Miracle-dz/UniFAR-FTUs huggingface dataset:
Heart Disease Prognosis Using Machine Learning Classification Techniques

Heart Disease is one of the fatal causes of worldwide death in also third world countries like Bangladesh. Though heart disease prediction with a satisfactory accuracy level is a very demanding and challenging topic, it is achievable using advanced machine learning (ML) techniques. Manufacturing a proper ML system can not only predict cardiovascular disease with high accuracy but also can reduce human intervention, the requirement of extra medical tests. Quick prediction can deduct the death rate and severity of the disease. This paper describes our proposed methodology of predicting heart disease that targets a goal of finding important features by applying ML algorithms resulting in improving the accuracy of the prediction. Instead of collecting the dataset from the online repository, we collected data from the Sylhet region of Bangladesh by physically going to door-to-door hospitals and healthcare industries to make an appropriate questionnaire and to produce the most valuable dataset related to heart disease prediction. Our dataset consists of 564 instances and 18 attributes. We trained our model using classification algorithms like Decision Tree, Logistic Regression, K-Nearest Neighbors (KNN), Naive Bayes, Support Vector Machine (SVM), etc. Though accuracy for different algorithms varies for a different number of instances in the dataset, SVM yielded the best performance with an accuracy level of 91% for the threshold instances of the dataset in our proposed system.
Extremely Low-Power Fifth-Order Low-Pass Butterworth Filter

A fifth-order Butterworth low-pass filter using multiple-input operational transconductance amplifiers (OTAs) is proposed in this paper. It is expressed that the number of OTAs that used for realizing fifth-order low-pass filter can be reduced using multiple-input OTA and results to decrease the power consumption and the active area. N-input OTA can be obtained using multiple-input bulk-driven quasi-floating gate technique. Subthreshold technique is used to achieve extremely low power consumption which can be applied to biomedical systems. The proposed topology is simulated using 0.18 $\mu \text{m}$ standard CMOS process. Simulation results show that the proposed filter has a bandwidth located within 250 Hz, a power consumption of 41 nW and a dynamic range of 61 dB.
Solar irradiance prediction for voltage variance analysis in the GCPV system using LSSVM

The large-scale deployment of green energy technology has led to the explosive development of photovoltaic power generation. Prediction of accurate solar irradiance is essential to ensure system efficiency and performance. The Least Square Support Vector Machine (LSSVM) model is proposed for predicting solar irradiance of grid-connected photovoltaic (GCPV) output power. The impact of the increase in photovoltaic power on the power flow of the grid voltage fluctuation is simulated and analyzed using MATPOWER. The result shows that LSSVM produces promising results for the short-term prediction of solar irradiance and photovoltaic output.
Automated unsupervised identification of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images

Identification of cone photoreceptor cells (CPCs) is essential for the diagnosis and treatment of various retinal disorders. In the present work, a new automated unsupervised learning-based method is proposed for the identification of CPCs in adaptive optics scanning laser ophthalmoscope images. This method consists of the following steps: image denoising, CPC number estimation, bias field correction, unsupervised CPC identification, and merging close CPC identification data. By comparing our results with those obtained manually, it was found that the proposed method showed high effectiveness, with the precision, recall and F1 score values of 92.9%, 84.4% and 88.4%, respectively. Furthermore, healthy retinal AO-SLO images with the difference in CPC densities and pathological (diabetic retinopathy) AO-SLO images are processed by our method. The results demonstrated that our method exhibited a good accuracy for the identification of CPCs in diabetic retinopathy and healthy retinas.
A Cloud-Based Application for Smart Irrigation Management System

Agriculture is one of the most important sectors in the Palestinian economy and it is the main consumer of freshwater. Several factors have a major impact on agricultural activities including water availability, soil type, climate condition, fertilizers, and diseases. In this paper, we provide a cloud-based software application that is combined with the Internet of Things (IoT) devices that can automate the irrigation schedule based on information obtained from agricultural experts and environmental data collected from the field using sensors technology. The application can easily be extended to automate fertilization as well as provide recommendations for weed and pest control.
Knowledge Graph construction of Thangka icon characters based on Neo4j

