Miracle-dz/UniFAR-FTUs huggingface dataset:
Are Deep Neural Networks good for blind image watermarking?

Image watermarking is usually decomposed into three steps: i) some features are extracted from an image, ii) they are modified to embed the watermark, iii) and they are projected back into the image space while avoiding the creation of visual artefacts. The feature extraction is usually based on a classical image representation given by the Discrete Wavelet Transform or the Discrete Cosine Transform for instance. These transformations need a very accurate synchronisation and usually rely on various registration mechanisms for that purpose This paper investigates a new family of transformation based on Deep Learning networks. Motivations come from the Computer Vision literature which has demonstrated the robustness of these features against light geometric distortions. Also, adversarial sample literature provides means to implement the inverse transform needed in the third step. This paper shows that this approach is feasible as it yields a good quality of the watermarked images and an intrinsic robustness.
Investigating for Punctuation Prediction in Chinese Speech Transcriptions

Many automatic speech recognition (ASR)systems typically produce text without punctuation. However, the lack of punctuation information makes it less readability and even difficult to understand. It is also not be appropriate for the subsequent natural language processing (NLP). Meanwhile, it makes the punctuation prediction more difficult that the Chinese language is quite distinct from other letters' languages. Thus, we concentrate on the unique pitch feature of Chinese and introduce a three-stage based on long short-term memory (LSTM)to predict punctuation in Chinese corpus. Then, based on the success of the combination between lexical features and pause time, we fuse pitch information into the lexical and pause time for predicting punctuation. This implementation is the way that utilizes three multi-modal features, which are the lexical, pause time and pitch, respectively. Experimental results on Chinese data set demonstrate that the effectiveness and superiority of the proposed model by using a three-stage recurrent neural network.
A Cognitive Ensemble Classifier based on Risk Sensitive Hinge Loss Function for Alzheimer’s Disease diagnosis in early stages

In this paper, we present a novel approach for Alzheimer’s disease diagnosis based on magnetic resonance images (MRI) using cognitive ensemble classifier. The proposed cognitive ensemble classifier employs a binary coded genetic algorithm (BCGA) for feature selection and an extreme learning machine (ELM) for classification. The cognitive ensemble classifier uses voxel based morphometric features extracted from MRI and subset of features are selected using BCGA. These selected features are then used to train ELM classifiers and an ensemble classifier is built based on risk sensitive hinge loss function. The study has been conducted using the open access series of imaging studies dataset and Alzheimer’s disease neuroimaging initiative dataset. The results clearly indicate that the proposed cognitive ensemble classifier produces better accuracy for AD diagnosis compared to other similar methods.
Learning to Play Pac-Xon with Q-Learning and Two Double Q-Learning Variants

Pac-Xon is an arcade video game in which the player tries to fill a level space by conquering blocks while being threatened by enemies. In this paper it is investigated whether a reinforcement learning (RL) agent can successfully learn to play this game. The RL agent consists of a multilayer perceptron (MLP) that uses a feature representation of the game state through input variables and gives Q-values for each possible action as output. For training the agent, the use of Q-learning is compared to two double Q-learning variants, the original algorithm and a novel variant. Furthermore, we have set up an alternative reward function which presents higher rewards towards the end of a level to try to increase the performance of the algorithms. The results show that all algorithms can be used to successfully learn to play Pac-Xon. Furthermore both double Q-learning variants obtain significantly higher performances than Q-learning and the progressive reward function does not yield better results than the regular reward function.
Platform Ecosystems for Indonesia Smart Cities

