Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Plant Leaves Using New Compact Convolutional Neural Network Models

Precision crop safety relies on automated systems for detecting and classifying plants. This work proposes the detection and classification of nine species of plants of the PlantVillage dataset using the proposed developed compact convolutional neural networks and AlexNet with transfer learning. The models are trained using plant leaf data with different data augmentations. The data augmentation shows a significant improvement in classification accuracy. The proposed models are also used for the classification of 32 classes of the Flavia dataset. The proposed developed N1 model has a classification accuracy of 99.45%, N2 model has a classification accuracy of 99.65%, N3 model has a classification accuracy of 99.55%, and AlexNet has a classification accuracy of 99.73% for the PlantVillage dataset. In comparison to AlexNet, the proposed models are compact and need less training time. The proposed N1 model takes 34.58%, the proposed N2 model takes 18.25%, and the N3 model takes 20.23% less training time than AlexNet. The N1 model and N3 models are size 14.8 MB making it 92.67% compact, and the N2 model is 29.7 MB which makes it 85.29% compact as compared to AlexNet. The proposed models are giving good accuracy in classifying plant leaf, as well as diseases in tomato plant leaves.
Tourism Information Systems with Grouping using Google Maps

During travelling, travelers usually have some sort of travels preferences such as its purposes, types or chosen categories and its destination/attractions. To ensure fully indulge travel, tourist usually needed instruction or guidance and travel map during those trips. A map is used to show the precise location of each destination. Some travelers travels without knowing the exact location of the places such as museums, restaurants, park or shopping district that yet hasn’t been known to them before, therefore in need of a tourism map. As a fact, tourism maps are one of the most common groups of cartographic documents since it has lots of diversity in contents, subject and publication title due to the increasing popularity and diverse forms of tourism activities. In this research, coordinates values were taken and saved in a database using dd  mm’ss” (degree, minutes, seconds) format whereas Google maps reads value in the format of latitude and longitude which led the system to implement automatic conversions in order to be functional with Google Maps. PHP programming, JavaScript, MySQL database with other assisting software suitable in extracting and converting coordinates value to latitude, longitudes value was used in making this program. This system really helps travelers knowing the exact location and assist in determining the chosen destination.
Hybrid Platform Driven by Low DOF Mechanisms

A hybrid platform combining a parallel manipulator and a planar mechanism is proposed to execute the task of 3D body guidance. The passive parallel manipulator includes a moving platform and three legs with spherical joints at both ends. A planar mechanism is the driving unit and equipped with only one or two actuators. The joint between the moving platform and planar mechanism is also spherical. Its location must satisfy that all corresponding positions at different poses are on a plane. Depending on the number of poses assigned, the joint can be selected arbitrarily or from a surface, several curves, and a few points. Similarly, the character of the point for installing each leg is the corresponding positions are on a sphere. The derivation of relevant equations for these surfaces, curves, and points are presented. The moving platform can move up to six 3D poses assigned in sequence. Numerical examples with simulation results are given to illustrate the design process and performance of this hybrid platform. Keywords: hybrid platform, 3D body guidance, poses, parallel manipulator
Development of Study Aids and Project Activity Procedures for STEM Educatio

It is important to develop a student’s awareness to enable them to understand and apply the basics of sciences, mathematics, and engineering. In this study, we aim to implement STEM (Science, Technology, Engineering, and Mathematics) education by enabling students to gain awareness on their own. We propose study aids and procedures for a project activity using study aids for STEM education. To enable students to gain awareness, teachers should provide a study environment that empowers students to develop their own solutions and plans and to actively develop and test their models. The project-based learning (PBL) system provides an appropriate study environment. Based on this viewpoint, we developed study aids using LEGO MINDSTORMS Set and Simple & Powered Machines Set as materials and procedures for a project activity using the study aids for PBL education. We also give examples of project activities implemented in our education system for students in various fields and we report the responses of students who participated in these project activities.
Wideband Low-Profile Dual-Polarized Antenna Based on a Gain-Enhanced EBG Reflector

This letter proposed a wideband dual-polarized antenna based on a gain-enhanced electromagnetic bandgap (EBG) reflector. The proposed reflector is studied with a purpose of mitigating the problem of deformed radiation patterns for a mushroom-like EBG reflector backed wideband crossed-dipole antenna, which is caused by undesirable surface current distribution on the patches of the EBG reflector. Introducing the gain-enhanced EBG reflector raises the average broadside gain of the antenna from 4.27 to 8.03 dBi. The antenna is designed to have a working bandwidth of 42.89% (3.04–4.70 GHz) for both ports, with a profile height of 6.26 mm.
Practical Considerations On The Use Of Adaptive Beamformers For Sparse Arrays With Positional Uncertainty

