Miracle-dz/UniFAR-FTUs huggingface dataset:
Usage of Hidden Markov Models for automatic sleep stages classification

Introduction Brain activity level is determined by wake-sleep cycle. Sleep is organized as a sequence of several stages. Their cyclic organization proves the existence of the special regulatory system. This work is devoted to development of the algorithm for automatic sleep stages determination and following study of brain bioelectric activity during healthy sleep. The most popular and widely used system for sleep classification was developed by Rechtschaffen and Kales (R&K) in 1968 [7]. The system allowed to standardize the criteria for sleep stages discrimination and thus provided the possibility to compare results of experiments from different laboratories and hospitals. According to that method, the whole EEG record is firstly divided on segments lasting 20-30 seconds and then for each segment main amplitude and spectrum parameters for standard EEG rhythms are calculated. By analyzing those values a human expert, e.g. somnologist, makes a decision about membership of analyzed segment to particular sleep stage. Obviously, it is very hard and time consuming to use that method for analysis of whole night sleep recording which sometimes lasts as long as 8-10 hours. In spite of tremendous number of research in the field of automatic sleep stage classification [3, 5, and 8], still manual sleep staging systems are more popular than automatic ones. For objective sleep studying we have used the polysomnography method which comprised on electroencephalography (EEG), electrooculography (EOG) and electromyography (EMG) registration. Then amplitude and frequency features were calculated and fed to neural net classifier based on Hidden Markov Models (HMM) [1]. That allowed us to identify sleep stages and phases and to build their sequence known as a hypnogram. The results of that classification were validated by comparison with classification made by human expert who had utilized R&K rules. We have demonstrated that HMM can be used for sleep staging based only on 2 bipolar EEG channels (Fpz-Cz and Pz-Oz) with the quality sufficient for usage in real diagnostic process.
Part of Speech Tagger for Hadiyyisa Language

Part of Speech (POS) Tagging is the process of assigning the correct part-of-speech to each word in a text that best suits the definition of the word as well as the context of the sentence in which it is used. A part-ofspeech tagger is used in many language technology applications as a first step in more complex NLP applications such as grammar checking, machine translation, information extraction and information retrieval. There are different approaches to the problem of POS Tagging. In this paper, we have used two approaches: Rule based and TnT approach. We have compared the performance of these techniques for tagging using combination with backoff taggers for Hadiyyisa Language. These approaches use supervised POS Tagging. It requires a large amount of annotated training corpus to build the tagging model and perform acceptable tagging of a new text. At the initial stage of POS Tagging of Hadiyyisa Language, we have very limited annotated corpus, i.e., 1280 manually tagged corpus of Hadyyisa sentences tagged with 32 identified tag sets and 10 basic tag sets. The 10 basic tag sets are derived from the 32 identified tag sets. The corpus was divided into 80% for training and 20% for testing. The research attempted to investigate a technique that maximizes the performance with this limited language resource. By experiment, the best configuration was investigated using TnT with Affix unknown word taggers, Rule-based with Affix initial state tagger, Rule based tagger when the initial state tagger with backoff in the sequence of TrigramTagger, BigramTagger, UnigramTagger, AffixTagger, and TnTunknown word handling with backoff in the sequence of TrigramTagger, BigramTagger, UnigramTagger, AffixTagger. These approaches have accuracy of 66.64%, 64.65%, 72.54%, and 73.06% with 32 derived tag sets tagged corpus and 80.34%, 72.67%, 87.25%, and 89.03% with 10 basic tag sets tagged corpus respectively. Therefore, better performance is gained by the basic tag set tagged corpus with the tagger TnT-unknown word handling with backoff in the sequence of TrigramTagger, BigramTagger, UnigramTagger, AffixTagger taggers than the other approaches.
Learning extreme verification latency quickly with importance weighting: FAST COMPOSE & LEVEL_IW

