Miracle-dz/UniFAR-FTUs huggingface dataset:
The development of decision making skill in sport : an ecological dynamics perspective

In this chapter we introduce a theoretical framework for studying decision making in sport: the ecological dynamics approach, which we integrate with key ideas from the literature on learning complex motor skills. Our analysis will include insights from Berstein (1967) on the coordination of degrees of freedom and Newell's (1985) model of motor learning. We particularly focus on the role of perceptual degrees of freedom advocated in an ecological approach to learning. In introducing this framework to readers we contrast this perspective with more traditional models of decision-making. Finally, we propose some implications to the training of decision-making skill in sport.
Usability and Interoperability of IEC 61499 based distributed automation systems

Since IEC 61499 has reached the state of an international standard and a substantial body of research results exists the question of the authors as main intention for this paper was: Do the models of IEC 61499 solve all problems when thinking of usability and interoperability in heterogeneous system environments? The main problems discussed within the paper concern to the execution model defined for basic function blocks and the scheduling of events within function block networks.
Predicting behaviour: comparing the performance of factual versus attitudinal approaches

Abstract Despite years of refinement and improvement to questionnaire design, the need remains to identify effective, but ‘user-friendly’ questioning procedures to predict behaviour, without compromising predictive performance. Questionnaires developed to predict behaviour typically use an attitudinal approach. However, those types of questionnaires are associated with increased respondent fatigue, decreased question comprehension, opposition to question tone and demand effects. An alternative approach involves use of factual questions. This study compares ease of application in the field as well as predictive performance of the two approaches to questionnaire design in the context of predicting willingness to donate blood. Results indicate that factual questions are quicker and easier to apply in the field than attitudinal questions, while predictive performance of the approaches is equivalent.
PENGEMBANGAN KEMAMPUAN PENELITIAN DAN PENULISAN KARYA ILMIAH BAGI GURU MATEMATIKA SMA/SMK MUHAMMADIYAH DI KLATEN DAN SUKOHARJO

Tujuan kegiatan pengabdian pada masyarakat ini adalah untuk membimbing guru matematika SMA/SMK Muhammadiyah dalam melakukan kegiatan penelitian dan penulisan karya ilmiah. Kegiatan pengabdian ini dilaksanakan dalam lima tahapan yaitu: 1) Sosialisasi kegiatan penelitian dan penulisan karya ilmiah sebagai bagian dari Pengembangan Keprofesian Berkelanjutan (PKB), 2) memperkuat materi penelitian tindakan kelas (PTK), 3) pembimbingan penyusunan proposal PTK, 4) pembimbingan penulisan laporan penelitian dan karya ilmiah, 5) diseminasi hasil penelitian. Semua tahapan dilaksanakan pada bulan April hingga Oktober 2016. Berdasarkan kegiatan yang telah dilaksanakan disimpulkan: 1) pelatihan dan pendampingan mampu memotivasi para guru untuk mengembangkan kemampuan profesionalisme melalui kegiatan penelitian dan penulisan karya ilmiah, 2) guru mampu melaksanakan kegiatan penelitian tindakan kelas secara berkelompok, 3) guru mampu menulis karya ilmiah dan mempresentasikan dalam forum diseminasi hasil penelitian, 4) terdapat 7 artikel ilmiah hasil penelitian PTK yang ditulis oleh guru sebagai hasil kegiatan pengabdian.
Fast seam carving using partial update and divide and conquer method

A variety of display devices with different resolutions and aspect ratios require image resizing while preserving the image's important information. Among the many available techniques, the seam carving method is the most promising due to its simplicity and effectiveness. However, the optimal seam carving method takes a long computation time due to its nature of sequential processing. This paper proposes two approaches to accelerate the original seam carving method. One is to update the cumulative minimum energy map (CMEM) partially around the seam and another is to process several seams using the divide and conquer (DNC) method. The proposed methods are about 2 ∼ 5 times faster than the original seam carving method, while preserving the image's information as effectively as the original seam carving method.
A Priority-Based Consensus Protocol

Consensus is a basic agreement problem whose solutions are funda- mental for building fault-tolerant distributed systems. Consensus for real-time systems is usually designed under strong timing assumptions, which state that there are upper bounds on both processing and message transmission times. Since violating these bounds may compromise safety, such systems are usually implemented based on pessimistic bounds. In this paper the consensus prob- lem is revisited taking into consideration that the system provides a priority- based communication network. It is shown that for those systems the message transmission time bound can be relaxed so that all but the highest priority mes- sages may be arbitrarily delayed or even lost. The derived consensus protocol can also cope with process crashes, processes may start executing the proto- col asynchronously, and consensus is reached within a known bounded time. These characteristics make the proposed solution very interesting to real-time systems. The protocol is proved correct and analyzed by simulation. Since there are a number of priority-based networks, the results presented here have both theoretical and practical implications.
Research on Religion, Spirituality, and Mental Health: A Review