Summary This paper presents the results of a study of the impacts of positional uncertainty in the array gain performance of adaptive beamforming algorithms applied to a sparse planar array. The resulting array gain degradations were computed for a range of signal-to-noise ratios and for a range of linear (pattern) and quadratic (white noise gain) constraints applied to the adaptive beamformer. The results indicate that the noise constraint is the one constraint with the largest impact on the sensitivity of adaptive beamformers to positional errors. Nonetheless, the use of multiple linear constraints can add an additional robustness that is significant in some cases. The use of a large fraction of the degrees of freedom available to the beamformer to impose linear constraints does not reduce the ability to adapt to a number (detertnined by the remaining degrees of freedom) of discrete interferers. It should also be noted that the use of linear constraints that differ significantly from the conventional beamformer's pattern can often result in large performance degradations not found when the constraints are chosen to follow the conventional beamformer's pattern. Finally, two interesting scaling relationships between the perfortnance at different frequencies and different interference powers were noted in our results.
Is It Time to Resurrect the Harvard Water Program

In 1955, a group of professors at Harvard University began a program to investigate ways to improve the planning and design of multiunit, multipurpose water resource systems. In part, the program responded to the lack of adequate guidance at the federal level for the design of water systems. Bureau of the Budget Circular A-47, issued in late 1952, required that net benefits be maximized, but offered little direction on picking the right combination of uses to achieve that end. The professors realized that the Harvard Graduate School of Public Administration, which offered training to civil servants, provided just the place for a water resources seminar to address the problem. The program would mix practically oriented government water planners and more theoretical academic talent. The Harvard academicians believed that techniques could be devised to allow planners to take into account far more alternatives than were usually considered with available procedures. The identification of more alternatives would, in turn, help maximize benefits. In such a system, any change in one of the variables would cause the net benefits to decline ~Maass and Hufschmidt 1959, pp. 99–100; Hufschmidt 1962! The program integrated economic theory and engineering practice in a democratic political arena. It necessarily embraced a strong interdisciplinary approach and operations research techniques. Professors came from engineering ~Gordon Fair, Harold Thomas, Jr.! , economics ~Robert Dorfman, Otto Eckstein, John R. Meyer! , and government and public administration ~Arthur Maass and Maynard Hufschmidt, a research associate! Maass chaired the program. Economics student Stephen A. Marglin, who was an undergraduate when Maass first recruited him, and engineering student Myron B. Fiering later also made important contributions. The Bureau of Reclamation, Army Corps of Engineers, Public Health Service, Soil Conservation Service, Geological Survey, and the California Department of Water Resources provided students and later funding for the program. Gordon Fair managed to acquire $150,000 in ‘‘seed’’ money from the Rockefeller Foundation, a substantial sum for that time ~Maass et al. 1962, pp. 10– 13; Hufschmidt 1962, 1967; Burden 1955; S. Marglin, personal interview, December 11, 2001; Maass, telephone interview, October 1, 2001! A complete list of participants in the program appears on pp. 12-13 of Maass et al. 1962!
Limits to the dynamic range of low-power continuous-time integrators

The power consumption of active filters limits the achievable dynamic range. In this paper, we start by considering ideal electronic building blocks, and we derive the fundamental limits to the dynamic range of different topologies of continuous-time integrators, for a given power consumption. Then, by using simplified nonideal circuit models, we present design guidelines for the optimization of the dynamic range to power consumption ratio of the integrators. We, thus, obtain practical limits to the dynamic range, as functions of the transition frequency of the transistors. We demonstrate the possibility of approaching these limits by designing a practical CMOS circuit: an 8 MHz second-order bandpass filter with Miller integrators. The performance of the filter was evaluated by HSPICE simulations, using full device models; the resulting dynamic range to power consumption ratio is close to the theoretical limits.
Behavioral Adaptation, Safety, and Intelligent Transportation Systems

It is intrinsic to human nature to modify behavior to suit new conditions. How drivers are likely to change the way they drive if their vehicles are equipped with intelligent transportation system (ITS) devices is considered. It is clear from the antilock braking system experience that improvements in safety cannot be predicted on the basis of proof-of-concept studies alone, in which one simply looks at changes in performance of the task being aided, whether that is braking, navigation, or detection of hazards. One also must look at changes in other aspects of the driving task and at the type of driving being done to determine the likely effect on safety. In particular, one should assume that there may be trade-offs of mobility for safety, that is, more driving in more difficult conditions and at higher speeds leading to more crashes. Further, one should expect drivers to attempt to increase productivity while driving, given reduced driving task demand. The prolific use of cellular phones is evidence of this behavior. Research is needed on driver mental models of ITS devices, to ensure that drivers understand how they function. The best design from a mechanistic point of view may not be the most effective for drivers.
A Novel Grey-RSS Navigation System Design for Mobile Robots