Urbanization has brought challenges, coming from the limited capacity of the environment and influencing social and economic aspects in urban areas. For example, the problems of health, high criminality, and economic imbalances. With the increase in information and communication technology, smart cities initiatives have grown in Europe, North America, and Asia since 2010, aiming to create sustainable urban development. Indonesia itself has had smart cities initiatives developed by local municipalities and regions. Currently, no less than seventy-five cities and regencies in Indonesia have started to adopt information and communication technology to improve public services. With platform ecosystems as a socio-technology-based innovation, interactions among the interconnected smart cities shall enhance strategic alignment between government’s policy responsiveness and citizen preferences on smart urban services, mediated by the increased political leadership and the advancement of the smart urban services. It is also expected that platform ecosystems for Indonesia smart cities shall increase collaboration among stakeholders and develop new opportunities for the development of circular economy to resolve the urbanization complexities.
SLAM-based 3D Line Reconstruction

Recovering 3D structure of the scene is widely studied in computer vision, which is called structure from motion. Most of the structure from motion approaches using features points to reconstruct 3D point cloud maps to represent scenes. However, there are always many lines in manmade scenes. Line is a higher-level representation of scene structure than point. We contribute a SLAM (simultaneous location and mapping) based method to reconstruct the 3D lines of urban scenes to emphasize the structures. In our approach, keyframe based SLAM system provides keyframes and camera poses, line segments are extracted and tracked in keyframes, the spatial line is determined in two steps: direction then position. The direction is acquired from normal vectors of multiple line projection planes and depth is searched by minimizing the total re-projection error of a spatial line in multiple keyframes. Degenerate and incorrectly tracked cases are detected by rank and principal components analysis. We present accurate 3D line model for urban scene with UAV inspection. The generated 3D lines give a better structural sense than sparse point cloud.
Characterizing Complexity of Electroencephalograms in Alzheimer's Disease at Multiple Temporal Scales

Entropy is a widely-used feature and a basic framework for electroencephalogram (EEG) analyses. Their corresponding multiscale methods were recently developed, adopting multiple time scales for entropy estimation. In this paper, towards Alzheimer's disease (AD) EEG recordings, we employed weighted-permutation entropy combining multiscale analysis, so that multiscale complexity information could be exposed across different scale factors. Our experiment and off-line analyses results confirmed that multiscale weighted-permutation entropy (MWPE) method could distinguish AD pattern and control pattern in terms of the evolution trend of MWPE profiles. The consistency of 16 channels were broken in AD brain. The entropy topographic distribution in AD patients distinctly differed from healthy subjects at large-scale.
De effectiviteit van Agrarisch Natuurbeheer

Het budget dat beschikbaar is voor natuurbeheer in Nederland staat momenteel onder druk. De laatste tien jaar is in binnen en buitenland veel onderzoek verricht naar de effectiviteit van agrarisch natuurbeheer. Uit deze studies is een beeld naar voren gekomen van een aantal sleutelfactoren die de effectiviteit van agrarisch natuurbeheer sturen. Op basis daarvan wordt in het eerste deel van de paper een conceptueel kader geschetst van factoren die de effectiviteit van agrarisch natuurbeheer beinvloeden. Daarbij wordt onderscheid gemaakt tussen algemene natuur en bedreigde of achteruitgaande soorten. In het tweede deel van de paper wordt een beknopt overzicht gegeven van de resultaten die behaald zijn met agrarisch natuurbeheer in Nederland de afgelopen 15 jaar.
The Impact of Pharmacy-Based Immunization on Vaccination Rates and Prevalence of Influenza Virus

