Miracle-dz/UniFAR-FTUs huggingface dataset:
An Access Control System using Bimodal Biometrics

In today's society, advances in technology have made life easier by providing us with higher levels of knowledge through the invention of different devices. However, each technological innovation harbours the potential of hidden threats to its users. One major threat is theft of private or personal data, information and properties. As digital data become more prevalent, users try to secure their information with highly encrypted passwords and ID cards. However, the misuse and theft of these security measures are also on the rise, taking advantage of security flaws in ID cards result in cards being duplicated or counterfeited and being misused. This increasing battle with cyber security has led to the birth of biometric security systems. In this work, iris and fingerprint samples were acquired using the iris camera and Secugen pattern extracting sensor respectively. The pre-processing of the acquired images were done, after which templates were generated and stored. Verification of the acquired images was done and voting fusion techniques was used to fuse the information presented by individual modalities. A door prototype was constructed with electric circuit design and an iris and fingerprint recognition software development using MatLab. was interfaced with the door prototype. The developed system was tested widely with the pre-enrolled subjects as well as freshly introduced subjects. The red light indicator showed the hardware and software connection and door lock . With template match, the door opens ( green light indicator comes on accompanied with the buzzer), and with non-match, the door is not opened (red light remains and the buzzer is off). General Terms Security, Pattern Recognition, Image Processing
Scientific support for a plastic bag reduction law

This report was compiled by the Scientist Action and Advocacy Network and summarizes evidence from academic and governmentcommissioned studies. Sections 2 and 3 were curated by Professor Tatiana A. Homonoff of the R.F. Wagner School of Public Service at New York University. Dr. Homonoff is an expert on the behavioral effects of fees and incentives, and the lead author of two studies described here [1, 2]. For questions or comments, email info@scaan.net.
Extending the Bayesian arsenal : An assumption check for normality

Funding information This work is made possible by the Research Masters thesis committee. This thesis outlines the development and application of a new Bayesian assumption check for assessing deviations from normality in the distribution of a variable. The proposedmethod yields Bayes factors that quantify evidence for normality against non-normality, bi-modality and skewness. Results from simulation studies comparing Bayes factor behavior and sensitivity of the candidate models are presented, indicating that identifying these deviations is feasible and effortless. Furthermore, an investigation into the test’s robustness to the prior distribution is presented and several practical implementations of the assumption checks are illustrated.
International Conference on Applied Energy ( ICAE 2018 ) , 22-25 August 2018 , Hong Kong , China A Review of Lithium-Ion Battery for Electric Vehicle Applications and Beyond

District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
What Elements are Essential to Recognize Human Actions?

RGB image has been widely used for human action recognition. However, it could be redundant to include all information for human action depiction. We thus ask the following question: What elements are essential for human action recognition? To this end, we investigate several different human representations. These representations emphasize dissimilarly on elements (e.g. background context, actor appearance, and human shape). Systematic analysis enables us to find out essential elements as well as unnecessary contents for human action description. More specifically, our experimental results demonstrate the following: Firstly, both context-related elements and actor appearance are not vital for action recognition in most cases. But an accurate and consistent human representation is important. Secondly, essential human representation ensures better performance and cross-dataset transferability. Thirdly, fine-tuning works only when networks acquire essential elements from human representations. Fourthly, 3D reconstruction-related representation is beneficial for human action recognition tasks. Our study shows researchers need to reflect on more essential elements to depict human actions, and it is also instructive for practical human action recognition in real-world scenarios.
Low-Overhead SEU-Tolerant Latches

Two latches,named SEUT-A and SEUT-B respectively,designed to tolerate radiation-induced Single Event Upset(SEU) are presented.SEU immunity is achieved by storing data on different nodes and through the recovery mechanism of the circuits.Neither of the designs needs transistor sizing to be functional and SEU-tolerant,so it can be implemented by small devices.The proposed structures are implemented and simulated using a standard 0. 18μm logic process model.Simulation results show that both of the proposed latches are SEU immune and less power-consumptive compared to the conventional unhardened one.SEUT-A uses only 11% more transistors and is 6% slower,whereas SEUT-B uses 56% more transistors but is 43% faster than the conventional one.
TDNet-A Generative Model for Taxi Demand Prediction

