Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Photovoltaic System Architecture of Module-Integrated Converter with a Single-sourced Asymmetric Multilevel Inverter Using a Cost-effective Single-ended Pre-regulator

In this paper, a new architecture for a cost-effective power conditioning systems (PCS) using a single-sourced asymmetric cascaded H-bridge multilevel inverter (MLI) for photovoltaic (PV) applications is proposed. The asymmetric MLI topology has a reduced number of parts compared to the symmetrical type for the same number of voltage level. However, the modulation index threshold related to the drop in the number of levels of the inverter output is higher than that of the symmetrical MLI. This problem results in a modulation index limitation which is relatively higher than that of the symmetrical MLI. Hence, an extra voltage pre-regulator becomes a necessary component in the PCS under a wide operating bias variation. In addition to pre-stage voltage regulation for the constant MLI dc-links, another auxiliary pre-regulator should provide isolation and voltage balance among the multiple H-bridge cells in the asymmetrical MLI as well as the symmetrical ones. The proposed PCS uses a single-ended DC-DC converter topology with a coupled inductor and charge-pump circuit to satisfy all of the aforementioned requirements. Since the proposed integrated-type voltage pre-regulator circuit uses only a single MOSFET switch and a single magnetic component, the size and cost of the PCS is an optimal trade-off. In addition, the voltage balance between the separate H-bridge cells is automatically maintained by the number of turns in the coupled inductor transformer regardless of the duty cycle, which eliminates the need for an extra voltage regulator for the auxiliary H-bridge in MLIs. The voltage balance is also maintained under the discontinuous conduction mode (DCM). Thus, the PCS is also operational during light load conditions. The proposed architecture can apply the module-integrated converter (MIC) concept to perform distributed MPPT. The proposed architecture is analyzed and verified for a 7-level asymmetric MLI, using simulation results and a hardware implementation.
Implementation of 1D Brinson model in 3D SMA specimens Influenced by stress concentration

The application of small-size SMA components has grown rapidly in various industries over the last few years. Due to their complex nature, local constitutive models for those components have proven somehow impractical; whereas global models have been unable to take the stress concentration into consideration and hence cannot predict the nucleation and stress patterns accurately, especially in small samples. Moreover, FE analyses are impossible to conduct in cases where a large number of evaluations are required to design a suitable SMA sample. This paper proposes a new iterative method to accurately calculate the stress and martensitic volume fraction in samples with stress concentration using 1D Brinson model. The method is implemented in the form of a computer code which is then refined iteratively using FEM model which is validated based on experimental data. Final assessments show that the proposed method could predict the stress values accurately at negligible computational costs.
DEVELOPMENT OF INDOOR HYBRID ACTIVE NOISE BARRIER

This paper develops an indoor active noise barrier (ANB) by using a hybrid active noise control (HB-ANC) system. The HB-ANC system reduces the noise diffracted from the top of the ANB and the noise propagated to the head position of the target person behind the ANB simultaneously to achieve higher noise attenuation. However, the waterbed effect of the feedback control part of the HB-ANC system will cause noise enhancement at some frequencies in the control area. In the paper, in order to solve this problem, a filter able to cancel the noise enhancement is integrated into the HB-ANC system. Then, the noise attenuation performance of the ANB under four sound field configurations is verified by simulations. The sound field configurations are set up to investigate how the diffraction from side of the ANB and the reflection influence the performance of the ANB. An experiment in the anechoic chamber is also conducted. The simulation and experiment results indicate that the low frequency noise can be reduced in a wide area behind the ANB, and at the head position of the person, the noise attenuation can be obtained within a wider frequency range, even for the sound fields where the diffraction from side and the reflection exist.
Three-dimensional shared memory fabricated using wafer stacking technology

We proposed a new three-dimensional (3D) shared memory for a high performance parallel processor system. In order to realize such new 3D shared memory, we have developed a new 3D integration technology based on the wafer stacking method. We fabricated the 3D shared memory test chip with three memory layers using our 3D integration technology. It was demonstrated that the basic memory operation and the broadcast operation of 3D shared memory are successfully performed.
Wheats: A Wearable Personal Healthcare and Emergency Alert and Tracking System