Thangka is a kind of Tibetan painting art, Thangka knowledge is too fragmentary, lacks integrated information generalization, and users have too few ways to understand it. In order to popularize users’ knowledge of Thangka and better manage the retrieval of thangka knowledge service mode, this paper proposes the construction of the knowledge graph of Thangka graph icon characters based on Neo4j. Through constructing the Schema layer of Thangka knowledge in a top-down way, designing the data layer of Thangka knowledge graph in a bottom-up way, and using Neo4j graph database to store the data of knowledge graph. The construction of the knowledge graph of thangka icon characters can serve as the foundation for the future information retrieval, visual display and the application of knowledge questions.
Eight Bit Quantum Fourier Transform Using the FDTD Method

A way of using the Finite Difference Time Domain method is described to simulate the Quantum Fourier Transform, which is an essential component of Shor’s factoring algorithm. This simulation is based on the direct implementation of the time-dependent Schrödinger equation in one dimension. Each bit is simulated as an electron in a harmonic oscillator. The behavior of each quantum gate is simulated by applying a magnetic field in specific orientations for set amounts of time based on the amount of time the electron requires to precess. By using a combination of these quantum gates, it is possible to simulate the behavior of the full Quantum Fourier Transform. An eight bit Quantum Fourier Transform was simulated for this work, but it could easily be expanded to reach higher numbers of bits. Results were compared with computational results and shown to match. Simulations were done in Python without requiring significant computational power.
Research on Supply Chain Risk of Platform-based Fresh Food E-commerce

The long-term accumulated brand notability of fresh food e-commerce platforms has brought the advantages of fresh product and customer resources to the platform-based fresh e-commerce supply chain, effectively solving the problem of unsmooth connection between production and sales in China's traditional fresh food industry. However, the unique freshness activity, and perishability of fresh products as well as the complex dynamics of supply chain make the platform-based fresh food e-commerce supply chain face uncertain risks and restrict the operation of the supply chain. On the basis of consulting related literature, this paper summarizes the supply chain risks as quality risk, logistics risk, information risk, cooperation risk and after-sales risk, uses analytic hierarchy process to carry out risk assessment, and finally puts forward corresponding control countermeasures to effectively prevent and avoid the above risks.
Privacy-Preserving Compressed Sensing for Image Simultaneous Compression-Encryption Applications

In recent years, using compressed sensing (CS) as a cryptosystem has drawn more and more attention since this cryptosystem can perform compression and encryption simultaneously. However, this cryptosystem is vulnerable to known-plaintext attack (KPA) under multi-time-sampling (MTS) scenario due to the linearity of its encoding process. In this paper, a privacy-preserving CS scheme for image compression-encryption applications is proposed, which embeds a non-linear operation called noise injected negative-positive transformation (NINPT) in the CS encoding process with the purpose of withstanding KPA. The encoding procedures of the proposed scheme include three steps. First, the original image is encrypted by using NINPT operation. Second, the intermediate ciphertext is re-encrypted and compressed by using CS simultaneously. Third, the final compressed ciphertext is quantized into bits via scalar quantization (SQ). Since the introduction of NINPT operation in the CS encoding process breaks the linearity of the CS sampling process, the proposed scheme can withstand KPA under MTS scenario. For image signal reconstruction, a projected Landweber with embedding decryption (PL-ED) algorithm is proposed. Simulation results demonstrate that the proposed scheme can withstand KPA under MTS scenario at the cost of slightly sacrificing the compression performance.
Teleoperation Method of Space Manipulator Considering both Safety and Efficiency