Muhammad Umer LEARNING EXTREME VERIFICATION LATENCY QUICKLY WITH IMPORTANCE WEIGHTING: FAST COMPOSE & LEVELIW 2016-2017 Robi Polikar, Ph.D. Master of Science in Electrical & Computer Engineering One of the more challenging real-world problems in computational intelligence is to learn from non-stationary streaming data, also known as concept drift. Perhaps even a more challenging version of this scenario is when – following a small set of initial labeled data – the data stream consists of unlabeled data only. Such a scenario is typically referred to as learning in initially labeled nonstationary environment, or simply as extreme verification latency (EVL). This thesis introduces two different algorithms to operate in this domain. One of these algorithms is a simple modification of our prior work, COMPOSE (COMPacted Object Sample Extraction), that allows the algorithm to work without its extremely computationally expensive core support extraction module. We call this modified algorithm FAST COMPOSE. The other algorithm we propose that works in this setting is based on the importance weighting domain adaptation approach. We explore importance weighting to match distributions between two consecutive time steps, and estimate the posterior distribution of the unlabeled data using importance weighted least squares probabilistic classifier. The estimated labels are then iteratively used as the training data for the next time step. We call this algorithm LEVELIW, short for Learning Extreme VErification Latency with Importance Weighting. An additional important contribution of this thesis is a comprehensive survey and comparative analysis of competing algorithms to point out the weaknesses and strengths of different approaches from three different perspectives: classification accuracy, computational complexity and parameter sensitivity using several synthetic and real world datasets.
Exploring Hypotheses Spaces in Neural Machine Translation

Both statistical (SMT) and neural (NMT) approaches to machine translation (MT) explore large search spaces to produce and score translations. It is however well known that often the top hypothesis as scored by such approaches may not be the best overall translation among those that can be produced. Previous work on SMT has extensively explored re-ranking strategies in attempts to ﬁnd the best possible translation. In this paper, we focus on NMT and provide an in-depth investigation to explore the inﬂuence of beam sizes on information content and translation quality. We gather new insights using oracle experiments on the efﬁcacy of exploiting larger beams and propose a simple, yet novel consensus-based, n -best re-ranking approach that makes use of different automatic evaluation metrics to measure consensus in n -best lists. Our results reveal that NMT is able to cover more of the information content of the references compared to SMT and that this leads to better re-ranked translations (according to human evaluation). We further show that the MT evaluation metric used for the consensus-based re-ranking plays a major role, with character-based metrics performing better than BLEU.
Optimization of PID Controller Based on PSO for Photovoltaic Dual Axis Solar Tracking in Gresik Location – East Java

164901-8080-IJET-IJENS © February 2016 IJENS I J E N S Abstract— To improve the efficiency of electricity production of solar cell panels made by adding a solar tracking system. With a sun-tracking system sectional Photovoltaic (PV) is always facing the sun, so that the optimum electrical energy produced. There is a control technique is offered to solve this problem, among others, conventional PID control. In this study built-PSO PID control system, to optimize existing PID control. Adding algorithms particle swarm optimization (PSO) as tuning PID. PID parameters can be selected so that more precise. Designed by PID control and PID-PSO for PC iteration . For horizontal axis of rotation with a minimum three-stage fitness function final 1:33. Values obtained KP = 212.4, Ki = 27.1, and KD = 152. In the design of control PV vertical axis of rotation at iteration to eight by the end of the minimum fitness function = 8.6801. values obtained Kip = 487.2, Kid = 21.4, and Kid = 732.02, Performance PSO-PID control system of horizontal rotary axis stabilized system with maximum value overshot = 1.69%, settling time = 0.05 sec. Performance PSO-PID control system for rotary axes generate maximum value overshot = 1.83%, settling time = 0.104 seconds. So that the system is designed capable of tracking the position of the sun Index Term— photovoltaic, solar tracking, PID control, PSO, auto tuning
Cowpea Breeding

Cowpea (Vigna unguiculata (L.) Walpers) is the most commonly grown grain legume in the dry savannah regions of sub-Saharan Africa. It is also an indigenous crop to these parts. It is grown for the protein rich grains and fodder for livestock. The bulk of cowpea produced is consumed in the sub-region hence very little international trade is associated with the crop. The productivity of the crop in SSA is hampered by a number of abiotic and biotic stresses some of which are drought, low soil fertility, insect pests, fungal, bacterial and virus diseases. Mean grain yield is less than 600 kg ha−1 which is a far cry from its potential of up to 2.0 tons ha−1. Being a legume, cowpea can fix most of its needed nitrogen in the root nodules. Breeding activities, taking advantage of the world cowpea germplasm collection maintained at IITA’s genebank, are ongoing with the aim of increasing the crop’s productivity in African farmers’ fields where limited inputs are applied by the generally resource poor farmers who produce the most amount of the crop. Through conventional breeding procedures it has been possible to develop and release to farmers varieties with resistance to insect pests such as aphid (Aphis craccivora), flower bud thrips (Megalurothrips sjostedti), diseases such as Cercospora leaf spot, macrophomina, bacterial blight, and the parasitic plants Striga and Alectra. In addition, these varieties possess traits preferred by farmers and consumers. There are varieties that mature as early as 60 days after planting as well as those with significantly reduced cooking time, helping to conserve energy. Recently efforts have commenced to facilitate progress in the breeding process by applying new breeding tools such as marker assisted selection. To this end genetic linkage maps have been generated for cowpea and molecular markers associated with important quantitative trait loci (QTL) like resistance to macrophomina, bacterial blight, flower thrips, foliage thrips, aphids and drought were identified. Some of the markers have been validated and are currently being used to introgress desirable traits into improved varieties using marker assisted backcrossing (MABC) and marker assisted recurrent selection (MARS).
Analysis and Optimization of Data Center Networks for Flexibility

