Miracle-dz/UniFAR-FTUs huggingface dataset:
Where to search for Alzheimer’s disease related changes in PET scans?

The development of non-invasive techniques for the early diagnosis of Alzheimer’s disease are of high importance facing the growing number of affected persons and the immense cost to our society caused be dementia. Computer based analysis of FDG-PET scans might become a possibility to make early diagnosis more efﬁcient. Temporal lobe is the the main location of medical ﬁndings. We have clues that in PET images the parietal lobe contains more information about Alzheimer’s disease. We used a probabilistic brain atlas to include prior information about the localization of changes in the human brain, classiﬁed Alzheimer’s disease versus normal control group and got better classiﬁcation rates focusing on parietal lobe.
Materialistic (and unhappy?) adult now, economically deprived child then: How are felt formative economic deprivation, materialism, and well-being measures related?

According to the US Census Bureau, in 2010, one in five children lived in poverty. The role of economic deprivation during childhood and its implications during adulthood has been explored by several researchers (e.g., Mheen et al., 1998). Of particular interest for the present study is to explore the role of economic deprivation and its relationship with materialism and well-being measures. Scholars (e.g., Inglehart, 1990) have maintained that economic deprivation experienced during childhood and adolescence years might lead to an adult who is materialistic, which has been linked to diminished level of life satisfaction (Wright and Larsen, 1993) and subjective wellbeing/happiness (Kasser, 2002). In other words, in the light of the rising numbers related to children living in poverty and findings from various research studies – it could be expected that the substantial proportion of the US population (also elsewhere) will be materialistic and consequently dissatisfied and unhappy in their lives. Thus, the present study explores the relationships between economic deprivation, materialism, and well-being measures.
Stochastic Process on Option Pricing Black-Scholes PDE– Financial Physics (Phynance) Approach

Phynance has often been perceived as a field, which incorporates both finance and physics aspects for facilitating proper understanding promotion concerning various economic aspects [1]. In this case, physics knowledge is usually applied towards explanation of experienced economic conditions. Economists realize that economic theories, which were traditionally formulated, have no capacity to offer substantial explanations regarding experienced conditions hence the need to turn to some theories found within physics, which have the capacity to bring about suitable explanations regarding experienced economic situations. This is usually essential as it makes it possible for substantial solutions to be sought regarding experienced challenges. The main objective of this study is to Construction of stochastic calculus on Option Pricing Black Scholes PDE through phynance approach. The main goal of this study is fourfold: 1) First, we begin our approach to briefly present the financial derivatives securities (i.e. Option Contract). 2) Next we extent this approach to introduce the fundamental derivations of the Black Scholes model for the pricing of an European call option. 3) Then we reinterpreted the Black Scholes in the formalism of Quantum mechanics. 4) Finally, we construct the mathematical model for Black – Scholes equation on Heat equation by use of derivatives calculus.In addition, this paper ends with conclusion.
Cost and Returns Analysis for Small-scale Dry Season Tomato Production in Onitsha Agricultural Zone of Anambra state

The study analyzed the cost and returns of dry season tomato production by small scale farmers in Onitsha Agricultural Zone of Anambra State, Nigeria. Eighty farmers were randomly selected for the study and data were analyzed, using descriptive analysis and profitability analysis. The results showed that the mean age of the farmers was 42 years, implying that they were in their productive ages. The respondents were fairly educated as about 45 percent of them had secondary school education. The result of the profitability analysis revealed average gross margin and net income of N670,103.72 and N657,454.62 for tomato intercrop farmers respectively; average gross margin and net margin of N589,910.14 and N577,261.04 respectively, for sole tomato enterprise farmers respectively. This indicated that dry season tomato production was a profitable venture in the study area. The analysis further identified inadequate farm credit and poor storage facilities as the main problems faced by the farmers. The study therefore recommends that farmers should be encouraged to form cooperative societies so as to enable them obtain loans from commercial banks and agricultural banks at regulated interest rates. Government should also focus research on viable methods of storing tomatoes and other vegetables, so as to encourage farmers to produce more and ensure food security.
Pengaruh Konsentrasi Doping terhadap