It is difficult to realize the security and operability of the space manipulator master-slave teleoperation system simultaneously. A motion mapping algorithm for master manipulator and slave manipulator based on piecewise curve and contact warning strategy based on distance are proposed. Firstly, based on the terminal velocity mapping, the distance coefficient is introduced into the velocity mapping matrix of the motion mapping algorithm to accomplish the dynamic adjustment of the teleoperation system motion mapping. Then, based on Voxmap-PointShell algorithm, a fast distance calculation algorithm is designed. The force warning when the end of the manipulator approaches the environment and the contact force prediction when the end of the manipulator contacts the environment are completed. The safety and operability of space manipulator master-slave teleoperation system are both realized.
Performance Analysis of CNTFET based 6T SRAM Cell with Tube and Chiral Variation under 16 and 32 nm Technologies

This paper deals with the performance analysis of Carbon Nanotube Field Effect Transistor (CNTFET) based 6TSRAM under different technologies. The efficiency of this circuit is observed by changing the number of tubes and the chiral vector of the device. Parameters like Average Power Consumption, Average Power Delay Product (PDP) and Average Delay were taken to consideration for observing the efficiency of the CNTFET based 6T SRAM. The results obtained show that the Average Power Consumption increases to almost 3 times when the value of chiral vector reaches maximum and 5 times for the maximum number of tubes in this observation. In case of average delay, the value becomes almost half when the chiral vector reaches maximum but there is a negligible change due to change in number of tubes. A similar change can be observed even when the channel length is varied.
The anti-inflammatory activity of Azilsartan in animal models of experimen- tally-induced chronic and granulomatous inflammations

Received on: 16.07. 2018 Revised on: 03.09. 2018 Accepted on: 06.09. 2018 It is well documented that blockade of angiotensin II type 1 receptor may interfere with the progression of the inflammatory processes. The present study aims to evaluate the dose-response relationship of the anti-inflammatory activity of azilsartan in rat models of chronic and granulomatous inflammation. The study includes two parts: First part: 42 rats were allocated into 7 groups, each containing six rats, to evaluate the anti-inflammatory activity of different doses of azilsartan in the rat model of formalin-induced chronic inflammation. Second part: 42 rats were allocated as in 1st group to evaluate the anti-inflammatory activity of azilsartan in the rat model of cotton pelletinduced granuloma. Azilsartan in a dose-dependent pattern (0.125, 0.25, 0.5, 1.0 and 2.0 mg/kg), significantly attenuated inflammation in both rat models utilized in the study with maximum effect achieved with 1.0 mg/kg, which is comparable to that reported for dexamethasone and relative linearity within the lowest dose range. In conclusion, azilsartan decreased formalin-induced chronic inflammation and cotton-pellet induced granuloma in rats in a dosedependent pattern. Therefore, it may be considered as a potential candidate for treating chronic inflammatory conditions in human.
Prevalence of Gastroesophageal Reflux Disease Among Diabetes Mellitus Patients in Ha’il City, Saudi Arabia

Objective: Gastroesophageal reflux disease is a chronic and relapsing condition which is a prolonged reflux of hydrochloric acid, pepsin, and bile salt into the esophagus. The purpose of the study is to determine the prevalence of gastroesophageal reflux disease in diabetes mellitus patients among Ha’il population and elicit a relation. Methods: This is a cross-sectional study that was conducted via a pre-validated questionnaire and was distributed among different social media with a sample size of 394 diabetic patients. Results: The prevalence of diabetes mellitus was 24.6%. Most participants (98.9%) had a 50% or greater chance of developing GERD. Only type of management of diabetes was found to be a significant factor in developing GERD (P value = 0.001). Conclusion: The prevalence of GERD symptoms in diabetic patients is not uncommon, 98.9% of the participants had a 50% likelihood of developing GERD. The higher the duration of DM, the lower the risk of exhibiting symptoms of GERD.
A Multilingual Modeling Method for Span-Extraction Reading Comprehension