The active magnetic bearing (AMB) offers several advantages such as having no friction, high rotational speed, less energy loss, and long life span. In rotation application, however, it must be connected to a motor which may degrade its performance. A bearingless motor is the combination of the active magnetic bearing and a motor. It saves software and hardware facilities, resulting in lower costs. In this paper, a permanent-magnet type bearingless motor is proposed based on a three-pole AMB. The translational magnetic field (generating the bearing forces) and the rotational magnetic field (generating the motor torque) are analyzed to establish the mathematical dynamic model of the overall system. Based on the dynamic model, a two-stage controller that sequentially levitates the rotor and controls the motor speed is designed. Numerical simulations are performed to verify the analysis.
A three-dimensional stochastic wire-length distribution for variable separation of strata

A complete wire-length distribution for future three-dimensional, homogeneous gigascale integrated (GSI) architectures with variable vertical separation of strata is derived. Because stratal pitch was not found to impact the wire-length distribution significantly, bonded three-dimensional implementations which are technologically feasible can be used to obtain large increases in global clock frequencies. The longest interconnect can be reduced by 30% through the introduction of a single additional stratum. A 93% reduction in the length of the longest interconnect can be obtained through the optimal use of a three-dimensional architecture for a 100 nm ASIC, potentially leading to a 15.8 times increase in global clock frequency.
Automatic fault detection, isolation, and recovery in transparent all-optical networks

Network fault identification is an important network management function, which is closely related to fault management and has an impact on other network management functions such as configuration management, and performance management. This paper investigates fault surveillance and fault identification mechanisms for a transparent optical network in which data travels optically from the source node to the destination node without going through any optical-to-electrical (O/E) or electrical-to-optical (E/O) conversion. Mechanisms and algorithms are proposed to detect and isolate faults such as fiber cuts, laser, receiver, or router failures. These mechanisms allow nonintrusive device monitoring without requiring any prior knowledge of the actual protocols being used in the data transmission.
Thermal noise modeling for short-channel MOSFETs

An analytical formulation of the thermal noise in short-channel MOSFETs, working in the saturation region, is presented. For the noise calculation, we took into account effects like the field dependent noise temperature and mobility, the device geometry and the channel length modulation, the back gate effect and the velocity saturation. The derived data from the model are in good agreement with reported thermal noise measurements, regarding the noise bias dependence, for transistors with channel lengths shorter than 1 /spl mu/m. Since the present thermal noise models of MOS transistors are valid for channel lengths well above 1 /spl mu/m, the proposed model can be easily incorporated in circuit simulators like SPICE, providing an extension to the analytical thermal noise modeling suitable for submicron MOSFETs.
Wavelength Dependence of the Transformation Mechanism of Sulfonamides Using Different LED Light Sources and TiO2 and ZnO Photocatalysts

The comparison of the efficiency of the commercially available photocatalysts, TiO2 and ZnO, irradiated with 365 nm and 398 nm light, is presented for the removal of two antibiotics, sulfamethazine (SMT) and sulfamethoxypyridazine (SMP). The •OH formation rate was compared using coumarin, and higher efficiency was proved for TiO2 than ZnO, while for 1,4-benzoquinone in O2-free suspensions, the higher contribution of the photogenerated electrons to the conversion was observed for ZnO than TiO2, especially at 398 nm irradiation. An extremely fast transformation and high quantum yield of SMP in the TiO2/LED398nm process were observed. The transformation was fast in both O2 containing and O2-free suspensions and takes place via desulfonation, while in other cases, mainly hydroxylated products form. The effect of reaction parameters (methanol, dissolved O2 content, HCO3− and Cl−) confirmed that a quite rarely observed energy transfer between the excited state P25 and SMP might be responsible for this unique behavior. In our opinion, these results highlight that “non-conventional” mechanisms could occur even in the case of the well-known TiO2 photocatalyst, and the effect of wavelength is also worth investigating.
Steady-state and dynamic models of unified power flow controller (UPFC) for power system studies

This paper provides comprehensive development procedures and final forms of mathematical models of a unified power flow controller (UPFC) for steady-state, transient stability and eigenvalue studies. Based on the developed models, the impacts of control strategy, parameters and location of UPFC on power system operating conditions are discussed. The accuracy of the developed models is verified through comparing the study results with those obtained from detailed time-domain simulation using the Electromagnetic Transients Program (EMTP).
Transgenic Model Systems Have Revolutionized the Study of Disease

The current pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected most of the world in a profound way. As an indirect consequence, the general public has been put into direct contact with the research process, almost in real time. Justifiably, a lot of this focus has been targeted toward research directly linked to coronavirus disease 2019 (COVID-19). In this opinion article, we want to highlight to a general audience the value of having a diverse “portfolio” of research approaches for society as a whole. In this study, we will focus on our field of research, namely the study of gene regulation through the use of transgenesis. We will highlight how this type of research can also be used to provide a better understanding as well as tools to fight SARS-CoV-2 and other future challenges.
Relationship between the monoamine oxidase gene overactivity and the other pathophysiological and behavioral parameters implicated in memory deficiency in albino Winstar rats as Alzheimer’s disease model

