Miracle-dz/UniFAR-FTUs huggingface dataset:
Healing Plants: Medicine of the Florida Seminole Indians

The first published record of Florida Seminole herbal medicine and ancient healing practices, Healing Plants is a colorfully illustrated compendium of knowledge and practices passed down orally to Alice Snow from generations of her Native American ancestors. The authors' overview of Seminole history, native medicine, and the life of Snow, a Seminole herbalist (illustrated with personal photographs) places the healing practices in their cultural context and describes actual treatments. Charts with plant names in Creek, Mikasuki, and English and lists of plant properties with their common and botanical names offer easy reference. Drawings and color photographs of the plants provide clear illustrations for the collector. Herbal treatments include those intended for babies, for people who have had a hysterectomy, a stroke, blackouts or shortness of breath, "monkey sickness," alligator bites, or a speeding heart, people who have pain or have been ill for a long time, who like to sleep all the time or can't sleep because of worry or bad dreams, who are pregnant or "on the wagon" or have lost wives or husbands. Alice Snow is both a traditional Seminole and a cultural innovator who combines old and new methods of preserving and teaching "Indian medicine. " Her record of medicinal plants and remedies is her contribution toward helping the Seminoles to hold onto their past while living in the present and moving toward the future. Though the book does not reveal the tribal doctors' secret healing songs, believed to empower the plants, it provides Seminoles with a reference handbook of plants; it also offers medical professionals, herbalists, and the general public an understanding of the world of Seminole medicine.
An approach for constructing the S-box using the CML system

We propose an approach for constructing S-box by using the CML chaotic system. The chaotic sequences produced by the CML chaotic system are used to permute and diffuse the elements of the S-box randomly. The obtained S-box has a strong randomness property due to the high dimensional feature of the CML chaotic system. We analyze bijective property, nonlinearity, strict avalanche criterion, outputs bit independence criterion, input/output XOR distribution and linear approximation probability of the constructed S-box. The experimental results show that the proposed approach for constructing S-box is effective.
Speed and accuracy in learning: A combined Q-learning diffusion decision model analysis

Recent advances in cognitive modelling merged two classes of cognitive models: Sequential sampling models of decisionmaking, and reinforcement learning models of error-driven learning. Such integrated models provide theoretical accounts of the cognitive processes underlying decisions and learning simultaneously. Here, we test whether a classical decisionmaking phenomenon -the speed-accuracy trade-offcan be observed in an instrumental learning task, and whether an integrated reinforcement learning/sequential sampling model is able to capture this effect. The results show that the model indeed captured the speed-accuracy trade-off effect in empirical data, as well as changes in response times and accuracies due to learning over the course of the experiment. This study further illustrates the great promise of the integration of the reinforcement learning and sequential sampling frameworks for cognitive psychology and cognitive neuroscience.
A System for Diacritizing Four Varieties of Arabic

Short vowels, aka diacritics, are more often omitted when writing different varieties of Arabic including Modern Standard Arabic (MSA), Classical Arabic (CA), and Dialectal Arabic (DA). However, diacritics are required to properly pronounce words, which makes diacritic restoration (a.k.a. diacritization) essential for language learning and text-to-speech applications. In this paper, we present a system for diacritizing MSA, CA, and two varieties of DA, namely Moroccan and Tunisian. The system uses a character level sequence-to-sequence deep learning model that requires no feature engineering and beats all previous SOTA systems for all the Arabic varieties that we test on.
Generating Point Cloud from Measurements and Shapes Based on Convolutional Neural Network: An Application for Building 3D Human Model

It has been widely known that 3D shape models are comprehensively parameterized using point cloud and meshes. The point cloud particularly is much simpler to handle compared with meshes, and it also contains the shape information of a 3D model. In this paper, we would like to introduce our new method to generating the 3D point cloud from a set of crucial measurements and shapes of importance positions. In order to find the correspondence between shapes and measurements, we introduced a method of representing 3D data called slice structure. A Neural Networks-based hierarchical learning model is presented to be compatible with the data representation. Primary slices are generated by matching the measurements set before the whole point cloud tuned by Convolutional Neural Network. We conducted the experiment on a 3D human dataset which contains 1706 examples. Our results demonstrate the effectiveness of the proposed framework with the average error 7.72% and fine visualization. This study indicates that paying more attention to local features is worthwhile when dealing with 3D shapes.
A low-loss high-linearity SOI SP6T antenna switch using diode biasing method