Span-extraction reading comprehension models have made tremendous advances enabled by the availability of large-scale, high-quality training datasets. Despite such rapid progress and widespread application, extractive reading comprehension datasets in languages other than English remain scarce, and creating such a sufficient amount of training data for each language is costly and even impossible. An alternative to creating large-scale high-quality monolingual span-extraction training datasets is to develop multilingual modeling approaches and systems which can transfer to the target language without requiring training data in that language. In this paper, in order to solve the scarce availability of extractive reading comprehension training data in the target language, we propose a multilingual extractive reading comprehension approach called XLRC by simultaneously modeling the existing extractive reading comprehension training data in a multilingual environment using self-adaptive attention and multilingual attention. Specifically, we firstly construct multilingual parallel corpora by translating the existing extractive reading comprehension datasets (i.e., CMRC 2018) from the target language (i.e., Chinese) into different language families (i.e., English). Secondly, to enhance the final target representation, we adopt self-adaptive attention (SAA) to combine self-attention and inter-attention to extract the semantic relations from each pair of the target and source languages. Furthermore, we propose multilingual attention (MLA) to learn the rich knowledge from various language families. Experimental results show that our model outperforms the state-of-the-art baseline (i.e., RoBERTa_Large) on the CMRC 2018 task, which demonstrate the effectiveness of our proposed multi-lingual modeling approach and show the potentials in multilingual NLP tasks.
Optimal crop planning for conjunctive use of irrigation water in Punjab: A path towards sustainable development

In the present study, an attempt has been made to develop optimum crop planning strategies to increase the productivity with minimum input cost, maximising net returns and significant savings of groundwater under the constraints of available resources like irrigation water, land and fertilizers etc. for Punjab state by using linear programming technique. The optimum crop model with existing water use conditions resulted that there will be net gain of Rs. 680 crores, Rs. 650 crores and Rs 17 crores at market prices, economic prices and natural resource valuation prices respectively. The results revealed that with 10 per cent reduction in current irrigation wateruse, the profit would decrease by 3.52 per cent, 3.53 per cent and 3.60 per cent respectively at the respective prices. The optimum crop model exhibited decline in gross cropped area by about 3 per cent each at all the prices and net loss was estimated of Rs. 989 crores, Rs. 740 crores and Rs. 1302 crores at market, economic and natural resource prices respectively. Whereas by using 80 per cent of current irrigation water usage in Punjab state there will be decrease in gross cropped area by 13.95 per cent, 12.98 per cent and 12.97 per cent at market prices, economic prices and NRV prices respectivelycausing net loss of Rs. 4047 crores, Rs. 3171 crores and Rs. 3682 crores at the respective prices. Thus, the study brought out that there is trade-off between water saving and profitability from the crops i.e. if water is to be saved, profits of the farmers would decline. Further, it was revealed that the efficiency of irrigation water could be increased by using water saving technologies such as laser land leveller and tensiometer etc.
The perception-prodution link and linguistic theory ; El vínculo entre la producción y la percepción y la teoría lingüística

Recent trends in infant (and adult) speech perception studies, especially in the psychological literature where much of the speech perception work is being and has been done, shows a growing focus on more integrated perception-production-sensorimotor (PPS) bases for perception (Werker & Gervain 2013). We look here at whether the results of such studies are significant for theoretical linguistics – specifically for the fundamental question of how the linguistic system is acquired. We examine a selection of recent experimental results, using Bruderer, Danielson, Kandhadai & Werker (2015) as the focal point.
Optimization of Carbopol 941 And HPMC on the Gel of the Bark of Strychnos lucida R.B Ethanol Extract as Hand Sanitizer

Some research resulted that show Strychnos lucida R.Br contains compound of tannin, flavonoids, phenols, alkaloids and saponins that can be used as antibacterial. Seeing the compounds contained, one csn make an antiseptic gel. An important components in the gel preparation is gelling agent. Gelling agent is widely used because it has high stability and increases the effectiveness of the use of gel as an antibacterial. This study aims to determine the optimum composition of Carbopol 941 and HPMC in the extract of Strychnos lucida R.Br stem using the Simplex Lattice Design method. The gel was made in three formulas with a comparison of Carbopol 941 and HPMC, 100%: 0%; 50%: 50%; 0%: 100%. Next, these were tested physicochemical properties including spreading, pH, and stickiness tests. The validity of the optimization method has done before by comparing the test result and the prediction in the optimum gel formula. The results showed that the optimum composition was obtained of Carbopol 941: HPMC by 50%: 50%. Verification results compared to the prediction results it did not show different for all tests, spreading, pH, stickiness tests and antibacterial. The optimum formula for the ethanol extract of Strychnos lucida R.Br stems have the potential for strong antibacterial activity with a inhibitory zone value of 13.55 mm.
Multimodal Discourse Analysis for teaching English as a Second Language