Religious and spiritual factors are increasingly being examined in psychiatric research. Religious beliefs and practices have long been linked to hysteria, neurosis, and psychotic delusions. However, recent studies have identified another side of religion that may serve as a psychological and social resource for coping with stress. After defining the terms religion and spirituality, this paper reviews research on the relation between religion and (or) spirituality, and mental health, focusing on depression, suicide, anxiety, psychosis, and substance abuse. The results of an earlier systematic review are discussed, and more recent studies in the United States, Canada, Europe, and other countries are described. While religious beliefs and practices can represent powerful sources of comfort, hope, and meaning, they are often intricately entangled with neurotic and psychotic disorders, sometimes making it difficult to determine whether they are a resource or a liability.
Visual similarity-based phishing detection without victim site information

Phishing attacks, which steal users' account information by fake websites, have become a serious problem on the Internet. There are two major approaches in phishing detection: the blacklist- and the heuristics-based approach. Heuristics-based approaches employ common characteristics of phishing sites such as distinctive keywords used in web pages or URLs in order to detect new phishing sites that are not yet listed in blacklists. However, these kinds of heuristics can be easily circumvented by phishers once their mechanism is revealed. In order to overcome this weakness, visual similarity-based detection techniques have been proposed. Because phishing sites have to mimic victim sites, visual similarity between phishing sites and their victim sites is supposed to be an inherent and not easily concealable characteristic. However, these techniques require images of real victim sites for detection. In this paper, we propose a phishing detection mechanism based on visual similarity among phishing sites that mimic the same victim site. Surprisingly, just by analyzing visual similarity among web pages without a priori knowledge, our method automatically extracts 224 distinct web page layouts mimicked by 2,262 phishing sites and achieves a detection rate of over 80 % while keeping the false-positive rate to 17.5 %. We also find that the false-positive rate can be reduced.
Socio-demographic insights into South African student drinking behaviour

Hazardous and harmful drinking is on the rise among adolescents and young adults and has been classified as a major health problem. University students is a subgroup of young adults that are characterised by more frequent, and even more dangerous drinking behaviours than their non-student peers and new intervention approaches are needed to foster behavioural change. The purpose of this study is to investigate the drinking behaviour and socio-demographic profile of a cohort of South African university students and propose future research avenues to address student drinking behaviour. Ex post facto survey data was collected by means of a questionnaire including the Alcohol Use Disorder Identification Test (AUDIT) and a demographic section. Data was gathered from university students (n=474) from a single campus within South Africa. Data analysis included descriptive statistics, reliability analysis, independent sample t-tests and one-way ANOVAs. Results indicate significant differences in drinking behaviour for gender groups; age; level of disposable income; type of beverage consumed, binge drinking, level and frequency of consumption. The findings have implications for higher education management, public health authorities, and academia and provide valuable insight on the socio-demographic profile and drinking behaviour of a cohort of university students. The findings serve as a foundation for future research into the development of a persuasive communications strategy (educational and prevention campaigns) that could foster much needed behavioural change.
Physical evidence supporting a ribosomal shunting mechanism of translation initiation for BACE1 mRNA

In Alzheimer disease, elevated levels of the BACE1 enzyme are correlated with increased production of amyloid peptides and disease pathology. The increase in BACE1 levels is post-transcriptional and may involve altered translation efficiency. Earlier studies have indicated that translation of BACE1 mRNA is cap-dependent. As ribosomal subunits move from the cap-structure to the initiation codon, they fail to recognize several AUG codons in the 5′ leader. In this study, we looked for physical evidence of the mechanism underlying ribosomal scanning or shunting along the BACE1 5′ leader by investigating structural stability in the 5′ leaders of endogenous mRNAs in vivo. To perform this analysis, we probed RNAs using lead(II) acetate, a cell-permeable chemical that induces cleavage of unpaired nucleotides having conformational flexibility. The data revealed that the ≈440-nt 5′ leader was generally resistant to cleavage except for a region upstream of the initiation codon. Cleavage continued into the coding region, consistent with destabilization of secondary structures by translating ribosomes. Evidence that a large segment of the BACE1 5′ leader was not cleaved indicates that this region is structurally stable and suggests that it is not scanned. The data support a mechanism of translation initiation in which ribosomal subunits bypass (shunt) part of the BACE1 5′ leader to reach the initiation codon. We suggest that a nucleotide bias in the 5′ leader may predispose the initiation codon to be more accessible than other AUG codons in the 5′ leader, leading to an increase in its relative utilization.
NOISE REDUCTION IN THERMAL IMAGERY DATA COLLECTED VIA AN AIRBORNE LINE-SCANNER By