From the 1990s through 2000s, states have changed pharmacist occupational regulations to allow provision of vaccinations. Little is known about the effects of these changes. This study estimates the impact of pharmacy-based immunization (PBI) regulations on seasonal influenza vaccination rates, provider source and health outcomes in the United States from 1996-2012. The evolution of PBI regulations was tracked in every state from 1996-2012 and influenza vaccination rates analyzed pre- and post-regulatory change in a quasi-experimental study design. Vaccination rates were determined from the National Behavioral Risk Factor Surveillance System (BRFSS). The outcomes were regressed on regulatory changes and other individual covariates (age, gender etc.) in a linear probability model. From 1996-2012, a total of 5,171,240 respondents were surveyed for the BRFSS. Excluding missing data, 3,866,450 respondents were included for analysis. Regulatory changes allowing PBI did increase the proportion of individuals vaccinated by 1.0% (95% CI: 0.3, 3.0). However this marginal increase in vaccination rates belies a complex underlying effect modification by age. In the presence of regulations, vaccination rates increase for those less than 65 years old (7.4%, 95% CI: 5.5, 10.4) but decrease for those 65 or older (-4.9%, 95% CI: -6.7, -2.3). PBI also appears to decrease the proportion of individuals who receive their vaccinations in physician offices by -1.7% (95% CI: -2.7,-0.7). No impact on health outcomes was observed. PBI regulations promoting pharmacy-based immunization have heterogeneous effects on vaccination by patient population. We observed increases in vaccination in certain subgroups following a change in regulation and decreases for others. Additionally, the regulations were associated with a decrease in vaccination receipt in physician offices. Further research focused on the potential effect modification of PBI by age and more robust data-sources will help further validate these findings.
ANALISIS PENGUKURAN KINERJA REKSA DANA SAHAM MENGGUNAKAN METODE SHARPE, TREYNOR, DAN JENSEN PADA BURSA EFEK INDONESIA

Tujuan dari penelitian ini adalah untuk mengetahui kinerja reksa dana saham berdasarkan metode Sharpe, Treynor, dan Jensen. Selain itu, penelitian ini memiliki tujuan mengetahui reksa dana mana yang memiliki kinerja outperform dan underperform terhadap IHSG. Periode penelitian yang digunakan adalah tahun 2012-2014. Penelitian ini merupakan penelitian kuantitatif deskriptif. Populasi penelitian adalah seluruh reksa dana saham yang terdaftar di Bursa Efek Indonesia periode 2013-2015. Pemilihan sampel ditentukan dengan teknik purposive sampling dengan kriteria saham yang dijadikan sampel adalah saham non-syariah dan aktif selama periode 2013-2015, sehingga diperoleh sampel sebanyak 48 reksa dana saham. Hasil penelitian berdasarkan metode Sharpe tahun 2013, 4 reksa dana saham berkinerja positif dan 44 negatif. Tahun 2014, 47 positif dan 1 negatif. Tahun 2015,tidak ada yang berkinerja positif dan 48 reksa dana saham negatif. Tahun 2013, 8 outperform dan 40 undeperform. Tahun 2014, 44 outperform dan 4 reksa dana saham underperform. Tahun 2015 tidak ada yang outperform dan 48 underperform. Berdasarkan metode Treynor tahun 2013, 5 positif dan 43 negatif. Tahun 2014, 48 positif dan tidak ada yang negatif. Tahun 2015, tidak ada yang memiliki kinerja positif dan 48 negatif. Pada tahun 2013 47 outperform dan 1 undeperform. Tahun 2014, 2 outperform dan 46 underperform. Tahun 2015 tidak ada yang underperform dan 47 outperform dan 1 underperform. Berdasarkan metode Jensen tahun 2013, 10 positif dan 30 negatif. Tahun 2014, 46 positif dan 2 negatif. Tahun 2015 7 positif dan 41 negatif. Perbandingan kinerja Reksa Dana saham terhadap benchmark. Tahun 2013, 47 outperform dan 1 underperform. Tahun 2014, 0 outperform dan 48 underperform. Tahun 2015, 48 outperform dan tidak ada yang underperform terhadap benchmark.
Explaining the Impact of a Communication Campaign to Change Vaccination Knowledge and Coverage in the Philipines

