Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing Rapid Quenching Electronics for Coupling an Ion Trap to a Mass Spectrometer

The Standard Model is a profound collection of knowledge in the realm of physics which aims to define and explain the building blocks of matter. Amidst the clarity and power that the Standard Model grants, there are still remaining ambiguities about the fundamental particles that make up our existence. These ambiguities revolve around the elusiveness of dark matter and gravity. Leading theories predict the time-variations of fundamental constants as a key location where light may be shed and answers may be found to uncover the nature of these fundamental particles. Molecules have been realized as a potential hotbed of information, as their sensitivities to nuclear motion may be exploited to reveal how with time, fundamental constants such as the electron-to-proton mass ratio (μ) can be altered to some precision. Using a radiofrequency ion trap as the residence for molecular ions and the sympathetically cooling atomic ions, a Coulomb crystal can form. Through resonanceenhanced multi-photon ionization (REMPI), state-selected O2 ions are created. Then the vibrational transition is probed. Photons may drive the following dissociation, priming the particles for detection on a time-of-flight mass spectrometer (TOFMS). There the particles’ masses may be precisely measured to determine if the vibrational transition was effectively driven. With this data we may learn more about the time variations in the electron-to-proton mass ratio. In this thesis I describe the design of the electronics which will couple the ion trap to the TOFMS. This description includes background into the ultimate mission and theory of relevant concepts. In addition, the design process in practice will be outlined in detail, and further information on future ambitions will be delineated. The design centers around three main portions of the circuit. First is the tank circuit, which drives the trapping radiofrequency (RF) signal to the electrodes of the trap. Second is the quench circuit, which actively quenches, or stops, the RF signal. Third is the extraction voltage (EV) circuit, which drives high voltages to the electrodes for dispensing the ions out of the trap and towards the TOFMS. I demonstrate the use of the electronics by trapping ions and effectively switching from the radiofrequency voltage to the high voltage. I lay the path for future work to attach the TOFMS to the ion trap vacuum chamber and achieve successful extraction and detection of the ions. With this technology we aim to obtain measurements which may answer some of the compelling questions around the Standard Model, and illuminate new physics.
Playing tic-tac-toe using a modified neural network and an improved genetic algorithm

This paper presents an algorithm of playing game tic-tac-toe. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (GA). In the proposed NN, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer that enhances the learning ability of the network. It will be shown that the proposed NN and GA provide a better performance than the traditional approach.
DeepSketch : Fast Sketch-Based 3 D Shape Retrieval

Freehand sketches are a simple but powerful tool for communication. They contain rich information to specify shapes, and thus retrieving 3D shapes from 2D sketches has received considerable attention in the field of computer graphics and computer vision. In this project, we present a system for cross-domain similarity search that helps us with sketch-based 3D shape retrieval. Instead of using hand crafted features for searching, we propose our DeepSketch neural network that is built on Siamese network to learn features that are basis for later similarity search using K-nearest Neighbor (KNN). We further did analysis on how individual strokes of a sketch image affect retrieval results, and also visualized features learned from our DeepSketch network.
Detecting Anomalies In Time Series Data

Anomaly detection has shown to be a valuable tool in a variety of application domains, e.g. detecting credit card fraud, network intrusion and sensor malfunction. This thesis provides an anomaly detection algorithm as a monitoring aid applied to time series data from the pulp and paper industry, developed for the company Eurocon MOPSsys AB. The algorithm is designed to be generally applicable to the targeted time series by providing methods for adapting parameters to the input data. The anomaly detection algorithm runs in an unsupervised setting using a statistical approach for detection. The algorithm works by fitting a statistical model to a training set of a given size and computing control limits for extracted features of the data. An anomaly is said to be found if a feature falls outside of its limits that are constantly updated to adapt to the current data. The thesis also gives an algorithm that detects changes in the trend of the time series by investigating residuals of linear fits to calculated trends of the data. The time complexities of the algorithms are linear in training size which make them suitable to run in an online environment. The algorithm was evaluated using time series data provided by MOPSsys consisting of both laboratory and sensor values. As an aid for the evaluation, the time series were inspected visually to manually label deviating patterns. The anomaly detection algorithm is shown to be able to find these deviating patterns. However, it could not be determined whether these patterns are anomalies with respect to the underlying process as no labelled test data was available. Changes in the trend were also found to be in agreement with the beforehand expected outcome. The developed algorithms show promising results but need labelled test data to give a more accurate evaluation of its performance.
The Effects of a Mini-Band Warm-Up, a Medicine Ball Warm-Up and Static Stretching on Lower Body Power