The luminance of Zinc Oxide materials has been synthesized using the phase solution method. The calcination process is carried out at a temperature of 800◦C. Performed phase identification, optical characterization, and luminance intensity generated by ZnO synthesis results. Addition of doping was done by using doping concentration of 1%, 3%, and 5% with a calcination temperature of 300◦C to obtain ZnO: Zn. We do phase identification and optical characterization of the three samples produced. The intensity of luminescence was tested to determine the effect of adding doping concentrations to the emissions produced by luminance materials ZnO: Zn. Obtained luminance material results emit green emissions with 510 nm to 535 nm wavelength range. The higher the doping concentration will be the more activators (doping) in the host (ZnO) that absorbs the energy for the excitation process so that the higher emission intensity emitted. KATA KUNCI: Luminisensi, zinc oxide, solution phase http://dx.doi. org/10.12962/j24604682.v14i1. 3554
Temporal Sequence Classiﬁcation in the Presence of Background Domain Knowledge

In the last decade there has been a huge interest in classifying temporal data. Temporal data is usually associated with high dimensionality, feature correlation and large amounts of noise, making the classiﬁcation task a challenge for the research community. Sequence classiﬁcation methods are one of the techniques applied to solve this problem taking into consideration the temporal order of the sequence. However these methods do not use domain knowledge to learn meaningful information. In this work, we describe the main approaches for sequence classiﬁcation and propose the adaptation of one of these techniques, Shapelet Decision Tree, through the incorporation of domain knowledge in its training process. With this adaptation we aim for providing the new classiﬁer with the ability of better dealing with the underlying relations between data that are known to exist in a given domain
Green Synthesis of Silver Nanoparticles from Murraya Koenigii Leaves Extract

The green synthesis approach was used for synthesis of silver nanoparticles. The Murraya koenigii leaves were used as reducing agent for (1mM) silver nitrate. The UV-Visible spectrum of synthesized silver nanoparticles shows peak at 428nm . Transmission electron microscope analysis shows polymorphic nature of silver nanoparticles with mean size of 18nm.The Selected area diffraction pattern shows its polycrystalline nature The functional groups present were known by FTIR studies. The antioxidant activity was checked and IC50 was found to be 90. 80μg/ml.
I Play, You Play: A Framework for Card Games in a Multi-touch Table

Card games have been around for thousand of years. There are countless variations of games and a large number of diﬀerent families. Usually, people gather around a table to play card games, but with the appearance of video games the social aspects of the traditional card game have undergone a transformation. Researchers have been trying to blend the traditional and modern facets of card games by extending the traditional game with technology. The proposed framework provides a set of tools for the development of tabletop card games played using tangible playing cards. Moreover, autonomous agents can be integrated into the games and play them. The Sueca card game was built to test the capabilities of the framework. The hardware’s limitations prevent a ﬂawless detection and recognition of the cards, using ﬁducial markers. Nevertheless, the achieved results demonstrate the percentage of incorrect detections can be decreased and have a limited inﬂuence during the games.
NEW CONCRETE MIX DESIGN APPROACh

Design of concrete mixes may be defined as a process of selecting suitable ingredients of concrete and determine their relative quantities. The selection of concrete ingredients involves a balance between economy and performance. Currently, there are many international methods approved world-wide for mix designs, such as: the American Concrete Institute (ACI) method and the British Standard (BS) method. These methods depend on certain equations and graphs based on mathematical analysis of results obtained from previous field experience (are they not empirical? For some of them). In general, mix design methods give some indication to the designer to validate and adjust the mix constituents via experimental mixes in the local laboratories in order to check the variables related to the characteristics and properties of the local materials and the surrounding environment conditions. This paper illustrates a new approach for concrete mix design named as:“Double Coating Method”, which is currently used in some research centres in the republic of Poland and was recently applied in the laboratories of the Civil Engineering Department in the University of Tripoli in Libya. Results obtained by this method and the ACI approach, using the local materials subject to local environmental conditions are presented and discussed.
LKALE SIG MEETING 2019, OXFORD Speakers and Abstracts Scaffolding Academic Reading in Higher Education: Communicating Expectations and Modelling Engagement