Supplying the right amount of taxis in the right place at the right time is very important for taxi companies. In this paper, the machine learning model Taxi Demand Net (TDNet) is presented which predicts short-term taxi demand in different zones of a city. It is based on WaveNet which is a causal dilated convolutional neural net for time-series generation. TDNet uses historical demand from the last years and transforms features such as time of day, day of week and day of month into 26-hour taxi demand forecasts for all zones in a city. It has been applied to one city in northern Europe and one in South America. In northern europe, an error of one taxi or less per hour per zone was achieved in 64% of the cases, in South America the number was 40%. In both cities, it beat the SARIMA and stacked ensemble benchmarks. This performance has been achieved by tuning the hyperparameters with a Bayesian optimization algorithm. Additionally, weather and holiday features were added as input features in the northern European city and they did not improve the accuracy of TDNet.
Mechanisms of amplitude modulation in wind turbine noise

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Mechanisms of amplitude modulation in wind turbine noise Malcom Smith, Andrew Bullmore, Matthew Cand, Robert Davis
More than Smart Speakers: Security and Privacy Perceptions of Smart Home Personal Assistants

Smart Home Personal Assistants (SPA) such as Amazon Echo/Alexa and Google Home/Assistant have made our daily routines much more convenient, allowing us to complete tasks quickly and efﬁciently using natural language. It is believed that around 10% of consumers around the world already own an SPA, and predictions are that ownership will keep rising. It is therefore paramount to make SPA secure and privacy-preserving. Despite the growing research on SPA security and privacy, little is known about users’ security and privacy perceptions concerning SPA complex ecosystem, which involves several elements and stakeholders. To explore this, we considered the main four use case scenarios with distinctive architectural elements and stakeholders involved: using built-in skills, third-party skills, managing other smart devices, and shopping, through semi-structured interviews with SPA users. Using a grounded theory approach, we found that users have incomplete mental models of SPA, leading to different perceptions of where data is being stored, processed, and shared. Users’ understanding of the SPA ecosystem is often limited to their household and the SPA vendor at most, even when using third-party skills or managing other smart home devices. This leads to incomplete threat models (few threat agents and types of attacks) and non-technical coping strategies they implement to protect themselves. We also found that users are not making the most of the shopping capabilities of SPA due to security and privacy concerns; and while users perceive SPA as intelligent and capable of learning, they would not like SPA learning everything about them. Based on these ﬁndings, we discuss design recommendations.
Úzkost u pacientů s alergií a atopickou dermatitidou

Význam přehledu Lidé trpící alergiemi se často vyznačují specifickým psychologickým profilem se sklony k úzkosti, depresi a emoční vzrušivosti. Emoční stres vyvolává příznaky alergie nejen zvyšováním míry úzkosti, ale i nepříznivými zásahy do funkce imunokompetentních buněk. Hlavním cílem tohoto přehledu je shrnout nové poznatky o vztahu mezi úzkostí a hypersenzitivitou u alergiků, zejména pacientů s atopickou dermatitidou, v kontextu psychoneuroimunologie.
Invited Paper : Spectrum Matching in Licensed Spectrum Sharing

Spectrum sharing is one of the promising solutions to meet the spectrum demand in 5G networks that results from the emerging services like machine to machine and vehicle to infrastructure communication. The idea is to allow a set of entities access the spectrum whenever and wherever it is unused by the licensed users. In the proposed framework, different spectrum provider (SP) networks with surplus spectrum available may rank the operators requiring the spectrum, called spectrum users (SUs) hereafter, differently in terms of their preference to lease spectrum, based for example on target business market considerations of the SUs. Similarly, SUs rank SPs depending on a number of criteria, for example based on coverage and availability in a service area. Ideally, both SPs and SUs prefer to provide/get spectrum to/from the operator of their first choice, but this is not necessarily always possible due to conflicting preferences. We apply matching theory algorithms with the aim to resolve the conflicting preferences of the SPs and SUs and quantify the effect of the proposed matching theory approach on establishing preferred (spectrum) provider-user network pairs. We discuss both one-to-one and many-to-one spectrum sharing scenarios and evaluate the performance using Monte Carlo simulations. The results show that comprehensive gains in terms of preferred matching of the provider-user network pairs can be achieved by applying matching theory for spectrum sharing as compared to uncoordinated spectrum allocation of the available spectrum to the SUs.
Green Supply Chain Management Practices in Developing Countries - Case Study from Jordan