23 Introduction.23 Experimental Approach to the Problem.26 Subjects.26 Procedures.27 Statistical Analysis.30 Results.30 Discussion.30 Practical Application.32 CHAPTER V. DISCUSSION AND CONCLUSIONS.34 REFERENCES.36 APPENDIX A. INSTITUTIONAL REVIEW BOARD APPROVAL.44 APPENDIX B. INFORMED CONSENT DOCUMENT.45 APPENDIX C. DATA COLLECTION SHEET.48 APPENDIX D. DESCRIPTION OF THE WARM-UP EXERCISES.49 Mini-Band Warm-ups.49 Dynamic Medicine Ball Warm-up.50 viii Static Stretch Warm-up.52
Distributed Subgraph Matching on Timely Dataflow

Recently there emerge many distributed algorithms that aim at solving subgraph matching at scale. Existing algorithm-level comparisons failed to provide a systematic view of distributed subgraph matching mainly due to the intertwining of strategy and optimization. In this paper, we identify four strategies and three general-purpose optimizations from representative state-of-the-art algorithms. We implement the four strategies with the optimizations based on the common Timely dataflow system for systematic strategy-level comparison. Our implementation covers all representative algorithms. We conduct extensive experiments for both unlabelled matching and labelled matching to analyze the performance of distributed subgraph matching under various settings, which is finally summarized as a practical guide.
A Circular Polarization RFID Tag for Medical Uses

The aim of this paper is to present Radio Frequency Identification (RFID) Tag. The use of this kind of antennas in the medical field has a great importance in making people's life easier and improving the way to get medical information. This article is dedicated to explain the details of the method used to obtain the circular polarization using a shaped cross slot. A simulation study with the SAR values is performed to obtain an idea about the effects of the electromagnetic waves. In this study, a specific diode pin CPINUC5206-HF has been used in order to obtain a high frequency (3 GHz). Two fabrication methods have been adapted: the printed circuit board method (PCB) and metal cutting through laser ablation method (MCTLA). A comparison study between the two methods has been also conducted.
VISION BASED DYNAMIC GESTURE RECOGNTION AND ITS APPLICATION IN HUMAN-HUMANOID ROBOT INTERACTION

Gesture recognition is an important component in human robot interaction. This paper realized a command gesture recognition architecture based on optical flow PCA and DTW for a stereo vision system SFBinoeye. The recognized gesture command was used to control humanoid robot SFHR's arm to move correspondingly. Optical flow is computed using block relative algorithm, which is then handled with PCA to get continuous projection coefficients with lower dimension. The projection coefficients are combined with the center position of hand as complex feature vector. A new weighted distance is defined in DTW, which is used for gesture pattern match. The proposed gesture recognition architecture is tested on 9 gestures with of recognition 92.4% rate. This architecture is successfully applied in the control of robot arm.
Influence of Crystallization and Ageing Time on the Reproducibility of Mesoporous Molecular Sieve SBA-15

The study aimed to assess how the crystallization and ageing times in SBA-15 synthesis influence the reproducibility and particle size of mesoporous molecular sieves. X-ray diffraction showed that higher crystallization times provide greater reproducibility of mesoporous silica, due to the fact that there is no significant variation in the width and intensity of peaks, while the same is not true for shorter crystallization times. Ageing time does not seem to exercise a significant influence when higher crystallization times are used in the synthesis. Scanning electron microscopy observations revealed that shorter crystallization times led to larger crystals in addition to the formation of large agglomerates, whereas with higher crystallization times the trend is to obtain smaller and more uniform grains. It is proposed that hydrogen bonds may be responsible for the formation of smaller particles and it is also established that depending on the synthesis conditions the reproducibility of the process can become low. Keywords: reproducibility, SBA-15, crystallization time, ageing time.
First language transfer in the acquisition of English prepositions by Jordanian EFL learners

Language transfer has an immense influence on all subsystems of the second language. Traditionally, the concept of language transfer was viewed as the effect of first language on the acquisition of the second language. Language transfer can be categorized into two types; negative transfer which stems from differences between first language and target language and positive transfer which results from similarities between two languages in contrast. This study aimed primarily at investigating negative Arabic transfer in the acquisition of English prepositions by Jordanian EFL learners. English prepositions constitute a learning problem for Jordanian EFL learners. Fill-in-the-blank test, grammaticality judgment and correction task and cloze test were used to collect data. A total of 355 Jordanian EFL learners at bachelor degree level participated in this quantitative study. The respondents were selected from ten universities in Jordan via cluster random sampling procedures. The study revealed the following main findings; negative Arabic transfer affected the acquisition of English prepositions. About 35.2% of prepositional errors resulted from negative Arabic transfer. The acquisition of English prepositions was influenced noticeably by intralingual interference. It was found that 64.8% of prepositional errors were ascribed to intralingual interference. The results also revealed that preposition combinations was the most difficult usage of English prepositions for Jordanian EFL learners. The proportion of errors in the use of preposition combinations was 65.2%. With reference to the use of pied-piping and preposition stranding in interrogatives, the analysis displayed that the respondents showed no preference of pied piping over preposition stranding and vice versa. The results of the study supported the moderate position, which holds that both language transfer and intralingual interference interact in shaping the acquisition of English prepositions. The study has some implications for textbook authors and the teaching of English prepositions to EFL learners.
A Microfluidic Mixer for Chaotic Mixing of Magnetic Particles