This letter describes a single-pole six-throw (SP6T) antenna switch in a 180nm silicon-on-insulator (SOI) CMOS technology for receive diversity and LTE transmit/receive applications. Using a new diode biasing method, the conventional biasing resistor and supply voltage are removed at the body of the stacked-FET switch, a diode is used to connect the body and gate for body bias instead. The biasing diode turns off and on and functions as a high and small resistor for the on and off state. The proposed design helps to achieve low loss and high linearity. The measured insertion loss (IL) at 0.9 and 1.9GHz are roughly 0.29 and 0.46dB, respectively. The switch shows a second harmonic of -86 and -83dBc, and third harmonic power of -94 and -87dBc with a +26dBm input power at 0.9 and 1.9GHz, respectively.
SGXJail: Defeating Enclave Malware via Confinement

Trusted execution environments, such as Intel SGX, allow executing enclaves shielded from the rest of the system. This fosters new application scenarios not only in cloud settings but also for securing various types of end-user applications. However, with these technologies new threats emerged. Due to the strong isolation guarantees of SGX, enclaves can effectively hide malicious payload from antivirus software. Were these scenarios already outlined years ago, we are evidencing functional attacks in the recent past. Unfortunately, no reasonable defense against enclave malware has been proposed. In this work, we present the ﬁrst practical defense mechanism protecting against various types of enclave misbehavior. By studying known and future attack vectors we identiﬁed the root cause for the enclave malware threat as a too permissive host interface for SGX enclaves, leading to a dangerous asymmetry between enclaves and applications. To overcome this asymmetry, we design SGXJail, an enclave compartmentalization mechanism making use of ﬂexible memory access policies. SGXJail effectively defeats a wide range of enclave malware threats while at the same time being compatible with existing enclave infrastructure. Our proof-of-concept software implementation conﬁrms the efﬁciency of SGXJail on commodity systems. We furthermore present slight extensions to the SGX speciﬁcation, which allow for even more efﬁcient enclave compartmentalization by leveraging Intel memory protection keys. Apart from defeating enclave malware, SGX-Jail enables new use cases beyond the original SGX threat model. We envision SGXJail not only for site isolation in modern browsers, i.e. , conﬁning different browser tabs but also for third-party plugin or library management.
Development of Top-Up And Bottom –Up Techniques for Assessment of Power Line Communication Channel Model

Power Line Communication (PLC) is the transfer of data and voice signals from one communication system to another over the electric power delivery network. However, with the advent of technology, human dependency on electricity and communication has grown beyond leaps and bounds. The power transmission line channel has not been designed with wired channel requirements for broadband applications and appears as a harsh environment for the low-power high-frequency communication signals. This study therefore evaluate the performance of PLC on power grid by simulating a practical multipath power line communication channel model using top-down and bottom-up approach. The statistical multipath parameters such as path arrival time, magnitude and interval for each category were analyzed. This is done over the frequency range of 100-300 kHz. The result shows that at 100 kHz, data can be transmitted up to 350 meters without signal distortions while for 300 kHz only 50 meters can be covered. In addition, signal attenuation with a distance of 2 km is about 0.2 of the original signal at 300 kHz and less at higher frequencies. The results in the time and frequency domains indicate that data transmission in PLC environment needs signal to be amplified at higher powers. Keywords : Power Line Communication, Power Grid, Transmission Line, Multipath Parameters, Channel Modelling, Top-Down Approach, Bottom-Up Approach. DOI : 10.7176/JNSR/9-16-03 Publication date : August 31 st 2019
ECG SIGNAL ANALYSIS OF EARLY AND LATE RISERS: A POPULATION BASED CASE CONTROL STUDY

This paper investigates the effect of early rising on heart rhythm. We have analyzed the ECG signals of early (or Controls) and late (or Cases) risers. In the study we obtained ECG signals of two hundred healthy humans having age range between twenty and thirty-five years. The twenty features of ECG signals were analyzed in the experiment. The significant difference in the two groups was reported based on the two features of the ECG signals i.e. QRS and QTc. Cases were associated with the variations in QRS complex and QTc features of their ECG signals. The QRS complex abnormal values were 76% for cases and 31% for controls. Similarly, the QTc was also found abnormal with 75% for cases and 33% for controls. The accumulative abnormal values of both QRS and QTc were found 75% and 48% for late and early risers respectively. There is a relative high occurrence of heart abnormalities in cases than controls. The probability of QRS and QTc abnormality is more for Cases as compared to Controls.
Quantum ghost imaging for remote sensing

We propose an advanced quantum ghost imaging setup for remote sensing applications, which does not rely on preliminary information on the distances of objects and investigate the quantum benefits of this setup for remote sensing applications. The photon source of the setup will be suited for standoff detection with illumination of remote objects in the infrared, while retrieving the spatial information in the visible regime with matured silicon technology. The setup utilizes single photon avalanche detectors with integrated time to digital converters for detection of both photons to capture the full 3D information of an unknown scene and is suited for imaging over large distances, without the necessity of an optical delay line
Performance Comparison of High Order Moments Blind Channel Identification