New technological developments have boosted the use of different modes or semiotic resources; social changes and developments, on the other hand, have changed the process of meaning making because discourse shapes and is shaped by social practices. Semiotic resources are used in communication (language, sound, gestures, facial expressions . etc) and this has impact and reflections on the methods of teaching. Literacy is not only about reading and writing, it rather means the ability to communicate through multiple modes. Hence, it is important to embed multimodality (the study of using multiple modes) in educational settings.
Reproductive ecology and territorial behavior of Boana goiana (Anura: Hylidae), a gladiator frog from the Brazilian Cerrado

Anuran males and females adopt different reproductive and behavioral strategies in different contexts. We investigated the reproductive ecology and territorial behavior of the treefrog Boana goiana (B. Lutz, 1968) from the Brazilian Cerrado. We hypothesized that competitor density/proximity would increase the behavioral responses of B. goiana males, and that mating would be assortative. We also tested if the number of eggs correlates with female size and if there is a trade-off between clutch size and egg size. We conducted two territoriality experiments to test the effects of male size, competitor proximity and competitor density. Larger males called more in the presence of a second male. In the second experiment, the largest males emitted more calls and the distance to the nearest male increased as resident males called more. In both experiments, the number of calls was influenced by either male size or spacing between males. Some males behaved as satellites, probably to avoid fights. Our analyses indicate that females choose males with similar sizes to their own, corroborating our hypothesis of size-assortative mating. We found no relationships between female size and clutch size/volume, and between egg size and number of eggs per clutch. We also report multiple spawning for this species. The low incidence of physical combats and the spacing pattern indicate that this species relies almost solely on calls to resolve contests, which could be explained by low motivation, or simply because males avoid combats to decrease injury risks. Thus, acoustic or even multimodal communication seems crucial for social interactions of B. goiana.
SCHOOL OF MATERIALS AND MINERAL RESOURCES ENGINEERING UNIVERSITI SAINS MALAYSIA FABRICATION AND CHARACTERIZATION OF POLYMER MICROFIBER BY USING COTTON CANDY MACHINE By NUR ALIA AFFIZA BINTI ABDULLAH

In this study, it was aimed to investigate the effect of collector dimension and Polylactic Acid/Polyethylene Glycol (PLA/PEG) blend on the mechanical and morphology properties of polymer microfiber. Polylactic acid (PLA) were plasticized with Polyethylene glycol (PEG) at various concentration of PEG at 0, 10, 20, 30 and 40 wt% prepared by using cotton candy machine with three different collector design to produce microfiber which design A with 5 cm width, design B with 4 cm width and design C with 1.5 cm diameter. Fourier transform infrared (FTIR) were conducted on each types of blend system to determine their chemical structure. Thermal properties of the PLA/PEG microfiber also have been investigated by using Differential Scanning Calorimetry (DSC) to determine the melting temperature (Tm), cold crystallization temperature (Tcc) and glass transition temperature (Tg). Mechanical properties was measured using Texture Analyser machine while density were done using density balance at room temperature and thickness also were taken by using thickness gauge for all samples. Results showed that, microfiber collected by design C has a higher tensile strength but lower elongation at break. This was due to the close packed and increased in thickness. Microfiber with higher composition of PEG have a lower mechanical properties for all collector design due to incorporation of PEG to the blend. For SEM test, it can be observed that the pore sizes and fiber diameter decreases from collector design A to C. This was due to the distribution space for the microfiber reduced. The PLA/PEG blend reduced the pores sizes and fiber diameter for all collector design.