nils-herrmann/clean_scirepeval huggingface dataset:
Cyber Physical Attack Resilient Wide Area Monitoring, Protection, and Control for the Power Grid
Venue: Proceedings of the IEEE
Year: 2017

Cybersecurity and resiliency of wide area monitoring, protection, and control (WAMPAC) applications is critically important to ensure secure, reliable, and economical operation of the bulk power system. WAMPAC relies heavily on the security of measurements and control commands transmitted over wide area communication networks for real time operational, protection, and control functions. The current "N 1" security criterion for grid operation is inadequate to address malicious cyber events; therefore, it is important to fundamentally redesign WAMPAC and to enhance energy management system applications to make them attack resilient. In this paper, we present three key contributions to enhance the cybersecurity and resiliency of WAMPAC. First, we describe an end to end attack resilient cyber physical security framework for WAMPAC applications encompassing the entire security life cycle including risk assessment, attack prevention, attack detection, attack mitigation, and attack resilience. Second, we describe a defense in depth architecture that incorporates attack resilience at both the infrastructure layer and the application layer by leveraging domain specific security approaches at the WAMPAC application layer in addition to traditional cybersecurity measures at the information technology infrastructure layer. Third, we discuss several attack resilient algorithms for WAMPAC that leverage measurement design and cyber physical system model based anomaly detection and mitigation along with illustrative case studies. We believe that the research issues and solutions identified in this paper will open up several avenues for research in this area. In particular, the proposed framework, architectural concepts, and attack resilient algorithms would serve as essential building blocks to transform the "fault resilient" grid of today into an "attack resilient" grid of the future.
Post traumatic stress disorder and coping strategies among adult survivors of earthquake, Nepal
Venue: BMC Psychiatry
Year: 2019

BackgroundPost traumatic stress disorder (PTSD) is the most frequently reported psychiatric morbidity among the survivors of natural disasters. It is the main hindrance to rehabilitate their life. However its prevalence particularly in Nepal is largely unknown.Aims and objectivesTo investigate the prevalence of post traumatic stress disorder and use of coping strategies among the adult survivors of earthquake.MethodsA cross sectional descriptive study was carried out on a sample of 291 adult survivors after 10 months of Nepal Earthquake 2015.  Nuwakot district with multistage sampling (cluster sampling and systematic random sampling) method. PTSD checklist 5 was used to measure PTSD, and adapted and modified brief cope scale was used to assess coping strategies. Data were analyzed using descriptive and inferential statistics (independent t test and one way ANOVA) at 5% level of significance.ResultsStudy findings revealed that PTSD was prevalent among 24.10% of adult survivors with highest intrusion symptoms (3.24 0.71) It was significantly associated with age (p 0.017) sex (p 0.013) education (p 0.0001) and injury to self (p 0.003) Elderly, females, illiterates and those who were injured during earthquake are at more risk for PTSD. Highest used coping strategy was active coping (2.92 0.51) Survivors not having PTSD scored more on active coping (p 0.0001) and self distraction coping (p 0.006) while those with PTSD mostly used passive coping (p 0.0001) religious coping (p 0.0001) and substance use coping (p 0.0001).ConclusionEarthquake poses significant impact on mental health of the survivors. After 10 months of devastating earthquake, prevalence of PTSD among the survivors is high. Maladaptive coping strategies further increase possibility of PTSD. Effective screening and awareness program regarding promotion of positive coping strategies among the vulnerable groups should be reinforced for prevention of psychiatric morbidity among the survivors of earthquake.
A statistical model for synthesis of detailed facial geometry
Venue: SIGGRAPH '06
Year: 2006

Detailed surface geometry contributes greatly to the visual realism of 3D face models. However, acquiring high resolution face geometry is often tedious and expensive. Consequently, most face models used in games, virtual reality, or computer vision look unrealistically smooth. In this paper, we introduce a new statistical technique for the analysis and synthesis of small three dimensional facial features, such as wrinkles and pores. We acquire high resolution face geometry for people across a wide range of ages, genders, and races. For each scan, we separate the skin surface details from a smooth base mesh using displaced subdivision surfaces. Then, we analyze the resulting displacement maps using the texture analysis/synthesis framework of Heeger and Bergen, adapted to capture statistics that vary spatially across a face. Finally, we use the extracted statistics to synthesize plausible detail on face meshes of arbitrary subjects. We demonstrate the effectiveness of this method in several applications, including analysis of facial texture in subjects with different ages and genders, interpolation between high resolution face scans, adding detail to low resolution face scans, and adjusting the apparent age of faces. In all cases, we are able to re produce fine geometric details consistent with those observed in high resolution scans.
Confocal surface plasmon microscopy with vortex beam illumination for biosensing application: Label free biosensing application of confocal surface plasmon microscope
Venue: 2015 8th Biomedical Engineering International Conference (BMEiCON)
Year: 2015

