Plant Disease Diagnosing Based on Deep Learning Techniques: A Survey and Research Challenges

Agriculture crops are highly significant for the sustenance of human life and act as an essential source for national income development worldwide. Plant diseases and pests are considered one of the most imperative factors influencing food production, quality, and minimize losses in production. Farmers are currently facing difficulty in identifying various plant diseases and pests, which are important to prevent plant diseases effectively in a complicated environment. The recent development of deep learning techniques has found use in the diagnosis of plant diseases and pests, providing a robust tool with highly accurate results. In this context, this paper presents a comprehensive review of the literature that aims to identify the state of the art of the use of convolutional neural networks (CNNs) in the process of diagnosing and identification of plant pest and diseases. In addition, it presents some issues that are facing the models performance, and also indicates gaps that should be addressed in the future. In this regard, we review studies with various methods that addressed plant disease detection, dataset characteristics, the crops, and pathogens. Moreover, it discusses the commonly employed five-step methodology for plant disease recognition, involving data acquisition, preprocessing, segmentation, feature extraction, and classification. It discusses various deep learning architecture-based solutions that have a faster convergence rate of plant disease recognition. From this review, it is possible to understand the innovative trends regarding the use of CNN’s algorithms in the plant diseases diagnosis and to recognize the gaps that need the attention of the research community

Development of cost estimation model of the membrane system

Apart from product quality, the manufacturing cost is an important element to compete in the competitive industry. Detail economic assessment is important to estimate the product cost accurately and avoid overestimating or underestimating that give bad impact to the firm. Membrane system; a compact, sustainable and cheaper wastewater treatment system compared to the traditional system. Yet, there is limited study analysing the economic aspect of the membrane system due to the limited historical data, a complicated process involved and deal with tangible overhead costs. Thus, this study aims to develop a cost model to estimate the total cost of the membrane system during its lifespan. Activity-based costing (ABC) method is used as cost estimation technique to calculating the overhead cost and added the direct costs to determine the life-cycle cost (LCC) of the membrane system by using Microsoft Excel while Microsoft Visual Basic is used to demonstrate a user-friendly cost estimation model. The proposed cost model is a simpler system because the end user is guided to get the LCC value without has to deal with a complicated equation. The proposed model cost is tested to estimating the LCC of HFMM in treating wastewater from the prototype stage until the disposal stage

Effects of plasma treated alumina nanoparticles on breakdown strength, partial discharge resistance, and thermophysical properties of mineral oil-based nanofluids

Mineral oil has been chosen as an insulating liquid in power transformers due to its superior characteristics, such as being an effective insulation medium and a great cooling agent. Meanwhile, the performance of mineral oil as an insulation liquid can be further enhanced by dispersing nanoparticles into the mineral oil, and this composition is called nanofluids. However, the incorporation of nanoparticles into the mineral oil conventionally causes the nanoparticles to agglomerate and settle as sediment in the base fluid, thereby limiting the improvement of the insulation properties. In addition, limited studies have been reported for the transformer oil as a base fluid using Aluminum Oxide (Al2O3) as nanoparticles. Hence, this paper reported an experimental study to investigate the significant role of cold plasma treatment in modifying and treating the surface of nano-alumina to obtain a better interaction between the nano-alumina and the base fluid, consequently improving the insulation characteristics such as breakdown voltage, partial discharge characteristics, thermal conductivity, and viscosity of the nanofluids. The plasma treatment process was conducted on the surface of nano-alumina under atmospheric pressure plasma by using the dielectric barrier discharge concept. The breakdown strength and partial discharge characteristics of the nanofluids were measured according to IEC 60156 and IEC 60270 standards, respectively. In contrast, the viscosity and thermal conductivity of the nanofluids were determined using Brookfield DV-II + Pro Automated viscometer and Decagon KD2-Pro conductivity meter, respectively. The results indicate that the 0.1 wt% of plasma-treated alumina nanofluids has shown the most comprehensive improvements in electrical properties, dispersion stability, and thermal properties. Therefore, the plasma treatment has improved the nanoparticles dispersion and stability in nanofluids by providing stronger interactions between the mineral oil and the nanoparticles