Results from the evaluation of a 1990 national vaccination program in cities in the Philippines are used to address three questions of concern to health communication researchers and practitioners: (1) whether interpersonal communication from change agents was a necessary condition for behavior change or whether a mass media campaign alone could influence vaccination behavior; (2) what kind of messages, specific (e.g., about the ages for vaccination) or general (e.g., about the danger of measles), most influenced behavior change; and (3) how existing gaps in vaccination status among socioeconomic groups were affected by the campaign. Surveys of 1,200 representative mothers were conducted before and after the campaign. The results showed that there was a substantial overall effect of the campaign, with timely vaccination coverage increasing from 35% to 51%. Increasing specific knowledge, rather than general knowledge, about measles vaccination was central to the campaign's success, accounting for three-fif.
Doxycycline and Coenzyme Q10 Treatment Modalities for Chronic Periodontitis: A Preliminary Study

Objective: Periodontitis represents one of the main causes of teeth loss. In this preliminary study, we aimed to evaluate the efficacy of different modalities for treatment of chronic periodontitis. Method and Materials: 40 patients were divided into 4 groups: group I, received subantimicrobial dose doxycycline (SDD; 20mg) and standard scaling and root planning (SRP); group II, received Co enzyme Q10 (CoQ10; 30mg) and SRP; group III, received both drugs and SRP; group IV, received SRP only. Medications were administered twice/day for 3 months. Gingival, plaque and bleeding indices, probing pocket depth, clinical attachment level and Osteocalcin level in gingival crevicular fluid (GCF) were assessed. Results: A combination of SDD and CoQ10 showed the best therapeutic effect (P<0.05) compared to other modalities. Treatment with SDD or CoQ10 improved significantly (P<0.05) the clinical parameters when compared to SRP alone. No significant reduction or increase in GCF osteocalcin level was evident. Conclusion: Combination of SDD and CoQ10 drugs that were given twice per day for 3 months is of promising clinical outcomes. However, long-term studies on a larger number of patients are recommended to confirm or refute these findings and to explore the exact role of osteocalcin in periodontitis and its treatment modalities.
Recuperando el paso en la evaluación del aprendizaje en linea en la era digital: una aproximación conexionista

A neural net was implemented to discriminate students who integrated knew knowledge in long term memory from those who did not by just considering word recognition latencies to concepts schematically related by a course. This is helpful to identify students that only retain information in short term memory to successfully pass an exam but do not acquire long term competencies. It is argued that by considering this learning assessment approach over formal e-learning settings, significant delay to innovate learning assessment in virtual learning platforms can be overcome since nowadays online learning assessment is reduced to reproduce or adapt old testing methods.
A Paradigm Shift for Improved Processing of Small Files in Hadoop

HDFS is designed to handle large files containing petabytes or exabytes of data. However, there are plenty of applications that need access & manipulation of large number of small files. HDFS suffers performance penalty while dealing with large number of small files. With the rapid development of Internet, users may tend to store their data and programs in a cloud computing platform. Personal data has an obvious feature -large number and small file size. In such cases, HDFS struggles to meet performance criteria. In hadoop architecture, the FileInputFormat generates a split per file. Map tasks usually process a block of input at a time. In case of large number of small files, each map task processes very little input. Every map task imposes extra bookkeeping overhead on NameNode and also consumes considerable time to process large number of small files. We have attempted a strategy wherein large number of small files are clubbed together to form a single split. This inherently reduces number of blocks generated by FileInputFormat, resulting in lesser processing time. Clubbing of small files is achieved through a customized mapper. Practical setup has indicated performance improvement of around 80%. The paper covers this paradigm shift in processing large number of small files in HDFS for performance improvement.
Ujaran Implisit dalam Filem Melayu Klasik Sri Mersing