The current study aimed to assess the pathophysiology mechanisms that mediate the effect on albin winstar rats' memory induced by the co -administration of fluoride and aluminum sulfate, as a model of Alzheimer's disease. This was done by assessing monoamine oxidase-A (MAO-A) activity, antioxidant activity, H2O2 and amyloid-β concentration in the hippocampus, embedded deep into the brain's temporal lobe, and level of cytokines in serum. The polymerase chain reaction approach was used to genotyping MAO-A, followed by single -stranded conformational polymorphism (SSCP) coupled with sequencing technique. The experimental animals were divided into two groups: control and treated groups. The uptake of heavy metals led to significantly increased MAO-A activity, amyloid -β deposition, H2O2 and cytokines levels in the treated group. However, the finding showed a significant decrease in antioxidant activity in the treated group. The results indicated that metals caused memory and learning impairments. PCR -SSCP genotyping showed many SNPs and haplotypes of the MAO-A exon 2 region, which showed the MAO-A gene polymorphism changes associated with Alzheimer's disease. The overall results indicated a role of metals to induce oxidative stress stimulating pathophysiological hallmarks in the hippocampus due to an increase in the influx of monoamine oxidase expression, which has been implicated in impaired memory, this study focused on the genetic variation of the exon 2 in monoamine oxidase-A gene and its relationship to Alzheimer's disease with the presence of several single nucleotide polymorphisms that may be related to Alzheimer's disease model in rats.
Pitch Accent Distribution and Focus Structure in Taifi Arabic: A Production Study

Prosodic encoding of focus in Taifi Arabic is not yet fully understood. A recent production study found significant acoustic differences between syntactically identical sentences with information focus, contrastive focus and without focus. This paper presents results from a production experiment investigating whether information and contrastive focus have prosodic effects on the pitch-accent distributions. Using question-answer paradigms, 16 native speakers of Taifi Arabic were asked to read three target sentences in different focus conditions. Results reveal that every content word is pitch-accented in utterances with and without focus. However, there are very few cases (23.12%) in which the post-focus words are deaccented. The largest percentage of deaccentuation was observed in the utterances with initial contrastive focus. The results show that focus structures in Taifi Arabic show both deaccentuation and post-focus compression. Therefore, the prosodic realization of focus in Taifi Arabic is different from their counterparts in other Arabic dialects such as Egyptian and Lebanese Arabic. These findings have an important implication for both the prosodic typology and focus typology.
Financial Distress and Firm Performance: Evidence from COVID-19.

This study is dedicated to discovering the impact of COVID-19 on Malaysia’s plantation industry firms. This paper uses quarterly data from annual report of 39 listed firms from Malaysia from 2018 to 2020. The variables to measure financial distress are debt ratio and debt-to-equity ratio while the measurement for firm performance is return on assets. The findings shows that there is a significant negative relationship between debt-to-equity ratio on firm performance. This indicates that the increase in debt-to-equity ratio results in a significant decrease in return on total assets. On the other hand, positive correlation exists between debt ratio and firm performance. This means that an increase in debt ratio results in an increase in the return value of total assets.
Image Preprocessing Method in Radiographic Inspection for Automatic Detection of Ship Welding Defects

Welding defects must be inspected to verify that the welds meet the requirements of ship welded joints, and in welding defect inspection, among nondestructive inspections, radiographic inspection is widely applied during the production process. To perform nondestructive inspection, the completed weldment must be transported to the nondestructive inspection station, which is expensive; consequently, automation of welding defect detection is required. Recently, at several processing sites of companies, continuous attempts are being made to combine deep learning to detect defects more accurately. Preprocessing for welding defects in radiographic inspection images should be prioritized to automatically detect welding defects using deep learning during radiographic nondestructive inspection. In this study, by analyzing the pixel values, we developed an image preprocessing method that can integrate the defect features. After maximizing the contrast between the defect and background in radiographic through CLAHE (contrast-limited adaptive histogram equalization), denoising (noise removal), thresholding (threshold processing), and concatenation were sequentially performed. The improvement in detection performance due to preprocessing was verified by comparing the results of the application of the algorithm on raw images, typical preprocessed images, and preprocessed images. The mAP for the training data and test data was 84.9% and 51.2% for the preprocessed image learning model, whereas 82.0% and 43.5% for the typical preprocessed image learning model and 78.0%, 40.8% for the raw image learning model. Object detection algorithm technology is developed every year, and the mAP is improving by approximately 3% to 10%. This study achieved a comparable performance improvement by only preprocessing with data.