We have developed surface plasmon interferometric microscope and demonstrated that by integrating a phase spatial light modulator (SLM) on conjugate back focal plane of confocal microscope objective lens, this enables us to perform surface plasmon phase imaging and phase sensing using phase stepping interferometry over well confined region [1 6] In this paper, we address one of the key limitations of the system, which IS data acquisition time. Since phase stepping algorithm requires 3 (for 120 degrees step) to 4 (for 90 degrees step) phases in order to obtain a relative phase value between the reference beam and the signal beam; therefore the phase pattern on the SLM needs to be frequently updated and the liquid crystal takes time to response; this slowsdown the data accusation process. Moreover acquiring the phase steps at different times increases microphonic noise and introduces artefacts into real time experiments, such as protein binding. In this paper, we show that a simple and innovative method to overcome these issues is to employ a vortex reference beam provided by 0 to 2p rad topological phase pattern on the SLM; this enables us to obtain multiple phase information in one single shot measurement without updating the SLM pattern.
Secondary Refinements of Free Perforator Flaps for Lower Extremity Reconstruction
Venue: Plastic and reconstructive surgery
Year: 2011

The aim of lower extremity reconstruction has focused on early wound coverage and functional recovery but rarely aesthetics. Free muscle flaps provide durable coverage; however, they require skin graft coverage and result in muscle atrophy limiting future revisions. Perforator based flap reconstructions can be easily elevated to allow for both orthopedic and contouring procedures. The authors reviewed the role of secondary procedures in achieving improved functional and aesthetic results following perforator flap reconstruction of lower extremity defects.  A retrospective review identified 70 patients treated at R Adams Cowley Shock Trauma Center with 73 free perforator flaps for coverage of lower extremity wounds from 2002 to 2009.  Seventy patients were identified who underwent reconstruction with a perforator flap: 65 with anterolateral thigh flaps and five with superficial circumflex iliac artery flaps. Nineteen of these patients underwent 32 refinement procedures of the reconstructed limb. Fifteen refinements were performed with suction assisted lipectomy, 21 with complex tissue rearrangement, including sharp debulking, and one with tissue expanders. Twenty seven of the 70 patients underwent 40 orthopedic related secondary procedures in which the free flap was elevated. The most common reasons for the orthopedic interventions were tibial nonunion requiring bone grafting (n 17) and osteomyelitis (n 11)  Limb salvage remains the primary goal of lower extremity reconstruction. Following convalescence and functional recovery, however, appearance becomes increasingly important with regard to quality of life. Initial flap selection with free perforator flaps, meticulous inset, and secondary refinements provide superior functional and aesthetic outcomes.
Administration Versus Politics in Theories of Democratic Budgeting
Year: 2019

All but one American state has some constitutional requirement for a balanced budget but few of them operate this way. Moreover, in 1979 the federal government enacted a public law that required a balanced budget by 1982. The law has not been repealed but neither have budgets become balanced. These observations point toward a dichotomy within the theory of democratic budgeting. One side of this dichotomy treats budgeting as an administrative matter of selecting rules for rational action. The other side recognizes that democratic budgeting has political character that cannot be reduced wholly to self enforcing rules. Personal budgeting is a simple matter of individual rationality. In contrast, democratic budgeting entails interaction among individuals, and that interaction is not readily reducible to individual rationality. At this point, democratic budgeting butts against Carl Schmitt's (1932) recognition of the autonomy of the political within society.
Min Entropy Latent Model for Weakly Supervised Object Detection
Venue: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Year: 2018

Weakly supervised object detection is a challenging task when provided with image category supervision but required to learn, at the same time, object locations and object detectors. The inconsistency between the weak supervision and learning objectives introduces randomness to object locations and ambiguity to detectors. In this paper, a min entropy latent model (MELM) is proposed for weakly supervised object detection. Min entropy is used as a metric to measure the randomness of object localization during learning, as well as serving as a model to learn object locations. It aims to principally reduce the variance of positive instances and alleviate the ambiguity of detectors. MELM is deployed as two sub models, which respectively discovers and localizes objects by minimizing the global and local entropy. MELM is unified with feature learning and optimized with a recurrent learning algorithm, which progressively transfers the weak supervision to object locations. Experiments demonstrate that MELM significantly improves the performance of weakly supervised detection, weakly supervised localization, and image classification, against the state of the art approaches.
CCC: Weakly Supervised Semantic Segmentation using Class Contribution Classification
Venue: 2021 International Conference on Electronics, Information, and Communication (ICEIC)
Year: 2021