Filem Melayu klasik merupakan khazanah filem negara yang menyimpan pelbagai elemen budaya dan penggunaan bahasa yang indah. Filem ini padat dengan penggunaan ujaran implisit dalam setiap kata, frasa dan ayat yang digunakan. Kajian ini mempunyai dua fokus utama iaitu mengenal pasti ujaran implisit yang terdapat dalam filem Melayu klasik ‘Sri Mersing’ dan menganalisis makna ujaran yang implisit menggunakan teori Relevans. Teori ini mengandungi tiga komponen penting iaitu konteks, kesan konteks dan kos proses. Kajian analisis teks dijalankan dengan menyata dan menghuraikan pengujaran implisit yang telah dikenal pasti serta mendedahkan peranan konteks, kesan konteks dan kos proses dalam merungkai makna ujaran yang implisit dalam filem tersebut. Hasil kajian mendapati lima petikan ujaran dalam filem ‘Sri Mersing’ yang mempunyai makna implisit. Elemen implisit tersebut mendedahkan keperluan memahami ujaran yang disampaikan dengan menggunakan konteks dan kesan konteks. Dapatan kajian memperlihatkan pemahaman masyarakat terhadap penggunaan bahasa Melayu yang kaya dengan ujaran dan makna implisit. Di samping itu, kajian ini juga telah menonjolkan keindahan dan keunikan bahasa yang terdapat dalam filem Melayu tradisional terutamanya sekitar 60-an
Analysis and Implementation of eSTREAM and SHA-3 Cryptographic Algorithms

Invaluable benchmarking efforts have been made to measure the performance of eSTREAM portfolio stream ciphers and SHA-3 hash function candidates on multiple architectures. In this thesis we contribute to these efforts; we evaluate the performance of all eSTREAM ciphers and all secondround SHA-3 candidates on NVIDIA Graphics Processing Units (GPUs). Complementarity, we present the first implementation of the cube attack in a multi-GPU setting. Our framework proves useful in the practical analysis of algorithms by providing a generic black box interface and speedup factors over 100 . Demonstrating its use we analyze two eSTREAM stream ciphers, MICKEY v2 and Trivium. We find that MICKEY is not susceptible to low-degree cube attacks, while our Trivium analysis confirms previous results, in addition to several new equations applicable to a partial key recovery. We also extend the linear differential cryptanalysis framework introduced by Brier, Khazaei, Meier and Peyrin at ASIACRYPT 2009 using two new trail search algorithms, and several optimizations. We find several collision and second preimage attacks on simplified and round-reduced variants of BLAKE and CubeHash, two SHA-3 second round candidates. Using the extended framework we also present improved collision attacks on CubeHash, when compared to previous results. In combination with the condition function concept, our new trail search algorithms lead to much faster collision attacks. We demonstrate this by providing a real collision for CubeHash-5/96. Additionally our randomized trail search finds highly probable linear differential trails and leads to significantly better attacks for up to eight rounds of CubeHash.
The Other Side of Child Protection: The Lived Experiences of Front Line Child Protection Workers.

Supervisory Committee Dr. Sibylle Artz, School of Child and Youth Care, Supervisor Dr. Roy V. Ferguson, School of Child and Youth Care, Departmental Member Dr. Leslie T. Foster, School of Child and Youth Care, Departmental Member As a result of working in high-risk situations, child protection workers are often confronted by such traumatic incidents as the physical and sexual abuse of children, serious neglect situations, and personal threats. The perception of how workers deal with their emotional challenges has not received a great deal of attention in the literature. To date, a phenomenological study focusing on the descriptive experiences of child protection workers struggling with secondary traumatic stress has not been published. This study attempts to rectify this, by examining from a phenomenological perspective how secondary traumatic stress (STS) experienced by child protection workers impacts their practice and personal lives. This study found that child protection workers engaged in direct practice will be exposed directly and indirectly to traumatic events through their work with children and families and the risks of experiencing symptoms of STS are almost a certainty for a child protection worker. Participants described the day-to-day pressures of managing a caseload and dealing with traumatic events or traumatized people. From their responses, three major categories emerged: Professional Issues relating to case practice and effectiveness; the Personal Impacts of child protection work on the way workers function, both on the job and in their private lives; and Behavioral or Physical Changes experienced by child protection workers. It is these categories that best illustrate the dramatic way secondary trauma affects child protection workers as a whole.