Today‘s communication networks are facing diverse demands which create the necessity for more flexible networks. In particular, data center networks are confronted with a plethora of time-varying requirements. A recent trend in data center networking research is the development of architectures that can adapt their topology at runtime to account for changing demands, e.g., using Optical Circuit Switches. This thesis will evaluate how such architectures can explicitly optimize the flexibility of data center networks.
Daman 1 BMW'S SAFETY GUIDELINES FOR THE TESTING AND DEPLOYMENT OF AUTOMATED VEHICLES

As automobile manufacturers take the leap from Advanced Driving Assistance Systems and implement Automated Driving Systems into their vehicles, certain aspects of vehicle safety become increasingly important. Whereas in today’s level 2 automation, the human driver is involved in the dynamic driving task, in level 3 and above, more technological measures are necessary to ensure safety, therefore requiring a newly designed electronic architecture. Nonetheless, analysis of human factors remain a key element to ensure the safe operation of the vehicle. Though conventional techniques may be employed to solve some of these challenges, others require new tools to be developed. In the absence of an international standard, the foundation for discussions of completeness is missing. With an expert analysis of topics and tools a focus can be brought into discussions and serve as a basis for further development. This analysis may also lead to uncover areas where final answers and methods are missing, but serves also to identify areas where effort must be concentrated. When members of the industry apply these principles to the development of automated driving systems, the number of accidents will be minimized following the testing and deployment of this new technology, therefore maximizing safety and customer acceptance. This submission represents the culmination of multiple sessions within industry, but also with contracting parties and government agencies with the goal of the creation of a comprehensive list of guidelines for the safe development of automated driving systems. BMW has defined 12 different areas that have been focused into guidelines for the development of a vehicle with a safe automated driving system. These areas include topics from functional safety through the human factors aspects of system handovers to the consideration of passive safety. While the 12 guidelines are selected to be a comprehensive list of safety topics, they are general in form and do not contain the details necessary to apply it as a blue print for the development. As these automated driving systems are not on the roads in appreciable numbers, the data from real world events are missing. Also the projects to develop the methods to generate and analyze data are still underway, which also forces some guidelines to remain broadly formulated. The proposed guidelines concentrate the capabilities and limitations of today’s safety evaluation for vehicles when applied to automation. By following the guidelines, the industry can ensure that this technology meets an acceptable level of safety when it comes to market.
Role of quality assurance and programme accreditation in supporting development of innovative agricultural curricula

An increasing global demand for food security and sustainability places substantial responsibility on higher agricultural education institutions. Quality assurance, accreditation, and innovation are central elements for the development of agricultural curricula. Most scholars agree that student learning is core to the role of the university. Quality judgements are framed around four criteria-academic scholarship, demands of the subject matter, relevance to society, and viability. Quality assurance is enhanced by peer-evaluation, rigorous research, and confirmation by student evaluation data. Quality assurance also recognises the contributions that research makes to the growing body of scientific knowledge. Accreditation strengthens trust affirming the purpose, experiences, organisation, and measured scalable learning outcomes. Policies for accreditation should recognise internal and external standards, provide user protection, provide independently-verified information, and im pro ve and enhance the culture and values of the people. The proposed framework fits national qualifications into a comprehensive common system of quality assurance, learning outcomes, recognised programme standards, cultural values, and accreditation. Innovation is crucial for curriculum viability. Measurement is essential for an improvement strategy in education. Faculty reward systems must match the academic functions. Six crucial concepts underpin the development and execution of innovative agricultural curricula.
Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

