Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Force in Single Point Incremental Forming by Using Artificial Neural Network

In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and the minimum vertical force component was selected as the model output. To train the model, a Multilayer perceptron neural network structure and feed-forward backpropagation algorithm have been employed. After testing many different artificial neural network (ANN) architectures, an optimal structure of the model i.e. 6-14-1 was obtained. The results, with a correlation relation between experiments to predicted force,-0.215 mean absolute error, show a very good agreement.
Predicting Word Maturity from Frequency and Semantic Diversity: A Computational Study

Semantic word representation changes over different ages of childhood until it reaches its adult form. One method to formally model this change is the word maturity paradigm. This method uses a text sample for each age, including adult age, and transforms the samples into a semantic space by means of Latent Semantic Analysis. The representation of a word at every age is then compared with its adult representation via computational maturity indices. The present study used this paradigm to explore to the impact of word frequency and semantic diversity on maturation indices. To do this, word maturity indices were extracted from a Spanish incremental corpus and validated, using correlation scores with Age of Acquisition and Word Difficulty indices from previous studies. The results show that both frequency and semantic diversity predict word maturity but that the predictive capacity of frequency decreases as exposure to language increases. The latter result is discussed in terms of inductive processes suggested in previous studies.
Utility in Forensic Anthropology: Findings Contributing to Case Conversion

Abstract In Approaching Utility in Forensic Anthropology, Evison, Francisco, and Guimarães (2012) propose an attrition model for the study of the impact of forensic anthropology in the justice system and consider wider implications for crime prevention and public health and safety. In this short supplementary article, brief illustrations of case findings are offered to demonstrate their significance in case progression—or conversions—in the investigative and prosecutorial process. The examples, it is suggested, support the specific arguments for improved communication and integration, feedback on evidential reliability, and tailoring of research and education to reflect caseload proposed via the attrition model, as well as policy advances that would improve efficacy in public health and safety.
Education Student Perceptions of Virtual Reality as a Learning Tool

The purpose of this study was to ascertain student perceptions of the use and value of three-dimensional virtual environments. A grounded theory approach was used to gather and examine data. Just over half of student participants reported positive experiences. However, most experienced technical difficulties. Despite the technical challenges of operating within the virtual space, the majority reported positive aspects of using the virtual space, including increased meaningful social interactions and reduced social anxiety. Overall, students reported positive experiences and value of virtual reality, but technical difficulties demonstrate the need for adequate technology and institutional technology support.
Image Enhancement Technique on Contrast Variation: A Comprehensive Review

Image enhancement is very important, especially for the analysis and diagnosis of detailed information. Most of the studies conducted in image enhancement focus on contrast normalization. Generally, contrast determines how information in images can be perceived easily, how various details in the image can be easy distinguished or how objects of interest can be located. In this paper, a comprehensive review of image enhancement based on spatial domain (Histogram Equalization (HE) and Homomorphic Filtering) and frequency domain (Discrete Wavelet Transform (DWT)) is presented. The improvement and modification of methods were explained systematically. The objective of this work was to study the advantages and drawbacks for each of the method based on a comparison of the results performance. Besides that, this research focuses on various types of applications, emphasizing the importance of contrast enhancement for the improvement of its performance, especially in terms of accuracy and sensitivity. Previous studies were reviewed and critically compared to gain a better understanding of image enhancement. New ideas for further research improvement in image enhancement were proposed.
The smartphone as an instrument for blood pressure measurement

Introduction: Number of population suffering from hypertension is increasing. So that, monitoring of this phenomenon should concentrate attention of medical industry, and receive high priority. One of the recommended procedure in hypertension treatment, and control is home blood pressure monitoring, which can be tested using smartphone application. Aim of the research: To evaluate the feasibility of a new blood pressure (BP) measurement tool – a smartphone application. Material and methods: The study included 50 subjects with the diagnosis of hypertension. Blood pressure measurement was tested in the following conditions: using a sphygmomanometer and using a smartphone by a specialist, and using a smartphone by the patient him/herself. The total number of results that differed from the measurement performed by the specialist by more than 5 mm Hg, and by 10% or more, was counted. Results: Mean results of systolic and diastolic BP did not differ significantly between measurements done by a specialist using a sphygmomanometer and those done using a smartphone application. There were 82% of results of systolic and 92% of diastolic BP that differed from Korotkoff sound technique in a range greater than 5 mm Hg and 36% in systolic and 86% in diastolic BP by 10% or more. Conclusions: The tested application should not yet be used for BP monitoring.
Efficiently High Speed Implementation of AES Algorithm on FPGA