In this paper, we compare different order of statistical moments to blindly estimate the propagation channel in an OFDM based wireless network. We first derive the theoretical expression of the channel estimation error and we compare it to simulation results in different scenarios. These simulation results show a good agreement with the theoretical expression. Furthermore, we show that blind channel identification algorithms, based on different moment's order, exhibit similar performance in terms of the Normalized Mean Square Error (NMSE) and in terms of the Bit Error Rate (BER). We conclude that the choice of the moment's order is uniquely based on the ambiguity solving stage in the algorithm. The proposed study shows that the choice of the 4 th moment is a trade-off between channel estimation performance and ambiguity solving complexity.
Identifying Users Based on Time-Frequency Characteristics

With the rapid development of information technology, whether it is with regard to the personalized recommendation of the business or network warning by the public security organ, the identification of online users is a very important research topic. The user’s web browsing behavior data contains potential behavioral characteristics, in this paper, we utilize the time-frequency analysis method, which extracts the behavior characteristics when users accessing the network, so as to obtain the user behavior pattern and calculate the similarity between the behavior patterns for achieving the purpose of user identification. This method is verified by the weblog, and the experiment results show that the method extracts user network behavior features based on time-frequency analysis to ensure the accuracy of user identification.
Jamaica's effort in improving universal access within fiscal constraints

Jamaica's primary health care system was a model for the Caribbean region in the 1990s. Because of it, Jamaicans enjoy relatively better health status than people in other countries of similar income level in the Caribbean region. However, Jamaica's health system is being severely challenged by persistent and reemerging infectious diseases and by the rapid increase in noncommunicable diseases (NCDs) and injuries. At the same time, the country has suffered from low economic growth and carries a high debt burden, which leaves limited fiscal space for improving health care. The Government of Jamaica has been trying to sustain the gain in health outcomes and improve access to health care for its population in an environment of constrained resources during the last decade. With the establishment of the Jamaica National Health Fund (NHF) in 2003 and the abolition of user fees at public facilities in 2008, the Government of Jamaica has taken steps toward achieving universal coverage. This study reviews the achievements and challenges in expanding universal access in Jamaica and assesses the impact of the NHF's drug-subsidy programs and the abolition of user fees on universal access, and discusses policy options for achieving universal coverage.
iPad App for Daily Parkinson Diary (P1.193)

Objective: To develop a patient-driven mobile app that optimizes Parkinson’s disease (PD) patient-reported outcome collection. To explore usability of the method in a PD population. Background: Clinical data collection in PD patients is typically limited to twice or thrice yearly visits with the neurologist. This creates potential for recollection bias and difficulty assessing disease severity and response to medication. Daily tracking of PD symptoms would be very valuable in a practice and research setting. Portable technology platforms can be used for this purpose. Design/Methods: Initially, PD patient-neurologist appointments were observed to ascertain what health topics dominated their discussion, how often specific health events were included in the neurological history form filled out prior to the patients appointment, how PD patients described symptom changes, and if PD patients kept a detailed account of their health events. An interactive prototype of an iPad app that would help PD patients keep detailed records of his/her daily health condition was created and tested by PD patients, caregivers, and neurologists. Iterative design changes were made based on their feedback. Results: An iPad app was designed and created with PD patients’ physical and cognitive challenges in mind. The app features a cognitively simple user interface that does not require instructions, an analog scale with graphical presentation for documenting slowness, tremor, gait/balance, dyskinesia, mood, and additional video input that can provide neurologists with objective accounts of PD patients’ health condition. 24 patients were interviewed and participated in the initial pilot. All were able to utilize the device and provide accurate answers. Conclusions: An iPad app-based PD diary is acceptable and usable. A 6-month study of PD patients’ use of this app for tracking their daily symptoms is ongoing. Once the study is completed, several validity measures will be assessed by independent interviews with patients and providers. Disclosure: Dr. Lungu has nothing to disclose. Dr. Kim has nothing to disclose. Dr. Hallett has received personal compensation for activities with Neurotoxin Institute, Cambridge University Press, Oxford University Press, Wiley-Blackwell, and Springer. Dr. Lukasiewicz has nothing to disclose. Dr. Harrington has nothing to disclose. Dr. Altemus has nothing to disclose. Dr. Baldwin has nothing to disclose.
Rapid, Low-Energy Interferer Detection Using Compressive-Sampling RF-to-Information Converters

Modern military radios for SIGINT or communication applications often need to operate in an interferer-rich environment. They typically need to quickly find interferers or jammers, both spectrally and spatially, to take appropriate countermeasures. We show how compressive sampling (CS) can enable unique RF capabilities and performance. The Direct-RF-to-Information Converter (DRF2IC) rapidly detects interferers or signals of interest (SOI) in the spectral domain and the Direct-Space-to-Information Converter (DSIC) rapidly detects their direction of arrival in the spatial domain. Thanks to CS, the SOIs are found quickly while only requiring low energy. We demonstrate RF ICs of these converters implemented as overlays on high performance receivers and beamformers. Their speed, low energy, and unified architectures makes them excellent solutions in SWaP-constrained platforms like man-portable, satellite and unmanned aerial system (UAS) applications.
Resource Allocation and Power Control in Cooperative Small Cell Networks With Backhaul Constraint