Purpose–Organizations worldwide adopt different Green Supply Chain Management (GSCM) practices in response to raising environmental concerns regarding pollution, climate change, natural resources depletion, and environmental degradation. Most of GSCM research has been conducted in developed countries; only few studies addressed developing countries. There is a dearth of research in the Middle East region, and even avoid of research in Jordan. Therefore, this paper aims to fill this gap by exploring the adoption of GSCM practices in the context of a developing country which is Jordan. Design/methodology/approach-A single case study is used to collect rich and in-depth information to explore the adoption of GSCM practices in developing countries. Data is collected through semi-structured interviews and documentation. Data is coded and analyzed using Nvivo 12. Findings -Using data from Jordan, this paper demonstrates that manufacturers in developing countries are showing interest and commitment towards protecting the environment despite the absence of governmental regulations by adopting a range of GSCM practices. Originality/value-The paper provides some insights on the adoption of GSCM practices in developing countries context.
Fictitious Self-Play for Vehicle-to-Grid Game with Imperfect Information

The vehicle-to-grid (V2G) technique, which enables the bidirectional power exchange between electric vehicles (EVs) and power grid, becomes promising in current smart grid research. In this paper, a game theoretic model is proposed to study the interaction among EVs in a V2G system with V2G technique incorporated. This V2G game is a game with imperfect information in which each EV does not any private information of other EVs. To find the Nash equilibrium of this game, a machine learning-based algorithm is proposed based on fictitious self-play. Our simulation results show that the proposed algorithm can approximately converge to the Nash equilibrium of the game under imperfect information. This demonstrates the efficacy of the proposed algorithm in solving the V2G game. A pre-training approach is also proposed to accelerate the convergence of the algorithm by using the historical data from the interactions of EVs in the game.
Encoder Decoder Decoder Regularizer

Motion sensors such as accelerometers and gyroscopes measure the instant acceleration and rotation of a device, in three dimensions. Raw data streams from motion sensors embedded in portable and wearable devices may reveal private information about users without their awareness. For example, motion data might disclose the weight or gender of a user, or enable their re-identification. To address this problem, we propose an on-device transformation of sensor data to be shared for specific applications, such as monitoring selected daily activities, without revealing information that enables user identification. We formulate the anonymization problem using an information-theoretic approach and propose a new multi-objective loss function for training deep autoencoders. This loss function helps minimizing user-identity information as well as data distortion to preserve the application-specific utility. The training process regulates the encoder to disregard user-identifiable patterns and tunes the decoder to shape the output independently of users in the training set. The trained autoencoder can be deployed on a mobile or wearable device to anonymize sensor data even for users who are not included in the training dataset. Data from 24 users transformed by the proposed anonymizing autoencoder lead to a promising trade-off between utility and privacy, with an accuracy for activity recognition above 92% and an accuracy for user identification below 7%.
Novel Astroviruses in Children , Egypt

1. Wyss S, Deb A, Watson R, Hammer S. Radiographic measurements for PDD diagnosis in Spix’s macaws (Cyanopsitta spixii) at Al Wabra Wildlife Preservation (AWWP), Qatar. In: Proceedings of the International Conference on Diseases of Zoo and Wild Animals. Zurich: University of Zurich; 2009. p. 349–54. 2. Lierz M, Herden C, Herzog S, Piepenbring A. Proventricular dilatation disease and avian bornavirus as a possible cause. Tieraerztl Prax (K). 2010;38:87–94. 3. Kistler AL, Gancz A, Clubb S, SkewesCox P, Fischer K, Sorber K, et al. Recovery of divergent avian bornaviruses from cases of proventricular dilatation disease: identifi cation of a candidate etiologic agent. Virol J. 2008;5:88. doi:10.1186/1743-422X-5-88 4. Honkavuori KS, Shivaprasad HL, Williams BL, Quan PL, Hornig M, Street C, et al. Novel borna virus in psittacine birds with proventricular dilatation disease. Emerg Infect Dis. 2008;14:1883–6. doi:10.3201/eid1412.080984 5. Heffels-Redmann U, Enderlein D, Herzog S, Herden C, Piepenbring A, Neumann D, et al. Occurrence of avian bornavirus infection in captive psittacines in various European countries and its association to proventricular dilation disease. Avian Pathol. 2011; 40:419–26. 6. Lierz M, Hafez HM, Honkavuori KS, Gruber AD, Olias P, Abdelwhab EM, et al. Anatomical distribution of avian bornavirus in parrots, its occurrence in clinically healthy birds and ABV-antibody detection. Avian Pathol. 2009;38:491–6. doi:10.1080/03079450903349238 7. Gancz AY, Kistler AL, Greninger AL, Farnoushi Y, Mechani S, Perl S, et al. Experimental induction of proventricular dilatation disease in cockatiels (Nymphicus hollandicus) inoculated with brain homogenates containing avian bornavirus 4. Virol J. 2009;6:100. doi:10.1186/1743422X-6-100 8. Gray P, Hoppes S, Suchodolski P, Mirhosseini N, Payne S, Villanueva I, et al. Use of avian bornavirus isolates to induce proventricular dilatation disease in conures. Emerg Infect Dis. 2010;16:473–9. doi:10.3201/eid1603.091257 9. Raghav R, Taylor M, DeLay J, Ojkic D, Pearl DL, Kistler AL, et al. Avian bornavirus is present in many tissues of psittacine birds with histopathologic evidence of proventricular dilatation disease. J Vet Diagn Invest. 2010;22:495–508. doi:10.1177/104063871002200402 10. Herzog S, Enderlein D, Heffels-Redmann U, Piepenbring A, Neumann D, Kaleta EF, et al. Indirect immunofl uorescence assay for intra vitam diagnosis of avian bornavirus infection in psittacine birds. J Clin Microbiol. 2010;48:2282–4. doi:10.1128/ JCM.00145-10
Epigenetic Regulation of P21, RASSF1, PTEN and P53 in Human Breast Cancer Cells Using Different Chemotherapeutic Drugs

