

The universal integration of computers into the environments of work and leisure has been a major factor in the increasing reliance upon imagery to communicate information of all kinds, challenging the supremacy of text as the dominant communication modality in some areas. As a consequence there is a greater emphasis on the importance of visual literacy, albeit specialised, alongside conventional literacy and numeracy as a requisite for both learning and effective functioning in the workplace. It is evident, that the sort of skills acquired from an early age for the processing of textual and numerical information, are not matched by equivalent skills for the processing of visual information, especially when encountered in unfamiliar formats. This can impede learning. This paper proposes the strategic use of animated text labels as didactic agents for directing the spatial and temporal attention of learners when introduced to unfamiliar visuals, and the capacity of such animated text labels to perform a preliminary explanatory function in addition to identification. The origin of text animation within screen based media is addressed as well as aspects of recent research into cognition and attention that can inform the use of such animations in accomplishing instructional goals.
Hierarchical Structural Learning for Language Generation

We develop novel generative methods for language modeling that leverage graphical structure instead of traditional, strict left-to-right generation. Language generation is viewed as a topdown process through a parse tree. Our models are applicable to language modeling and representation as well as neural language parsing. We also propose a novel distribution for language modeling that enables these models. We both experiment with methods using supervised parse trees and methods that infer the most useful parse tree in an unsupervised manner.
A Study to Compare Different Methods for Determination of Generation Time of Mycobacterium tuberculosis Isolates

Original Research Article Apart from genes responsible for drug resistance of Mycobacterium tuberculosis, dramatic reduction of metabolic activity of tubercle bacilli in chronically infected animals reveals long generation time. This could be an additional explanation of drug resistance. Amongst different methods available to determine generation time, colony count method, which is cheap, easily available and affordable one, is compared with a novel method i.e. DNA spectrophotometry in an attempt to cut short turnaround time. Thus, this study was conducted to compare two different methods (Colony count method and DNA spectrophotometry) for determination of generation time of Mycobacterium tuberculosis in vitro. For this, 20 new sputum smear positive patients were placed in the study. Mycobacterium tuberculosis strains were isolated in pure culture by decontaminating, liquefying & concentrating sputum sample & anti-tubercular susceptibility tests were performed. From these, 10 all-drug (Rifampicin and Isoniazid) sensitive isolates were chosen and reference strains were procured. Single mycobacterial cell suspension was prepared from each. After proper standardization, they were incubated in CO2 incubator and 10μl of each culture suspension was inoculated in Middlebrook 7H11 agar plate to measure CFU/ml and from 500 μl of each culture suspension, DNA extraction is done by Phenol-Chloroform method which is followed by Spectrophotometric quantification of OD/ml (at 260nm) at different time-points (Hour 0,18,36,54,72). Generation time was evaluated from graph of the above colony counts using formula. It was observed that serial culturing by counting of CFU is the best method for assessment of generation time while DNA spectrophotometry could not be used for this purpose. In short, colony count method still stands as the gold standard for determination of generation time for mycobacteria whereas DNA spectrophotometry failed poorly to evaluate the same.