: With the increasing number of internet and wireless communication users in any organisation, data security has become a major problem for the valuable information that needs to be protected. So to protect the user data that is being transmitted over open channels some means of resilient data protection is needed. So AES can be considered as the most widely used modern symmetric key encryption standard for such sensitive data that needs to be kept secured. This paper propounds high speed implementation of AES algorithm while maintain with the minimum amount of hardware resources. The proposed AES algorithm supports 128 bit key length. In order to achieve high speed pipelined architecture is used. The AES-128 design is implemented on FPGA with XC6SLX16-3CSG324 package using Verilog language with the help of Xilinx ISE tool.
Can Online Learning Boost Academic Performance? A Microeconomics Study

This study of the 2007 cohort of Durban University of Technology students enrolled in its introductory microeconomics course examines whether the length of time they spend in the online economics classroom is associated with different levels of academic performance. The study, using linear regression analysis, finds that performance is significantly correlated not only with gender and academic ability, but also with the length of time students spend productively in the online classroom as reflected in their achievement in online assessments. A cautious interpretation of these results is that the study offers at least modest evidence of how motivation to engage in online learning may impact on performance.
Scene segmentation with deep neural networks

In this thesis, we address the challenging task of scene segmentation, which generally refers to parsing a scene image into a set of coherent semantic regions. Scene segmentation requires multi-level scene understanding ranging from high-level semantic recognition to low-level boundary detection. Therefore, high-level contextual modeling as well as low-level information incorporation are both important in the functionality of scene segmentation models. In addition, semantic classes appear disproportionally in scene images, which further complicates the learning process of segmentation models. In this thesis, we focus on addressing these challenges inherent to scene segmentation. More specifically, we mainly explore and discuss how effective high-level context should be incorporated in scene semantic segmentation. In the mean time, we discuss how to effectively retain low-level information that are essential in accurate low-level semantic parsing. Besides, we discuss and explore the issue of class frequency imbalance, which is severe and significant in scene semantic segmentation. Accordingly, we present three works, each of which explore and address parts of these challenges individually. First of all, we adopt Patch-Convolutional Neural Network (Patch-CNN, which is trained from scratch with image patches) to be our parametric model for local patch analysis. Based on the occurrence frequency distribution of classes, an ensemble of CNNs (CNN-Ensemble) are learned, in which each CNN component is trained with different patch sampling strategy and each one focuses on learning different and complementary visual patterns. We notice that different CNN component performs significantly differently at parsing low-frequent semantic classes. Importantly, we observe a significant
Supporting Software Engineering Practices in the Development of Data-Intensive HPC Applications with the JuML Framework

The development of high performance computing applications is considerably different from traditional software development. This distinction is due to the complex hardware systems, inherent parallelism, different software lifecycle and workflow, as well as (especially for scientific computing applications) partially unknown requirements at design time. This makes the use of software engineering practices challenging, so only a small subset of them are actually applied. In this paper, we discuss the potential for applying software engineering techniques to an emerging field in high performance computing, namely large-scale data analysis and machine learning. We argue for the employment of software engineering techniques in the development of such applications from the start, and the design of generic, reusable components. Using the example of the Juelich Machine Learning Library (JuML), we demonstrate how such a framework can not only simplify the design of new parallel algorithms, but also increase the productivity of the actual data analysis workflow. We place particular focus on the abstraction from heterogeneous hardware, the architectural design as well as aspects of parallel and distributed unit testing.
An Energy Efficient Routing for Vehicular AD HOC Networks using Real-Time Perception of Node Information

Abstract Integrating recent years’ results and analyzing the VANET (Vehicular ad hoc networks), taking the important role of mobile nodes into account a vehicular opportunity route based on real-time information (VORI) is proposed. VORI uses mobile nodes to collect real time area information, and construct hot area for best inter-area selecting with the information to help delivery message. VORI is consisting of node position query and data transmission. The limited query reduces the number of query copies within the net, and with dynamically selecting hot area message delivery works well.
A Case Study of Mathematics Teachers' Use of Short-Cycle Formative Assessment Strategies