Pervasive and mobile computing makes it possible to achieve system of personal healthcare and emergency alert and tracking which can monitor personal health status in a real-time manner and automatically issue the alert for medical aids in case of emergency by tracking user’s location correctly. In this paper, a novel wearable personal healthcare and emergency alert and tracking system namely WHEATS is proposed. This system reduces the job of caregiver. WHEATS uses tiny wearable sensors to continuously collect user’s vital signals and Bluetooth devices to transmit the sensory data to a mobile phone, which can perform on-site vital data storage and process. After local data process, the mobile phone can use its GSM(Global System for Mobile Communications) module, WiFi(Wireless fidelity) and GPRS(General Packet Radio Service) to periodically report user’s health status to the healthcare centre via nearby healthcare system by using WIM(Wireless Identity Module) embedded in SIM(Subscriber Identity Module) card. WHEATS issues alert emergency signals for medical aids once detecting abnormal vital signals. A-GPS (Assisted GPS) is used to track user exact location when user vital signs are abnormal or in emergency. This system reduces medical expenses, data transmission, and timely communication with nearby healthcare centre for emergency medical aid.
Interference of areas of subcycle light pulses

Progress in reducing the duration of light pulses (down to one cycle of field oscillations or less), achieved in the last decades, has made it possible to experimentally observe and study a number of atomic-scale phenomena that occur at ultrafast times. Their study and observation are unavailable with conventional sources of monochromatic laser radiation. When using few- or subcycle pulses, a number of well-known phenomena in optics, which are well studied when using long monochromatic radiation sources, either lose their meaning, or their underlying physical mechanisms require revision. For example, the direct interference of subcycle pulses with their direct overlap is not possible due to their short duration. This note addresses the interference phenomenon, when a pair of subcycle pulses act on a medium, while do not simultaneously overlap inside it. In this case, it is not the pulses themselves that interfere in the medium, but the probability amplitudes of the bound states of the medium. Therefore the result of their impact on the medium can be interpreted as the interference of the areas of pulses—electric pulse areas (integral of the electric field strength over time) and envelope areas (integral of the slowly varying envelope of the electric field strength over time).
Innovations in crop production: a matter of physiology and technology

Crop production per unit greenhouse area has doubled during the last 25 years in The Netherlands, while the energy use has been drastically reduced. The growth conditions for plants have been improved significantly through understanding crop physiology in combination with new technologies. In this paper some of the recent innovations in greenhouse horticulture are discussed. Semi-closed greenhouses combine energy saving by storing heat in aquifers with yield improvement. These effects on yield are mainly due to a higher CO2 concentration. The next generation cultivation focuses on energy saving with lower costs. The main components of this concept are an intensive use of energy screens to conserve heat, controlled inlet and distribution of outside air to regulate air humidity, and flexible temperature set-points based on energy losses and plant demand. Greenhouse covers that scatter direct solar radiation without influencing the transmissivity improved crop production in several crops up to 10%. In tomato this increase was due to the improved vertical and horizontal light distribution, a larger photosynthetic capacity of the lower leaves and a larger leaf area index. In heavily shaded potted plants like anthurium and bromeliads, substantially less shading is necessary under diffuse light and well controlled growth conditions, which enhances crop photosynthesis. In this way yield improvements of up to 50% were observed. Some growers have already installed LED lamps as source for assimilation light. Modern LEDs may convert electricity into light 25% more efficiently than high pressure sodium lamps. Even more important are the possibilities to influence physio-logical and morphological processes by manipulating the positioning, timing and spectrum of the lamps. A large number of these innovations began with crop and greenhouse models, which are powerful tools in research. New developments in simulating plant processes can be found in functional-structural models (FSPM) and systems biology models. They can be used to design new production systems or to predict the ideal phenotype of plants. Plant monitoring based on combinations of plant sensors (e.g., chlorophyll fluorescence) and models will be used more and more to adjust the greenhouse envi¬ronment to the needs of the plants. Application of models through web-based services are likely to be at the point of large scale introduction to support growers in their decisions.
Research Evidence on the Use of Learning Analytics: Implications for Education Policy

Learning analytics is an emergent field of research that is growing fast. It takes advantage of the last decade of e-learning implementations in education and training as well as of research and development work in areas such as educational data mining, web analytics and statistics. In recent years, increasing numbers of digital tools for the education and training sectors have included learning analytics to some extent, and these tools are now in the early stages of adoption. This report reviews early uptake in the field, presenting five case studies and an inventory of tools, policies and practices. It also provides an Action List for policymakers, practitioners, researchers and industry members to guide work in Europe.
Settling the Communication Complexity for Distributed Offline Reinforcement Learning

We study a novel setting in offline reinforcement learning (RL) where a number of distributed machines jointly cooperate to solve the problem but only one single round of communication is allowed and there is a budget constraint on the total number of information (in terms of bits) that each machine can send out. For value function prediction in contextual bandits, and both episodic and non-episodic MDPs, we establish information-theoretic lower bounds on the minimax risk for distributed statistical estimators; this reveals the minimum amount of communication required by any offline RL algorithms. Specifically, for contextual bandits, we show that the number of bits must scale at least as $\Omega(AC)$ to match the centralised minimax optimal rate, where $A$ is the number of actions and $C$ is the context dimension; meanwhile, we reach similar results in the MDP settings. Furthermore, we develop learning algorithms based on least-squares estimates and Monte-Carlo return estimates and provide a sharp analysis showing that they can achieve optimal risk up to logarithmic factors. Additionally, we also show that temporal difference is unable to efficiently utilise information from all available devices under the single-round communication setting due to the initial bias of this method. To our best knowledge, this paper presents the first minimax lower bounds for distributed offline RL problems.
KNOWLEDGE DISCOVERY FROM VEHICLE E-GOVERNANCE DATA USING DATA WAREHOUSING AND DATA MINING