We propose a new semantic Segmentation technique that depends on the convolutional neural network of Xception using a modified categorical cross entropy function to perform class contribution classification. We introduce a class contribution function for each class contribution in the image instead of categorical cross entropy for maximum class classification. This approach is to be used for weakly supervised semantic segmentation (WSSS) using image level annotation instead of the pixel level annotations used in fully supervised semantic segmentation. We trained and tested our approach on both PASCAL VOC2007 and VOC2012 datasets. We show that our approach outperformed many other weakly supervised methods, specifically, it can attain a segmentation accuracy of 49.7% on PASCAL VOC2007 test set and an accuracy of 41.3% on PASCAL VOC2012 test set while the network is trained to learn the semantics of the objects in the image using the cheap image label annotation instead of the expensive and time consuming segmentation masks.
Self powered intelligent buoy system by water wave energy for sustainable and autonomous wireless sensing and data transmission
Venue: Nano Energy
Year: 2019

Harvesting ocean wave energy is a killer application of triboelectric nanogenerator (TENG) for advantages in simple mechanism, high power density and high efficiency at low frequency. Here we report a self powered intelligent buoy system (SIBS) in which a high output multilayered TENG is used for water wave energy harvesting. With a power management module, the output voltage can be converted and regulated as a steady DC voltage of 2.5 V for the operations of a microprogrammed control unit (MCU) several micro sensors and a transmitter. With the intelligent monitoring mechanism of the MCU, the harvested energy can be deployed for each sensor with different priority and data transmission cycle, and the SIBS can be at standby and active status by itself at different energy levels. At a wave frequency of 2 Hz, the SIBS can provide an average output power density of 13.2 mW/m2 and realize sustainable and autonomous wireless sensing for acceleration, magnetic intensity and temperature in range of 15 m, with amount of 19 bytes every 30 s. The SIBS has first demonstrated a complete TENG based micro energy solution for self powered intelligent system, including energy harvesting, management, deployment and utilization, with an unattended manner and infinite lifetime. As a significant milestone for the TENG, this work has provided a universal platform for self powered wireless sensor network nodes and exhibited broad prospects in internet of things, big data, artificial intelligence and blue energy.
Pengendalian Kualitas Produk dengan Metode Six Sigma, Seven Tools, dan Kaizen untuk Mengurangi Produk Cacat di PT. Mitra Rekatama Mandiri
Year: 2016

PT. Mitra Rekatama Mandiri is one of the manufacturing industries engaged in metal casting and machining which manages and produces metal castings, with output in the form of components of agricultural equipment and mining, which is the pulley. The work carried out by machine and manually. The production process is still a lot of damage to products that are not suitable quality standards set by the industry. Therefore, to identify, analyze and repair the damage factor products used in the production process quality control methods, by Six Sigma and seven tools and Kaizen. Based on the research results in the form of data processing and analysis with DMAI cycle in the concept of Six Sigma DMAIC define phase characterizing the quality (CTQ) attribute data in the form of as many as 10 different types of damage. The results of the identification process to map control measure p on stage. The results of the baseline measurements of corporate performance in the production process of finishing obtained DPMO value of 88.716 which may mean that a million chance there will be 88.716. Producted possibility of the product damage. Finishing the production process is at 3:57 sigma level. The result of identification with Pareto diagram and with CTQ most dominant cause damage that is kind rantap of 98% followed by the kind of broken mengsle 94% 78% kropos kind of broken, damaged type of lump 46% of the total to be damaged by 265. identify problems damage with fish bone diagram to determine the factors that cause the damage. In the improve phase seek corrective action plan with Kaizen Kaizen implementation of two instruments, namely Five M Check List and Five Step Plan. From the analysis, it can be concluded that the main cause of damage is the human factor and the environment, and as well as Kaizen implementation toolsaEUR(tm) the main policy that must be executed by the management company that surveillance or tighter control every stage of the process. Improvement by analyzing the factors that cause defective products made to reduce the most dominant types of damaged, so that product quality is maintained according to customer demand.  defect, Kaizen, quality control, seven tools, six sigma
Evaluation and Dissemination of a Checklist to Improve Implementation of Work Environment Initiatives in the Eldercare Sector: Protocol for a Prospective Observational Study
Venue: JMIR research protocols
Year: 2020