Characterization of cold plasma with glow discharge mechanism of plasma jet system

Cold plasma with glow discharge mechanism exhibiting a uniform ionization process when a background gas passes through the discharge region of the plasma reactor under a certain optimum configuration of input parameters. A glow discharge is a homogeneous and effective mechanism of cold plasma for industrial applications due to the continuous and stable discharge process compared to the filamentary discharge. Meanwhile, the development of glow discharge plasma operated under atmospheric pressure condition is indispensable to overcome the weaknesses of filamentary discharge plasma, such as the nonuniform and discontinuous discharge process. The discharge mechanism is essentially dependent upon the input parameters of the plasma system, such as the amplitude of the voltage supply, the operating frequency, and the flow rate of the background gas. In this paper, the effects of voltage supply on plasma discharge characteristics produced from the plasma jet reactor with the high-voltage electrode are discussed. The value of voltage supply is tuned to be suitable with the discharge gap, frequency supply, and background gas flow rate in producing the homogeneous glow plasma discharge. The characteristics of the glow plasma discharge produced are analyzed based on the pattern of the charge-voltage Lissajous figure and time-domain discharge current techniques. Results show that the most efficient and uniform plasma is disclosed by the configuration of input parameters such as 0.5 kV of supply voltage, 20 kHz of operating frequency, and 0.8 L/min of purified helium gas flow rate. The parallelogram-like Lissajous figure obtained indicating the homogeneous plasma discharge with a constant value of discharge capacitance

Proposed analytic framework for student relationship management based on a systematic review of CRM systems literature

Notwithstanding the research attention given to the importance and capability of the student relationship management strategy in higher education sustainability, there is no any systematic framework for implementation. This research as one of the preliminary studies has been undertaken to provide a structural framework of strategic practices for positioning this strategy at an operational level. In doing so, a methodological approach was implemented in two tiers. Firstly, a systematic review of the leading-edge literature on the customer relationship management systems was performed owing to the lack of significant research on the topic, as well as the structure and nature of the concept. Then, the principal components factor analysis with varimax rotation, which is a method of exploratory factor analysis was used to finalize the research. The findings revealed an articulated structural framework with five hypotheses, which may partially or fully be applied to narrow the major gap in the current knowledge. The measurement scale has also been developed for simplification in implementation of the application. Limitations and directions for future research were accordingly discussed

Critical success factors of student relationship management

Due to the upward trend in the globalization of sustainability issues and the intense competitive environment, it is evident that higher education institutions need new strategic approaches to succeed. To this end, the inquiry for this paper has been made into the debate about student relationship management. Going through the literature indicates that institutions have mainly perceived the concept as a technological initiative for solving the problems in individual domains, accompanied by uncoordinated efforts. Thus, the aims of this study are to theoretically present the critical success factors of this strategic approach and to empirically examine the recognized factors. To do so, a confirmatory factor analysis that is a quantitative analytic method was performed. The results and analyses revealed that there has been a significant correlation between the four critical success factors including knowledge management, student relationship management technology, student orientation, and employees' involvement. It was also found that these factors are significantly correlated with the construct of student relationship management success. The findings have consequently highlighted that in addition to the technological tool, the role of knowledge management, employees' involvement, and student orientation appeared to be particularly important for the implementation of the application

Selective formation of tungsten nanowires

We report on a process for fabricating self-aligned tungsten (W) nanowires with polycrystalline silicon core. Tungsten nanowires as thin as 10 nm were formed by utilizing polysilicon sidewall transfer technology followed by selective deposition of tungsten by chemical vapor deposition (CVD) using WF6 as the precursor. With selective CVD, the process is self-limiting whereby the tungsten formation is confined to the polysilicon regions; hence, the nanowires are formed without the need for lithography or for additional processing. The fabricated tungsten nanowires were observed to be perfectly aligned, showing 100% selectivity to polysilicon and can be made to be electrically isolated from one another. The electrical conductivity of the nanowires was characterized to determine the effect of its physical dimensions. The conductivity for the tungsten nanowires were found to be 40% higher when compared to doped polysilicon nanowires of similar dimensions

Application of geographic information systems and simulation modelling to dental public health: Where next?