Breast cancer is considered one of the most heterogeneous diseases that might be difficult to characterize and then to treat. Several research groups worldwide have explored different genetic and epigenetic approaches that might help. In the present study, different kinds of chemotherapeutic drugs have been applied to breast cancer cells (MCF-7) to assess their role in changing the methylome of these malignant cells. Global methylation was quantified in treated and untreated cells and the results obtained indicated that the drugs/drug combinations applied (temozolomide, carboplatin, sodium phenylbutyrate, cyclophosphamide, erlotinib, procaine, vorinostat and combinations) have a tremendous effect on the methylation landscape of the cells. Real time PCR was employed to assess the level of expression of different tumor suppressor genes; RASSF1, PTEN, P21 and P53. The results indicated that applying different drugs/drug combinations has affected the level of gene expression of the above mentioned genes. All drugs/drug combinations were incubated for 4 and 8 days with the cells. The four-day and the eight-day incubation have resulted in down regulation of P53, PTEN and P12 while an up regulation of RASSF1 gene was obtained. This might indicate that the time of incubation has no effect on the regulation of the expression of these genes. However, this study needs more conformational investigation to elucidate the mode of action of the used drugs in epigenetically regulating these genes.
Demonstrating PID Control Principles using an Air Heater and LabVIEW

At Telemark University College in Norway a number (eventually eight) small air heater lab stations have developed for the purpose of effectively demonstrating and/or learning basic PID control skills. This paper describes a number of practical control topics that can be highlighted by this lab station, namely control system performance indexes, control principles, and controller tuning. The control systems are implemented on a PC which runs the graphical programming tool LabVIEW. The analog voltage I/O between the lab station and the PC is implemented with an inexpensive USB-based I/O device. The experiences with this system have been positive.
Recurrent Focal Myositis of the Left Thigh – rare but treatable inflammatory myopathy-A case report

Focal myositis presents as an acute and localized inflammation of the muscle without systemic involvement. The etiology is unknown. Several case reports in the literature have described different presentations of the condition, the majority affecting the limbs with a spectrum of clinical progression, laboratory, and radiological findings. It is often confused with infection, muscle tumor such as sarcoma, paraneoplastic syndrome or even immune-mediated polymyositis. Delay in diagnosis and inappropriate treatment may lead to recurrence of the condition. We report a case of recurrent focal myositis of the left thigh in a man in whom optimal treatment commenced six months after the onset led to regression of his symptoms and signs. Keyword: Focal myositis, muscle biopsy, magnetic resonance imaging.
Topological Path Planning For Crowd Navigation

Real-time navigation in dense human environments has been a challenging problem in robotics for years. Most existing path planners fail to account for the dynamics of pedestrians because introducing time as an additional dimension in search space is computationally prohibitive. Alternatively, most local motion planners only address imminent collision avoidance and fail to offer long-term optimality. In this work, we present an approach, called Dynamic Channels, to solve this global to local quandary. Our method combines the high-level topological path planning with low-level motion planning into a complete pipeline. By formulating the path planning problem as graph-searching in the triangulation space, our planner is able to explicitly reason about the obstacle dynamics and capture the environmental change efficiently. We evaluate efficiency and performance of our approach on public pedestrian datasets and compare it to a state-of-the-art planning algorithm for dynamic obstacle avoidance.