In this paper, multi dimensional schema design, data cube and OLAP operations on Vehicle e-governance data is discussed. The proposed data mining model and its implementation on Vehicle e-governance data is also discussed. In the first phase, Clustering data mining algorithm is implemented to identify important clusters from the Vehicle e- governance data. In the second phase, Association Rules Mining algorithm is applied to explore novel relationships from the important data clusters observed in the first phase. The results indicate that novel relationship can be found using the proposed model.
Media’s Support in Promoting Environment Awareness

Environment is the basic need of life like food and water. But our actions have aggravated it severely. Realising our mistake we have taken commendable steps to reform it and a proper media attention might give a higher success rate to any mission related to environment. Most recent steps by the Government of India for promoting sanitation ‘Swachchha Bharat Abhiyan’ has got success by the united efforts of the Government and media. Media has always covered social and environmental issues thus it is the most revolutionary device for spreading consciousness towards environment protection. Here in this paper, I have put all my endeavours to throw some light on the topic “ Media's support in promoting environment awareness ".
Formulating a capability approach based model to sustain rural Sub-Saharan African inhabitant's self-reliance towards their built environment

Changing climate conditions and depleting resources are becoming more important on the global agenda, the paradigm shifting to understand which means (resources) are necessary to generate future well-being. Unfortunately, the formal built environment remains the most polluting global industry and due to its conservative character seems difficult to change. Most undertaken efforts focus on improving characteristics of material, construction and processes in technology seeking the ability to solve all contemporary environmental problems. This article argues that in the informal rural African built environment examples of other attitudes towards the same goals can be found, providing many sustainable solutions that have a circular process and are based on local renewable materials. Rural communities perceived as a multitude of communities of practices, with a collective (sustainable) intelligence towards their built environment can provide a circular, sustainable, self-reliant and resilient model for the built environment. This article argues that in order to articulate sustainable 'local' solutions, the inhabitant's self-reliance is of vital importance, therefore stating a need for a model to evaluate what affords the inhabitant's self-reliance and how this model could be used as support for the 'expert' to evaluate the inhabitant's capabilities towards their built environment. This article uses the rural locality as a case study with the intention for subsequent global (urban and rural) application.
Assessment of the European classification criteria for S jogren's syndrome in a series of clinically defined cases: results of a prospective multicentre study

Objective-To assess the recently proposed preliminary criteria for the classification of Sjogren's syndrome (SS) in a multicentre European study of a new series of clinically defined cases. Methods-The criteria included six items: I = ocular symptoms; II = oral symptoms; II = evidence of keratoconjunctivitis sicca; IV = focal sialoadenitis by minor salivary gland biopsy; V = instrumental evidence of salivary gland involvement; VI = presence of autoantibodies. Each centre was asked to provide five patients with primary SS, five with secondary SS, five with connective tissue diseases (CTD) but without SS, and five controls (patients with ocular or oral features that may simulate SS). The preliminary six item classification criteria set was applied to both the SS patients and the non-SS controls, and the performance of the criteria in terms of sensitivity and specificity was tested. Results-The criteria set was tested on a total of 278 cases (157 SS patients and 121 non-SS controls) collected from 16 centres in 10 countries. At least four of the six items in the criteria set (limiting item VI to the presence of
ADAPTIVE OBSERVER BASED FAULT DIAGNOSIS APPROACH APPLIED TO A THERMAL PLANT

This paper presents an on-line model-based procedure for the detection and diagnosis of sensor and process faults in plants. The detection and diagnosis method proposed is based on parity equations and on an adaptive observer based approach. The authors propose the use of dynamic features (static gain and bandwidth) of black-box (AutoRegressive with eXogenous input - ARX) models, as features for fault detection and diagnosis purposes. The ARX models of the thermal process under investigation are obtained by closed-loop recursive identification techniques. Residual analysis and geometrical tests are then used for fault detection and diagnosis, respectively. The proposed procedure has been evaluated using a benchmark thermal process.
Influence of dietary component manipulation and feed management strategies on growth and rumen development of weaned dairy heifers