The project looked at the reduction of noise present in thermal imagery data collected from an airborne line-scanner system. A one-dimensional line-scanning process is used to collect the imagery data. The flight profile of the data collection is an altitude of 200 feet and a forward velocity of 50 knots, and the sampling rate of the system used to collect the imagery data is 559.3kHz. It was found that approximately 15% of the imagery data collected had high frequency noise at 53kHz, 105kHz, 154kHz, and 217kHz. This noise is referred to as "platform" noise in the report. The imagery data was initially corrected, via post-processing, with a small 1x3 averaging window that is applied only when a set threshold is met. The major effect of this technique was the reduction of the four noise bands with minimal computational effort. This allowed for use of the noisy imagery data. The averaging window noise reduction technique was compared with a low pass filter, a multi-band rejection filter, and a discrete wavelet transformation. The metrics for the comparisons were the mean square error (MSE) and the signal-to-noise ratio (SNR). Qualitative analysis of the techniques was performed with the Fast Fourier transformation (FFT) and the histogram of the processed images. Four images were used to examine the noise reduction techniques. These images are two thermal images which do not contain the "platform" noise and two synthesized which are based on the thermal imagery data collected and on physical statistics of the background that was over flown. An FFT estimation of the "platform" noise was used to add "platform" noise to the four surrogate images. There are three questions that this project focuses on. The first question is what effect did the 1x3 averaging window have on the underlying image? The second question is what other techniques will perform better than the 1x3 averaging window if time is not a limitation? The final question is what effect does the use of surrogate synthetic imagery have on the evaluation of noise reduction? The multi-band rejection filter had very good results. The power of the noise at specific frequencies hindered the discrete wavelet transform from performing better in the noise reduction. -ii-DEDICATION I would like to dedicate this work to my wife, Talitha Bennett, and to my two sons, Trey and Jess Bennett. -iii-ACKNOWLEDGEMENTS I would like to thank the Lord for His guidance and direction in my life. …
IWCMSE: Integrated Water Consumption Monitoring Solution for Enterprises

Water is an essential resource for human life. Enterprises consume large amount of water and it is crucial for successful business operation. There is a constant drive to conserve water and improve water efficiency. Wireless sensor network (WSN) based water monitoring application acts as a decision support system and plays critical role in enterprises. Our proposed Integrated Water Consumption Monitoring Solution for enterprises (IWCMSE) is used to identify inefficiency in water usage and take better decisions to cut down on water wastage. The IWCMSE architecture, novel LP formulation to maximize recycled water usage and stochastic prediction model to forecast the water usage at a building level in an enterprise are described in the paper. We showcased three case studies based on real time data collection across our enterprise and the results show savings of up to 30% of water usage is achievable.
THE EFFECT OF SELF-EFFICACY AND SELF-REGULATION ON KNOWLEDGE SHARING BEHAVIOR UNDER SOCIAL COGNITIVE PERSPECTIVE

The aim of this study is to develop an integrative understanding of the factors supporting or inhibiting individual knowledge-sharing intentions. This study employs as our theoretical framework the social cognitive theory and self-regulation mechanism factors that are believed to influence individual knowledge sharing. It was found that self-efficacies affect individual self-regulation. And positive self-regulation leads to positive intention to share knowledge.
A distributed location estimating algorithm for wireless sensor networks

The location estimation is a fundamental and essential issue for wireless sensor networks( WSNs). In this paper, we assume that only a few sensor nodes (named as beacon nodes) get their locations by Global Positioning System (GPS) and the remaining nodes without GPS (named as normal nodes) need to estimate their own locations by gathering the nearby neighboring information. Existing works are either too costly or not accurate enough. To improve previous works, we propose a distributed location estimation algorithm for WSNs. In our algorithm, each node without location information only needs to collect the location information of neighboring nodes and use simple computation to estimate its location. Besides, we improve the accuracy of the normal node's estimative region by discarding the communication area of the beacon node (named as the farther neighboring beacon node), which does not cover the normal node, from the original estimative region. We derive some rules to adjust the estimative region according to the relative location of the normal node and the farther neighboring beacon node. Simulation results show that the proposed algorithm achieves better accuracy of estimative locations
Gamma frequency oscillations in rodent models for schizophrenia