In recent decades, efforts to increase higher education participation for students from traditionally underrepresented backgrounds have resulted in greater linguistic and sociocultural diversification of Australian universities. While the success of targeted scholarship, admission, and bridging programs for facilitating more equitable entry to higher education is well documented, widening participation initiatives must also involve the provision of focused language and literacies support as students move beyond university entry to participate in ‘mainstream’ higher education. A growing body of research indicates that, once completing bridging courses or enabling pathways into university, many students from traditionally underrepresented backgrounds struggle with the tacit assumptions and hidden cultural values associated with academic literacy practices. Reading is identified as a particularly challenging aspect of engagement for students unfamiliar with the expectations and assumptions surrounding literate practices in the academy. This presentation reports on research undertaken at a large, regional university in Australia, characterised by higher than average numbers of learners from traditionally underrepresented backgrounds. Taking an academic literacies approach, the study focused on academics’ perceptions of specialist language and discursive practices in their discipline, their opinions regarding the linguistic needs and strengths of learners, and their expectations regarding students’ academic reading practices. This presentation will discuss the practical strategies and approaches employed by discipline specialists when seeking to scaffold academic reading and critical engagement with text within content-area teaching. The discussion will also provide the opportunity to consider larger questions of institutional responsibility and the role of academics in the linguistically diversified university.
Speech Recognition for a Small Aerial Robot

Unmanned Aerial Vehicles are aircrafts that allow the gathering of data in remote areas of difﬁcult access. Capturing audio signals with a drone triggers a series of new applications such as in the ﬁeld of Search and Rescue. The reason why Speech Recognition hasn’t been widely developed for drones is the corrupting noise the engines add to the speech signals. The main goal of this research is to present a study on how to overcome the bad speech recognition performances due to this speciﬁc type of additive noise. The implementation and testing of Wiener Filter, Least-Mean-Square Adaptive Filter, Noise Gate, Motion-Dependent Spectral Subtraction and Discrete Wavelet Transform was done for different levels of Signal-to-Noise Ratio. Due to the very promising results, the Least-Mean-Square Adaptive Filter is chosen for further improving a Speech Recognition System. A Feedforward Neural Network that predicts the ﬁlter’s coefﬁcients from the information on the velocities of the 4 motors is developed and integrated in the system resulting in a better performance. The last proposal of change in the ﬁlter is using as input two signals with different Signal-to-Noise Ratio values instead of the noisy speech and the noise-only speech signals. Lastly, a Recurrent Neural Network for Speech Recognition trained with speech corrupted by the drone’s ego-noise was also tested but this approach didn’t show to be competitive with the previous implementation. Experimental results show that using the Least-Mean-Square Adaptive Filter with ﬁlter’s coefﬁcients computed by a Neural Network and using two noisy signals with different Signal-to-Noise Ratio values is a good solution for the problem explored and presents robustness against the high levels of noise present.
An Implicit Tensor-Mass Solver on the GPU for Soft Bodies Simulation

The realistic and interactive simulation of deformable objects has become a challenge in Computer Graphics. In this paper, we propose a GPU implementation of the resolution of the mechanical equations, using a semi-implicit as well as an implicit integration scheme. At the contrary of the classical FEM approach, forces are directly computed at each node of the discretized objects, using the evaluation of the strain energy density of the elements. This approach allows to mix several mechanical behaviors in the same object. Results show a notable speedup of 30, especially in the case of complex scenes. Running times shows that this efficient implementation may contribute to make this model more popular for soft bodies simulations.
Enterprise Information Architecture Patterns for Government

—Currently, there isn’t a speciﬁc method to ﬁnd patterns for Enterprise Information Architecture (EIA) in the area of Government. The goal of this work is to investigate the use of patterns and anti-patterns and propose a method to generate Enterprise Information Architecture patterns catalog for the Portuguese Government. Using patterns the organizations are expected to document proven practice solutions for recurring problems in a given context, in order to be used when creating new Enterprise Information Architecture in future projects. To accomplish that, we propose a ﬁve-phased method to generate patterns which involves the selection of Enterprise Information Architecture documents with similar context, the comparison between them using an iterative process with weighted similarity rules, the generation of the pattern, classifying it as a pattern or anti-pattern, and the documentation of it. For demonstration purposes, an example based on a practical case is shown. Evaluation was made using interviews and surveys, and also by comparison with other Enterprise Information Architecture approaches.
Low Temperature Nickel Induced Crystallization of Amorphous Silicon Nanorods on Silicon and Glass Substrates

In this work, crystallization of amorphous silicon (a-Si) nanorods was done by metal induced crystallization (MIC) method at low temperature (500oC) suitable for circuit applications and low cost, disposable biosensors. The crystallization of a-Si nanorods was investigated by Raman and TEM methods. These data showed oriented crystallized Si nanorods have been obtained by metal induced crystallization (MIC) method on different substrates, which can be suitable for 3D integrated circuits, optical and electrochemical applications. This simple method can be used to produce silicon nanorod arrays with high quality suitable for nanoelectronic and optoelectronic applications.
Smart Gait