Dennis, Tana S. Ph.D., Purdue University, August 2016. Influence of Dietary Component Manipulation and Feed Management Strategies on Growth and Rumen Development of Weaned Dairy Heifers. Animal Sciences. Major Professors: Jon Schoonmaker and Tamilee Nennich. Well-developed replacement heifers provide a central foundation for the continued success of the dairy industry. Emphasis on improving pre-weaned calf nutrition has predominated in the industry, but opportunities exist to improve postweaning heifer nutrition and management. We aimed to evaluate common feed management strategies seen in the industry and their effects on growth, feed efficiency (G:F), and rumen development of calves from birth to 8 mo of age using penand individually-fed animal trials. Little information exists regarding post-weaning performance and rumen development of calves fed conventional or high planes of nutrition pre-weaning; therefore, we evaluated two milk replacer feeding programs with two post-weaning diets differing in non-fiber carbohydrate (NFC) content. Overall, calves fed a high plane of nutrition pre-weaning with a low NFC post-weaning diet were 9.8 kg and 12.4 kg lighter than calves fed low or high planes of nutrition pre-weaning, respectively, with a high NFC post-weaning diet. Additionally, average daily gain (ADG) and frame height were increased for high NFC-fed animals regardless of pre-
Localization in Wireless Sensor Networks

In many applications, measured sensor data is meaningful only when the location of sensors is accurately known. Therefore, the localization accuracy is crucial. In this dissertation, both location estimation and location detection problems are considered. In location estimation problems, sensor nodes at known locations, called anchors, transmit signals to sensor nodes at unknown locations, called nodes, and use these transmissions to estimate the location of the nodes. Specifically, the location estimation in the presence of fading channels using time of arrival (TOA) measurements with narrowband communication signals is considered. Meanwhile, the Cramer-Rao lower bound (CRLB) for localization error under different assumptions is derived. Also, maximum likelihood estimators (MLEs) under these assumptions are derived. In large WSNs, distributed location estimation algorithms are more efficient than centralized algorithms. A sequential localization scheme, which is one of distributed location estimation algorithms, is considered. Also, different localization methods, such as TOA, received signal strength (RSS), time difference of arrival (TDOA), direction of arrival (DOA), and large aperture array (LAA) are compared under different signal-to-noise ratio (SNR) conditions. Simulation results show that DOA is the preferred scheme at the low SNR regime and the LAA localization algorithm provides better performance for network discovery at high SNRs. Meanwhile, the CRLB for the localization error using the TOA method is also derived. A distributed location detection scheme, which allows each anchor to make a decision as to whether a node is active or not is proposed. Once an anchor makes a decision, a bit is transmitted to a fusion center (FC). The fusion center combines all the decisions and uses a design parameter K to make the final decision. Three scenarios are considered in this dissertation. Firstly, location detection at a known location is considered. Secondly, detecting a node in a known region is considered. Thirdly, location detection in the presence of fading is considered. The optimal thresholds are derived and the total probability of false alarm and detection under different scenarios are derived. i
Negative Symptoms in Schizophrenia: A Review and Clinical Guide for Recognition, Assessment, and Treatment Neuropsychiatric Disease and Treatment

: Schizophrenia is frequently a chronic and disabling disorder, characterized by heterogeneous positive and negative symptom constellations. The objective of this review was to provide information that may be useful for clinicians treating patients with negative symptoms of schizophrenia. Negative symptoms are a core component of schizophrenia that account for a large part of the long-term disability and poor functional outcomes in patients with the disorder. The term negative symptoms describes a lessening or absence of normal behaviors and functions related to motivation and interest, or verbal/emotional expression. The negative symptom domain consists of ﬁ ve key constructs: blunted affect, alogia (reduction in quantity of words spoken), avolition (reduced goal-directed activity due to decreased motivation), asociality, and anhedonia (reduced experience of pleasure). Negative symptoms are common in schizophrenia; up to 60% of patients may have prominent clinically relevant negative symptoms that require treatment. Negative symptoms can occur at any point in the course of illness, although they are reported as the most common ﬁ rst symptom of schizophrenia. Negative symptoms can be primary symptoms, which are intrinsic to the underlying pathophysiology of schizophrenia, or secondary symptoms that are related to psychiatric or medical comorbidities, adverse effects of treatment, or environmental factors. While secondary negative symptoms can improve as a consequence of treatment to improve symptoms in other domains (ie, positive symptoms, depressive symptoms or extrapyr-amidal symptoms), primary negative symptoms generally do not respond well to currently available antipsychotic treatment with dopamine D 2 antagonists or partial D 2 agonists. Since some patients may lack insight about the presence of negative symptoms, these are generally not the reason that patients seek clinical care, and clinicians should be especially vigilant for their presence. Negative symptoms clearly constitute an unmet medical need in schizophrenia, and new and effective treatments are urgently needed.