To measure sustainable improvements in the work environment, a flexible and highly responsive tool is needed that will give important focus to the implementation process. A digital checklist was developed in collaboration with key stakeholders to document the implementation of changes in eldercare sector workplaces.  This paper describes the study protocol of a dissemination study that aims to examine when, why, and how the digital checklist is spread to the Danish eldercare sector following a national campaign particularly targeting nursing homes and home care.  This prospective observational study will use quantitative data from Google Analytics describing use of the checklist as documented website engagement, a survey among members in the largest union in the sector, information from a central business register, and monitoring of campaign activities. The evaluation will be guided by the five elements of the RE AIM framework: reach, effectiveness, adoption, implementation, and maintenance.  The study was approved in June 2016 and began in October 2018. The campaign that is the foundation for the evaluation began in 2017 and ended in 2018. However, the webpage where we collect data is still running. Results are expected in 2020.  This protocol provides a working example of how to evaluate dissemination of a checklist to improve implementation of work environment initiatives in the eldercare sector in Denmark. To our knowledge, implementation in a nationwide Danish work environment has not been previously undertaken. Given that the checklist is sector specific for work environment initiatives and developed through systematic collaboration between research and practice, it is likely to have high utility and impact; however, the proposed evaluation will determine this. This study will advance dissemination research and, in particular, the evaluation of the impact of these types of studies. Finally, this study advances the field through digital tools that can be used for evaluation of dissemination efforts (eg, Google Analytics associated with website) in the context of a rigorous research design activity.
Additive manufacturing techniques for fabricating complex ceramic components from preceramic polymers
Year: 2017

Capsule summary THE MATERIALS Manufacturers can use preceramic polymers to produce ceramic components in a range of compositions using a variety of additive manufacturing technologies. Preceramic polymers even can overcome some of the problems that are intrinsic to additive manufacturing in general. THE APPLICATION Modifying the composition, molecular architecture, and molecular weight of preceramic polymers allows adaptation of these materials to specific processing requirements of individual additive manufacturing technologies. THE OPPORTUNITY Further development of new additive manufacturing technologies, in addition to improvement of existing technologies, will enable manufacturing of advanced ceramic components with enhanced mechanical characteristics and new functional properties.
Impact energetique d'un couplage de procedes adsorption photocatalyse pour traiter l'air interieur
Year: 2018

Dans le cadre de l'appel a projet "Vers des batiments responsables a l'horizon 2020" realise par l'ADEME, le projet CUBAIR a ete lance en 2014. Un des objectifs de ce projet concerne l'impact energetique d'un prototype installe dans un batiment a Paris (le CVRH) Un bilan thermique sur la salle concernee a permis de caracteriser le comportement thermique de celle ci, en l'absence du systeme de depollution dans un premier temps, puis en sa presence. L'impact energetique est principalement determine par un calcul de puissance de chauffage et/ou de climatisation.
Voxelated soft matter via multimaterial multinozzle 3D printing
Venue: Nature
Year: 2019

There is growing interest in voxelated matter that is designed and fabricated voxel by voxel1 4. Currently, inkjet based three dimensional (3D) printing is the only widely adopted method that is capable of creating 3D voxelated materials with high precision1 4, but the physics of droplet formation requires the use of low viscosity inks to ensure successful printing5. By contrast, direct ink writing, an extrusion based 3D printing method, is capable of patterning a much broader range of materials6 13. However, it is difficult to generate multimaterial voxelated matter by extruding monolithic cylindrical filaments in a layer by layer manner. Here we report the design and fabrication of voxelated soft matter using multimaterial multinozzle 3D (MM3D) printing, in which the composition, function and structure of the materials are programmed at the voxel scale. Our MM3D printheads exploit the diode like behaviour that arises when multiple viscoelastic materials converge at a junction to enable seamless, high frequency switching between up to eight different materials to create voxels with a volume approaching that of the nozzle diameter cubed. As exemplars, we fabricate a Miura origami pattern14 and a millipede like soft robot that locomotes by co printing multiple epoxy and silicone elastomer inks of stiffness varying by several orders of magnitude. Our method substantially broadens the palette of voxelated materials that can be designed and manufactured in complex motifs. Voxelated soft matter is designed and fabricated using multimaterial multinozzle three dimensional printing, which switches between different viscoelastic inks along the same print filament to print multiple materials simultaneously.
Smart Fleet Management System Using IoT, Computer Vision, Cloud Computing and Machine Learning Technologies
Venue: 2019 IEEE 5th International Conference for Convergence in Technology (I2CT)
Year: 2019

The objective of this paper was to present the effective use of niche technologies in solving most critical problems of Fleet Industry. The proposed fleet management system described in the paper used a rich set of technologies like Internet of Things(IoT) Cloud Computing, Computer Vision, Machine Learning, Deep Learning and Embedded. IBM Watson IoT and Heroku platforms hosted the application to receive data from vehicle dashboard device. Driver's face authentication and driving pattern monitoring, Fuel Consumption prediction modules used OpenCV (Computer Vision) SVN (Machine Learning) and CNN (Deep Learning) techniques. Vehicle's Telematics, deviation from route, unauthorized entry in the container, continuous monitoring of trucks internal environment was handled by a high end embedded device with a set of sensor box, cameras, OBD P device and a gateway. Real data was collected to train and test the face detection and authentication models used in the system. Simulation results demonstrated that the proposed approach can achieve realistic demand of handing and manipulating humongous data coming every few seconds from several vehicles through IoT, NoSQL CloudantDB database and Cloud Computing. The paper also presented the architecture of the system and experimentation results done for various modules of the system.