This paper presents a new gait and stationary assistant based on sensing and providing feedback through the use of of-the-shelf devices, like smartphones and smartwatches. Ataxic and healthy individuals’ inertial data was collected with these devices by following a protocol based on the Timed 25-Foot Walk standardized assessment test. This data was analyzed, synchronized and used to build Neural Network models able to identify balanced and imbalanced moments with an accuracy of 99.18%, 98.61% and 98,04%, respectively, at rest, walking, and both at rest and walking. In addition, these models were developed to be able to perform real-time inferences with these devices and a data synchronization algorithm was developed. From these results, this feedback system was considered to be promising in identifying imbalances with high accuracy, therefore not disturbing the users in balanced conditions. Author
Vision Based Pose Computation from Landmarks: an application to Quadrotors

Worldwide, UAVs have become an important tool for the realization of different tasks that, otherwise, would have to be performed by humans in, sometimes, difficult and dangerous conditions. Even so, there is plenty of space for improving the technical capabilities and functionalities of these vehicles. Particularly, this thesis aims at the development of a module for providing pose error measurements to help stabilize the vehicle’s position when it is airborne. This module is composed by lightweight hardware components that can easily be attached to an UAV and uses visual information acquired by a camera for error estimation. The first part of this thesis presents the theoretical background needed to the rest of the work developed. Consisting of some basic computer vision concepts such as camera models and image transformations and the description and analysis of features detectors and descriptors algorithms. The second part presents the developed solution, its implementation and the experimental results. The developed module was attached to a robotic arm and, by closing the loop with a control feedback law, the tests performed shown that the end effector’s pose error is correctly estimated and can be driven to zero.
F-formations and collaboration dynamics study for designing mobile collocation

Mobile devices offer great opportunities in the field of collaborative learning for providing digital information while still supporting social interactions between group members. We designed and tested an orienteering mobile learning game to better understand how device use shaped collaboration in highly mobile conditions. The study involved four groups of three students all equipped with tablets. We focused our analysis on the relationship between participants' arrangements (F-formations), their device usage and coordination mechanisms (i.e. awareness, regulation, information sharing, and discussion). Our results emphasize the importance of considering the transitions between arrangements. From these observations we derive recommendations for the design of relevant interactions techniques for mobile collaborative activities.
Model Order Reduction for Aircraft Structural Analysis

The order, or dimension, of the structural dynamic models applied to airframe structures is considerably high. Consequently, the computation time involving these models can become unsustainable when it comes to MultiDisciplinary Optimization, like in the case of the NOVEMOR platform. This thesis studies the possibility of reducing the mentioned airframe models, thus resulting in a precise solution, but with less computational time spent in the solving process. Firstly, a research on the reduction methods was made, with focus on the ones which had applications to structural dynamics. This research revealed the prevalence of methods which used the concept of generalized coordinates. The vector basis which defines the vector space of these coordinates are formulated using Ritz vectors, free vibration eigenmodes or proper orthogonal modes. After defining this basis, the reduced models can be formulated using techniques like the Galerkin Projection or the Least Mean Square Reduction. After this research, some reference models were chosen and the most adequate reduction methods were applied to them. As a result of this implementation, a better understanding of the behaviour of these methods was obtained and an adequate selection of these reductions could be made in order to achieve the goal of this thesis: reducing an airframe structural model. A wing structure model from a commercial aircraft was formulated as a case study. The reduction methods applied in this model used the two techniques already mentioned above, exploiting the proper orthogonal modes. The reduction of this model resulted in a considerable decreasing of the computation time necessary for its solving process, maintaining, however, the precision of the solution.
Mobility Patterns through a Mobile App for Public Transport Users

—Today’s transportation systems rely more and more on the ability to offer a quick and nonrestrictive experience to their users. To allow for such an experience the need to make available relevant information to be utilized to facilitate the interaction of user and operator, must to be observed. In order to facilitate this transaction of information, this work will shows in the form of an Android application, that it is possible to create a system capable of gathering information about the mobility patterns of a public transportation user with the intent of improving the decision making process both users and operators make when interacting. This solution will focus on offering a low cost system to operators that is easy to implement on their existing systems, and seamless in the form it gathers information from the users.