Schizophrenia is a debilitating mental disorder that is characterised by a breakdown in normal thought processes, blunted emotional responses and a variety of cognitive difficulties. Gamma frequency (30 – 80 Hz) oscillations are associated with many processes that are disrupted in people with schizophrenia memory, perception and attention. This thesis aimed to develop methods and tools to investigate the basic mechanisms that underlie the alterations in gamma frequency brain activity that are observed in patients suffering from schizophrenia. To do this we developed a variety of experimental animal models for schizophrenia. We successfully demonstrated that both genetic and pharmacological changes lead to alterations in gamma oscillations and that antipsychotic medications can modulate them.
Learning to question: leveraging user preferences for shopping advice

We present ShoppingAdvisor, a novel recommender system that helps users in shopping for technical products. ShoppingAdvisor leverages both user preferences and technical product attributes in order to generate its suggestions. The system elicits user preferences via a tree-shaped flowchart, where each node is a question to the user. At each node, ShoppingAdvisor suggests a ranking of products matching the preferences of the user, and that gets progressively refined along the path from the tree's root to one of its leafs. In this paper we show (i) how to learn the structure of the tree, i.e., which questions to ask at each node, and (ii) how to produce a suitable ranking at each node. First, we adapt the classical top-down strategy for building decision trees in order to find the best user attribute to ask at each node. Differently from decision trees, ShoppingAdvisor partitions the user space rather than the product space. Second, we show how to employ a learning-to-rank approach in order to learn, for each node of the tree, a ranking of products appropriate to the users who reach that node. We experiment with two real-world datasets for cars and cameras, and a synthetic one. We use mean reciprocal rank to evaluate ShoppingAdvisor, and show how the performance increases by more than 50% along the path from root to leaf. We also show how collaborative recommendation algorithms such as k-nearest neighbor benefits from feature selection done by the ShoppingAdvisor tree. Our experiments show that ShoppingAdvisor produces good quality interpretable recommendations, while requiring less input from users and being able to handle the cold-start problem.
Digital material fabrication using mask‐image‐projection‐based stereolithography

Purpose – The purpose of this paper is to present a mask‐image‐projection‐based stereolithography (MIP‐SL) process that can combine two base materials with various concentrations and structures to produce a solid object with desired material characteristics. Stereolithography is an additive manufacturing process in which liquid photopolymer resin is cross‐linked and converted to solid. The fabrication of digital material requires frequent resin changes during the building process. The process presented in this paper attempts to address the related challenges in achieving such fabrication capability.Design/methodology/approach – A two‐channel system design is presented for the multi‐material MIP‐SL process. In such a design, a coated thick film and linear motions in two axes are used to reduce the separation force of a cured layer. The material cleaning approach to thoroughly remove resin residue on built surfaces is presented for the developed process. Based on a developed testbed, experimental studies we.
Towards an Assessment Methodology to Support Decision Making for Sustainable Electronic Waste Management Systems: Automatic Sorting Technology

There is a lack of structured methodologies to support stakeholders in accessing the sustainability aspects for e-waste management. Moreover, the increasing volume of electronic waste (e-waste) and the availability of automated e-waste treatment solutions demand frequent reconfigurations of facilities for efficient e-waste management. To fill this gap and guide such ongoing developments, this paper proposes a novel methodological framework to enable the assessing, visualizing and comparing of sustainability impacts (economic, environmental and social) resulting from changes applied to a facility for e-waste treatment. The methodology encompasses several methods, such as discrete event simulation, life cycle assessment and stakeholder mapping. A newly-developed demonstrator for sorting e-waste is presented to illustrate the application of the framework. Not only did the methodology generate useful information for decision making, but it has also helped identify requirements for further assessing the broader impacts on the social landscape in which e-waste management systems operate. These results differ from those of previous studies, which have lacked a holistic approach to addressing sustainability. Such an approach is important to truly measure the efficacy of sustainable e-waste management. Potential future applications of the framework are envisioned in production systems handling other waste streams, besides electronics.
Implementation of an Automatic Syllabic Division Algorithm from Speech Files in Portuguese Language

A new algorithm for voice automatic syllabic splitting in the Portuguese language is proposed, which is based on the envelope of the speech signal of the input audio file. A computational implementation in MatlabTM is presented and made available at the URL this http URL Due to its straightforwardness, the proposed method is very attractive for embedded systems (e.g. i-phones). It can also be used as a screen to assist more sophisticated methods. Voice excerpts containing more than one syllable and identified by the same envelope are named as super-syllables and they are subsequently separated. The results indicate which samples corresponds to the beginning and end of each detected syllable. Preliminary tests were performed to fifty words at an identification rate circa 70% (further improvements may be incorporated to treat particular phonemes). This algorithm is also useful in voice command systems, as a tool in the teaching of Portuguese language or even for patients with speech pathology.