A numerical simulation is carried out in order to investigate the efficiency of a microfluidic mixer for chaotic mixing of the magnetic particles. Lagrangian tracking method is utilized to obtain the trajectories of the particles in the mixer domain. Two characterizing indices are computed for a range of the operating parameters of the mixer. Intensity of segregation is calculated to measure the ability of the device to spread the particles and to obtain the local concentration. Moreover, in order to examine the chaotic features in the micro-mixer, largest Lyapunov exponent is computed as the supplemental characterizing index. Simulation results show that optimum operating conditions for the mixer is obtained when the Strouhal number is less than 0.6, which corresponds to the largest Lyapunov exponent of about 0.37.
An Automatic Attendance Checking System using Smartphones: An Infrastructureless Approach

—In this paper, we design and implement an attendance checking system that can automatically check whether students with their smartphones are inside the classroom or not. We seek to ﬁgure out the geospatial relations of the students by making their smartphones transmit and receive the beacon frames of the Bluetooth Low Energy (BLE) technology. To this end, we measure how BLE signals attenuate and how obstacles affect the propagation of the BLE signals. Based on the observations, we design the attendance checking system that can estimate whether the students are inside or outside the classroom. The BLE measurements of the smartphones are combined and used to classify the students by K-means clustering. By conducting experiments in real testbeds, we demonstrate that our system can successfully check the attendance of students.
Study on PSO algorithm in solving grid task scheduling

In order to resolve the resources management in dynamic heterogeneous environment,a kind of task schedul-ing model for grid environment was proposed.The model considers the computing resources,storage resources and bandwidth resources of current virtual organization in grid,and the optimal target of the model is to achieve the max-ratio and the min-cost of the above three kinds of resources,viz to build the min-max function.To compare with GA(genetic algorithm),PSO(particle swarm optimization) was applied in solving the min-max function so that the ratio of using re-sources and the efficiency of scheduling task are enhanced.Meanwhile,with the rise of iterative times,the searching speed,optimization ratio and avoiding pre-maturity are also distinctly enhanced.
Prediction of Soil Loss using SLEMSA and USLE Erosion Models for an Agricultural Field in Makurdi , Benue State , Nigeria

A field experiment was conducted at the Teaching and Research Farm of the College of Agronomy, University of Agriculture, Makurdi (Latitude 7 o 46‟ – 7 o 50‟N and Longitude 8 o 36‟ – 8 o 40‟E) during the 2015 and 2016 cropping seasons. Soil erosion plots (runoff plots) were set up under a slope gradient of 2.5 % to estimate soil loss using Soil Loss Estimation Model for Southern Africa (SLEMSA) and Universal Soil Loss Equation (USLE) erosion models under rainfed condition. Soil management practices namely, bare fallow (control), 4 and 8 t/ha mulched maize, maize + cowpea and unmulched maize were replicated three times. The data collected on soil loss was analyzed using analysis of variance test based on randomized complete block design (RCBD). Under direct measurement, higher soil loss was observed under the bare fallow plots followed by unmulched maize treated plots compared to the cover management treated plots, while lower values of soil loss were noticed under 8 t/ha mulched maize management. The values of soil loss ranged from 0 – 31.8 t/ha/yr during the two cropping seasons. The moderate to higher soil loss values (13.9 – 31.8 t/ha/yr) obtained under the bare fallow plots were beyond the tolerable limit of 12.5 t/ha/yr. Soil loss estimated using SLEMSA and USLE models indicated very low (tolerable) ratings under cover management practices. Correlation analysis between the soil loss values estimated by the SLEMSA and USLE showed high positive significant correlation (r = 0.982) and (r = 0.99) in 2015 and 2016 respectively.
COMP4801 Final Year Project Plan

The intermediate goal for this project, is to apply deep learning techniques to perform semantic segmentation of videos captured from in-car cameras based on the state-of-art models and algorithms. Specifically, we will first select a suitable semantic video segmentation dataset to perform training and testing of machine learning models in our further work, and then investigate the high-performance approaches recently developed by other researchers. An evaluation will be made on these models in terms of their efficiency and accuracy, and comparison will be made to check the difference made by their distinctive models, algorithms and system architectures. In this way, advantages and deficiencies of the existing methods could be exposed and verified, and possible ways of improvement and modification could be discovered for further experiment.
Towards An Arguing Agents Competition : Architectural Considerations