A single case study was used to examine two middle grades mathematics teachers' use of short-cycle formative assessment strategies. Data was collected using multiple sources to provide a description of this single case. Participant change in knowledge of short-cycle formative assessment strategies was collected and analyzed through participant pre- and post-interviews and targeted instructional support was provided through professional development sessions designed to meet diverse needs of participants. Participant change in use of short-cycle formative assessment strategies was collected and analyzed through classroom observations using Assess Today observation protocol and targeted instructional support was provided through post-observation conferences with written feedback. Findings from the study verified that changes in teachers' use of short-cycle formative assessment strategies were positively influenced by the targeted instructional support provided to each participant during the study. The study further indicated that an assessment of teacher's present knowledge and use of short-cycle formative assessment strategies should be considered before providing targeted instructional support to maximize the learning potential for each teacher. Future research is needed regarding the importance of building student self-efficacy through teacher use of short-cycle formative assessment, as well as the importance of involving students in the formative assessment process.
Methodology in Teaching Chinese to Speakers of Other Languages (TCSOL): Teachers’ Beliefs and Practices in Native and Non-Native Chinese-Speaking Contexts

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Exploring the use of mathematics apps in the elementary school classroom

Many reports indicate that students have difficulty in mathematics (Carr, 2012; Hinton, 2014; National Assessment of Educational Progress, 2013). Some evidence suggests that technology can help improve student performance in the field (Boogart et al., 2014; Riconscente, 2013). This study investigates how the use of digital mathematics applications (apps) in a grade 2/3 class could affect student attitudes and academic performance by assessing and comparing the quality of different apps. Five specific apps, Thinking Blocks, Sushi Monster, Math Tappers, Prodigy, and Show Me, were carefully selected based on set criteria. This study used a mixed methodology, including survey data, open-ended questions, interviews, and performance tests. Twenty students, including eleven grade 2 (six males, five females) and nine grade 3 (five males, four females), participated in this study. The results indicated the importance of focusing on specific types of mathematics apps rather than focusing on the technology itself. The students enjoyed the challenge of solving math problems and believed this helped them learn. The game-based apps, especially the micro-world type app, were some of the favourite apps that the students selected because it engaged them, provided positive feedback, and they were able to create customised characters. The students preferred to use fun and easy apps rather than those that were more complicated to use. Students’ mathematics performance significantly increased after the use of math apps, but other factors, such as the quality of the teacher’s instruction, additional use of mathematics manipulatives, and support from home could have influenced the results.
Effect of Cultivars and Sowing Dates on Nutrient Uptake and Yield of Chickpea under Aberrant Climatic Conditions in Black Soils of Central India

Field experiments were carried out in Indian Institute of Soil Science, Bhopal, India to identify the most suitable variety, appropriate sowing time and their subsequent interaction on nutrient uptake and yield performance in chickpea under rainfed conditions in black soils. There were two dates of sowing viz., first and second fortnight of November and four varieties of chickpea like, JG 16, JG 11, JG 315 and JG 218. The results shown that the nutrient uptake and yield were depending on the time of sowing. The nutrient uptake patterns showed that the first sowing date plants recorded greater nutrient uptake compared to the second date of sowing in both experiments. Among the varieties JG 315 recorded the highest nutrient uptake followed by JG 11. The yield obtained in both sowing dates shown that sowing at first fortnight of November was better and would give 14-29% more yield in chickpea. This study concluded that late sowing will reduce the nutrient uptake, dry matter production and yield irrespective of the varieties. Original Research Article Neenu et al.; AIR, 12(4): 1-11, 2017; Article no.AIR. 37624 2 Among the varieties the highest yield was recorded by the variety JG 11 irrespective of the date of sowing. and hence under late sowing conditions the variety JG 11 is preferred over other varieties.
Asymptotic performance of multiuser massive MIMO systems