We present a scheme to estimate the direction of arrival of acoustic signals reflected by underwater targets using wideband hydrophone arrays of opportunity. Such arrays may be obtained by arranging together multiple smaller sub-arrays that were originally designed to work independently. The array of opportunity that results may be subject to practical mounting limitations, hence the typical constraint that closest array elements should not be spaced more than one half-wavelength may not be upheld. In these conditions, the array is affected by spatial ambiguity.Our proposed scheme solves this issue by fusing direction-of-arrival information with side information on the estimated target location (obtained via multilateration). This makes it possible to eliminate most of the ambiguity, and yields accurate direction-of-arrival estimates. Our simulation results show that our scheme achieves satisfactory direction of arrival estimation and localization results. Moreover, even by relying on arrays of opportunity, we can outperform classical direction-of-arrival algorithms applied to larger arrays with half-wavelength spacing design.
Expression Classification in Children Using Mean Supervised Deep Boltzmann Machine

Automated facial expression classification has widespread application in multiple domains such as human computer interaction, health and entertainment, biometrics, and security. There are six basic facial expressions: Anger, Disgust, Fear, Happiness, Sadness, and Surprise, apart from a neutral state. Most of the research in expression classification has focused on adult face images, with no dedicated research on automating expression classification for children. To the best of our knowledge, this is the first research which presents a deep learning based expression classification approach for children. A novel supervised deep learning formulation, termed as Mean Supervised Deep Boltzmann Machine (msDBM) is proposed which classifies an input face image into one of the seven expression classes. The proposed approach has been evaluated on two child face datasets - Radboud Faces and CAFE, along with experiments on the adult face images of the Radboud Faces dataset. Experimental results and analysis reinforces the challenging nature of the task at hand, and the effectiveness of the proposed msDBM model.
HYBRID SIMULATION NETWORK FOR VEHICULAR AD HOC NETWORK (VANET)

Intelligent Transportation Systems (ITS) plays a vital role in providing different means of traffic management and enables users to be better informed of traffic condition, promoting safer, coordinated and efficient use of transport network. Vehicular Ad Hoc Network (VANET) shows promising reliability and validity in ITS. But, it poses challenges to researchers in designing protocol specifically for VANET as the deployment of VANET in real world will incur high cost. Therefore, simulation and non-physical testbed implementation have been widely adopted by the VANET research community in the development and assessment of the new or improved system and protocol of VANET. This paper presents a viable simulation platform for network development. Besides, a code cast or better known as network coding, a data packet transmission method has been developed and introduced into VANET protocol using the presented platform to assess and determine the potential of the introduced simulation platform.
LONG-TERM CARE SYSTEMS IN EUROPE

The evaluation of long-term care (LTC) systems carried out in Work Package 7 of the ANCIEN project shows which performance criteria are important and – based on the available information – how European countries score on those criteria. This paper summarises the results and discusses the policy implications. An overall evaluation was carried out for four representative countries: Germany, the Netherlands, Spain and Poland. Of the four countries, the Dutch system has the highest scores on quality of life of LTC users, quality of care and equity of the LTC system, and it performs the secondbest after Poland in terms of the total burden of care (consisting of the financial burden and the burden of informal caregiving). The German system has somewhat lower scores than the Dutch on all four dimensions. The Polish system excels in having a low total burden of care, but it scores the lowest on quality of care and equity. The Spanish system has few extreme scores. Some important lessons are the following. The performance of a LTC system is a complex concept where many dimensions have to be included. Specifically, the impact of informal caregiving on the caregivers and on society should not be forgotten. The role of the state in funding and organising LTC versus individual responsibilities is one of the most important differences among countries. Choices concerning private funding and the role of informal care have a large effect not only on the public expenditures but also on the fairness of the system. International research into the relative preferences for the different performance criteria could produce a sound basis for the weights used in the overall evaluation. Available for free downloading from the CEPS website (www.ceps.eu) and ANCIEN website (http://www.ancien-longtermcare.eu/) © Copyright 2012 Esther Mot and Anikó Bíró ENEPRI Policy Briefs extract the policy implications of research carried out by member institutes of the European Network of Economic Policy Research Institutes. Initiated by CEPS in 1999, ENEPRI conducts research on welfare and employment issues with the aim of diffusing research, coordinating research plans and increasing the awareness of the European dimension in national problems (see www.enepri.org). The research presented in this Policy Brief was conducted under the ANCIEN project (Assessing Needs of Care in European Nations), which focuses on the future of long-term care for the elderly in Europe. Funding for the project is received from the European Commission under the 7 Framework Programme (FP7 Health-2007-3.2.2, Grant no. 223483). See the back page for more information “About ANCIEN”. The views expressed are attributable only to the authors in a personal capacity and not to any institution with which they are associated.