The primary purpose of this paper is to contribute to the discussion regarding the nascent Arguing Agents Competition (AAC) by exploring some of the issues relevant to the creation of a distributed online Competition. A secondary goal is to outline the implementational work that is currently underway and both to spur interest in contributions towards the development of the AAC architecture and to elicit participation in the eventual, resulting competitions. To achieve these ends an architecture for supporting a persistent, distributed, online AAC is introduced that is rooted in an extant computational argumentation game. Following this some issues relevant to such an approach are explored.
Social capital based fisherman empowerment in Lombok Utara regency , Indonesia

This article discusses the empowerment of fishermen who rely on social capital in Indonesia, especially Lombok Utara regency. Fisherman empowerment is conducted by depending on social capital that includes network, cooperation, local institution and local leadership empowerment. That social capital has been through interpretation, redefinition, and influence from the recently emerged social powers. The results of the redefinition and influence are the growing social awareness towards cooperation, the establishing of new and old network within the daily interaction and communication among the fishermen, such as the “transformation’ from begibung to fishermen community. It also results in the growing of new life principles, such as the reconstruction of merariq which gives birth to the acculturation of marriage system, cooperation between old institutions with formal organizations like the cooperation between Banjar with its family welfare education and local leadership empowerment. The study was conducted by using qualitative methodology.
Generating Realistic Facial Expressions through Conditional Cycle-Consistent Generative Adversarial Networks ( CCycleGAN )

Generative adversarial networks have been widely explored for generating photorealistic images but their capabilities in multimodal image-to-image translations in a conditional generative model setting have been vaguely explored. Moreover, applying such capabilities of GANs in the context of facial expression generation conditioning on the emotion of facial expression and in absence of paired examples, to our knowledge, is almost a green field. Thus, the novelty of this study consists in experimenting the synthesis of conditional facial expressions and we present a novel approach (CCycleGAN) for learning to translate an image from a domain (e.g. the face images of a person) conditioned on a given emotion of facial expression (e.g. joy) to the same domain but conditioned on a different emotion of facial expression (e.g. surprise), in absence of paired examples. Our goal is to learn a mapping such that the distribution of generated images is indistinguishable from the distribution of real images using adversarial loss and cycle consistency loss. Qualitative results are presented, where paired training data does not exist, with a quantitative justification of optimal hyperparameters. The code for our model is available at https://github.com/gtesei/ccyclegan.
Survey of data provenance technique

Data provenance is a hot research issue these years. This paper introduced its concept and profile of this field first based on related works. Then divided it into two parts,one was the model in open world which including two typical formal model,the other was the model in closed world,which including database provenance models and workflow provenance models. After this,it compared over ten provenance systems in technical side. At last proposed some promising aspects of this field.
Land snail assemblage patterns along motorways in relation to environmental variables

Motorways are one of the widespread and frequently discussed landscape features, especially in Central Europe. We established three transects along the three main motorways in southeastern, southwestern, and northern directions from Prague (D1, D5, R10). These transects covered major environmental gradients of geographical position, altitude, succession, and vegetation cover. Altogether 44 land snail species (more than 26 % of the Czech Republic’s land snail fauna) were found at the 45 sites on the verges along 225 km of motorways. Surprisingly 21 % of species were such included in the Red List of the Czech Republic’s molluscs, and the endangered species Daudebardia brevipes was even present by a very abundant population. We expected the motorways to be of importance as man-made linear structure for the spreading of invasive and synathropic species, but only one such species has been found Monacha cartusiana. Our hypothesis about assemblages made up of invasive or synantropic species was not verified. The most important factors were: geographical position, altitude, vegetation cover (especially presence / absence of shrubs), and succession stage explained by the age of motorway construction. We distinguished three main groups of land snails: species of open stands, and two groups of woodland species. The representation of open country species and ubiquitous species in the land snail assemblages of motorway verges is higher than in the fauna of the Czech Republic as a whole. The occurrence of sensitive species increased in stands covered by natural vegetation contrary to the outplanting.
FORENSIC VOICE COMPARISON USING LONG-TERM ACOUSTIC MEASURES OF LARYNGEAL VOICE QUALITY

Voice quality (VQ) is reported by forensic analysts to be a useful variable in voice comparison casework. Despite this, very little research has assessed the efficacy of VQ as a speaker discriminant. This paper employs semi-automatic methods to test the performance of a forensic voice comparison system using long-term acoustic measures of laryngeal VQ. Fundamental frequency, cepstral peak prominence, harmonics-to-noise ratios and a range of spectral tilt measures were extracted from vowel-only samples of studio, landline telephone, and mobile telephone recordings. Using likelihood ratio-based testing, the VQ features produced promising results. The high quality condition produced EERs as low as 5.8% and Cllrs as low as 0.26, although performance was degraded in the telephone conditions. When fused with a baseline MFCC system, results were mixed, with VQ improving performance only for some configurations of speakers.