This thesis addresses and identifies outstanding challenges associated with the Multi user massive Multiple-Input Multiple-Output (MU massive MIMO) transmission, whereby various system scenarios have been considered to tackle these challenges. First, for a single cell scenario, the uplink effective capacity under statistical exponent constraints, the asymptotic error and outage probabilities in a multi user massive MIMO system are provided. The proposed approach establishes closed form expressions for the aforementioned metrics under both perfect and imperfect channel state information (CSI) scenarios. In addition, expressions for the asymptotically high signal-to-interference ratio (SIR) regimes are established. Second, the statistical queueing constraints, pilot contamination phenomenon and fractional power control in random or irregular cellular massive MIMO system are investigated, where base station locations are modelled based on the Poisson point process. Specifically, tractable analytical expressions are developed for the asymptotic SIR coverage, rate coverage and the effective capacity under the quality of service statistical exponent constraint. Laplace transform of interference is derived with the aid of mathematical tools from stochastic geometry. Simulation outcomes demonstrate that pilot reuse impairments can be alleviated by employing a cellular frequency reuse scheme. For example, with unity frequency reuse factor, we see that 40% of the total users have SIR above −10.5dB, whereas, with a reuse factor of 7, the same fraction of users have SIR above 20.5dB. In addition, for a certain parameters setting, the coverage probability in the lower 50 percentile can be maximized by adjusting power compensation fraction between 0.2 and 0.5. Also, for SIR threshold of 0dB, allocating 0.25 fraction of uplink transmit power can achieve approximately 6% improvement in coverage probability in the cell edge area compared to constant power policy and about 14% improvement compared to the full channel-inversion policy. Third and last, motivated by the powerful gains of incorporating small cells with macro cells, a massive MIMO aided heterogeneous cloud radio access network (H-CRAN) is investigated. More specific, based on Toeplitz matrix tool, tractable formulas for the link reliability and rate coverage of a typical user in H-CRAN are derived. Numerical outcomes confirm the powerful gain of the massive MIMO for enhancing the throughput of the H-CRAN while small remote radio heads (RRH cells) are capable of achieving higher energy efficiency.
Modelling and dynamic simulation of CTMP plant

In this thesis, mathematical models for the process units of a chemi-thermomechanical pulping (CTMP) plant have been developed. The models were developed based on first principles and empirical modelling approaches. The models have been used to simulate the dynamic behavior of a CTMP plant. A CTMP plant is composed of four major processes: the chip pretreatment process, the refining process, the pulp processing process, and finally the bleaching process. A mill audit was performed to study the chip quality variations along the chip pretreatment process and typical variations were used for the simulation of a CTMP plant. The refining process was modelled based on the concept of specific energy and refining intensity. The model was used to predict pulp properties and handsheet properties from the refiner operating conditions. Data from mill trials and literature were compared with the prediction and there was good agreement between predicted and measured values. The effects of reject rate on fibre fractionation, freeness, and consistency through the screens were investigated and models were developed. In modelling the bleaching process, a kinetic model was used to relate the final pulp brightness to the hydrogen peroxide charge, temperature, and retention time. The flow pattern of the pulp stock in the bleaching tower was studied and modelled as a combination of continuous stirred tank reactors and a plug flow reactor. The dynamic simulations revealed the impact of the major disturbances and operating conditions on the performance of the whole pulping process. Control strategies have been proposed and tested for the bleaching plant. This work has systematically studied the dynamics of a CTMP plant and brought a thorough understanding of the dynamic behavior of the plant. The models developed in this work can be used as a tool for process modification, process operation, and process control.
Exploring Users' Experience of the Web

web, user studies, interview study, design While browsing the Web is a widespread everyday activity there is a shortage of detailed understanding of how users organise their Web usage. In this paper we present results from a qualitative in-depth interview study of how users browse the Web and combine browsing with their other activities. The data are used to explore three particular problems which users have with browsing the Web. Firstly, users have problems managing their favourites, and in particular accessing their favourites through a hierarchical menu. Second, users have problems with combining information across different Web sites what we call the “meta-task” problem. Third, users have concerns with security and privacy, although these concerns seem to change as users become more experienced with shopping on the Web. We discuss three concepts which address these problems: “home page favourites”, “Web clipping” and the “Web card”. These concepts are attempts at incremental improvements to the Web without affecting the Web's essential simplicity.
A method for revocation in group signature schemes

A group signature scheme allows any group member to sign on behalf of the group in an anonymous and unlinkable fashion. In the event of a dispute, a designated trusted entity can reveal the identity of the signer. In this paper we propose a revo-cation method for group signatures based on the group signature scheme from [12]. This method requires no time periods and oﬀers constant length signatures