A joint resource allocation (RA), user association (UA), and power control (PC) problem is addressed for proportional fairness (PF) maximization in cooperative multiuser downlink small cell networks with limited backhaul capacity, based on orthogonal frequency division multiplexing. Previous studies have relaxed the per-resource-block (RB) UA and RA problem to a continuous optimization problem based on long-term signal-to-noise ratio, because the original problem is known as a combinatorial NP-hard problem. We tackle the original per-RB UA and RA problem to obtain a near-optimal solution with feasible complexity. Motivated by the fact that the condition for obtaining the near-global solution with the dual problem approach is rarely satisfied for increasing number of users, we derive explicit first order optimality conditions to obtain a 2-distance ring solution of the primal UA and RA problem, and propose a sequential optimization method. In addition, we propose a PC algorithm based on the first order KKT optimality conditions, in which transmission power of each RB is iteratively updated. The overall proposed scheme can be implemented with feasible complexity even with a large variable dimension. Numerical results show that the proposed scheme achieves the PF close to its outer-bound. Though there have been extensive studies on UA, RA, and PC in multicell networks, the proposed scheme is first to closely achieve the optimal PF performance in frequency-selective fading channels with feasible computational complexity.
VIEWPOINT MANIPULATIONS FOR 3D VISUALIZATIONS OF SMART BUILDINGS

This thesis covers the design and implementation of a new single-input viewpoint manipulation technique aimed for a speciﬁc use case. The design of the technique is made based on previous literature. The objective of the research is to assess whether a single-input viewpoint manipulation technique can be as eﬃcient as a multi-input viewpoint manipulation technique when used for observing a three dimensional (3D) model of a smart building. After checking the existing literature about basics of viewpoint manipulation, it was decided to design a single-input viewpoint manipulation technique that can be used on a wide range of hardware including touch screen devices not capable of multi-touch input and personal computers with a regular mouse. A 3D visualization of a nursing home was implemented to be viewed with the new technique. The nursing home in question is a smart house with sensors deployed in it, and sensor data is visualized in the 3D model. Aside from the new single-touch technique, a commonly used multi-touch technique was also implemented in order to compare the single-touch technique against it. Participants were recruited and user tests were made to ﬁnd issues with the system. The yielded results indicate some clear points in the new technique that can be improved for future research.
ACADEMIC DIFFICULTIES FOR UNIVERSITY STUDENTS IN THE FACULTY OF AGRICULTURAL , FOOD AND ENVIRONMENTAL SCIENCES, DEBRECEN UNIVERSITY

Our previous study discussed the first results of a survey on the academic competencies of L2 medical students (DEOEC, University of Debrecen) from non-Hungarian countries, who pursued their undergraduate medical diploma courses in English. Our present study envisages exploring the academic competencies of the first year students of the Faculty of Agricultural, Food and Environmental Sciences, Debrecen University. Our goal is to establish a network of group-leaders (helpers) from among lecturers who might provide useful support for first year students in relation to the above mentioned skills and competencies to make our students more successful during their academic years and to provide them with marketable degrees.
The Role of Individuals’ Need for Online Social Interactions and Interpersonal Incompetence in Digital Game Addiction

ABSTRACT Since online digital game addiction became one of the serious social computing issues related to public health, there has been an unprecedented need to explore and understand online digital game addiction from a psychosocial perspective. Extant studies have empirically tested the effects of as well as the relationship among prominent psychological distresses such as depression, loneliness and aggression on game addiction. Likewise, previous studies have also empirically established that social interaction may take a different form and alter the social exchanges in ways that may be particularly attractive to those who are lonely. This way, online social interaction within the interfaces of digital games such as MMORPGs can become a substitute for real-life social interaction because of the online anonymity and lack of physical presence which allow users to control social interaction. However, a few studies have explored the relationships among individuals’ need for online social interaction, interpersonal incompetence and self-regulation (control) and their effects on game addiction. In addition, the mediating role of individuals’ need for online social interaction in online digital game addiction has neither been proposed nor empirically tested. The main purpose of this study is to examine digital game addiction from the perspectives of individuals’ need for online social interaction, interpersonal incompetence, self-regulation and loneliness. We believe that the findings of this study will offer new insights to policymakers in dealing with the issues of digital game addiction. More specifically, the purpose of this study is to understand the mediation effect of individuals’ need for online social interaction on game addiction.