Public health research in dentistry has used geographic information systems since the 1960s. Since then, the methods used in the field have matured, moving beyond simple spatial associations to the use of complex spatial statistics and, on occasions, simulation modelling. Many analyses are often descriptive in nature; however, and the use of more advanced spatial simulation methods within dental public health remains rare, despite the potential they offer the field. This review introduces a new approach to geographical analysis of oral health outcomes in neighbourhoods and small area geographies through two novel simulation methods-spatial microsimulation and agent-based modelling. Spatial microsimulation is a population synthesis technique, used to combine survey data with Census population totals to create representative individual-level population datasets, allowing for the use of individual-level data previously unavailable at small spatial scales. Agent-based models are computer simulations capable of capturing interactions and feedback mechanisms, both of which are key to understanding health outcomes. Due to these dynamic and interactive processes, the method has an advantage over traditional statistical techniques such as regression analysis, which often isolate elements from each other when testing for statistical significance. This article discusses the current state of spatial analysis within the dental public health field, before reviewing each of the methods, their applications, as well as their advantages and limitations. Directions and topics for future research are also discussed, before addressing the potential to combine the two methods in order to further utilize their advantages. Overall, this review highlights the promise these methods offer, not just for making methodological advances, but also for adding to our ability to test and better understand theoretical concepts and pathways

Factors Associated with Negative Direct Sputum Examination in Asian and African HIV-Infected Patients with Tuberculosis (ANRS 1260)

OBJECTIVE: To identify factors associated with negative direct sputum examination among African and Cambodian patients co-infected by Mycobacterium tuberculosis and HIV. DESIGN: Prospective multicenter study (ANRS1260) conducted in Cambodia, Senegal and Central African Republic. METHODS: Univariate and multivariate analyses (logistic regression) were used to identify clinical and radiological features associated with negative direct sputum examination in HIV-infected patients with positive M. tuberculosis culture on Lowenstein-Jensen medium. RESULTS: Between September 2002 and December 2005, 175 co-infected patients were hospitalized with at least one respiratory symptom and pulmonary radiographic anomaly. Acid-fast bacillus (AFB) examination was positive in sputum samples from 110 subjects (63%) and negative in 65 patients (37%). Most patients were at an advanced stage of HIV disease (92% at stage III or IV of the WHO classification) with a median CD4 cell count of 36/mm³. In this context, we found that sputum AFB negativity was more frequent in co-infected subjects with associated respiratory tract infections (OR = 2.8 [95%CI:1.1-7.0]), dyspnea (OR = 2.5 [95%CI:1.1-5.6]), and localized interstitial opacities (OR = 3.1 [95%CI:1.3-7.6]), but was less frequent with CD4 ≤ 50/mm³ (OR = 0.4 [95%CI:0.2-0.90), adenopathies (OR = 0.4 [95%CI:0.2-0.93]) and cavitation (OR = 0.1 [95%CI:0.03-0.6]). CONCLUSIONS: One novel finding of this study is the association between concomitant respiratory tract infection and negative sputum AFB, particularly in Cambodia. This finding suggests that repeating AFB testing in AFB-negative patients should be conducted when broad spectrum antibiotic treatment does not lead to complete recovery from respiratory symptoms. In HIV-infected patients with a CD4 cell count below 50/mm3 without an identified cause of pneumonia, systematic AFB direct sputum examination is justified because of atypical clinical features (without cavitation) and high pulmonary mycobacterial burden

Multi-ethnic genome-wide association study for atrial fibrillation

Atrial fibrillation (AF) affects more than 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF