Search results for: light detection and ranging

Authors: Ebere Christian Ugochukwu, Okafor Josephine, Oyawoye Tomisin

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The occurrence of multidrug resistance patterns that have been developed by bacteria has made it difficult to properly treat infections using standard clinical medications. Hence, the use of herbs as an alternative source of therapy is considered cheap and easily accessible to locals. This research explored the antimicrobial effects of aqueous and ethanolic extracts obtained from Chrysophyllum albidum (commonly called ‘Agbalumo’ in southwest Nigeria and ‘Udara’ in the eastern and southern parts of Nigeria) plant parts (leaves, roots and seeds) against bacteria isolated from urinary catheter tips. The following isolates were obtained; Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Proteus mirabilis, and Klebsiella aerogenes. The agar well diffusion method was used. The average percentages of antimicrobial resistance of the isolates to gentamycin were 45.5% for P. aeruginosa, 42.1% for E. coli, 46.9% for K. aerogenes, and ˃90% for other isolates. Qualitative phytochemical screening of the plant parts extracts was done using chemical test for the screening and identification of bioactive chemical constituents. The ethanolic extract mixtures (leaf, root and seed) had the greatest effect on all the isolates, with inhibition zones (IZs) ranging from 8-26 mm and MICs ranging from <16-32 mg/ml. The Potencies of the C. albidum extracts based on the IZ and MIC values were greater in the extract mixtures, followed by those in the roots. Phytochemical screening revealed that all the extracts contained phenol except for the seeds while tannins were present in all the extracts except the leaves. The activity of the ethanolic extracts of each part at high and low concentrations was greater than that of the aqueous extracts at the same concentrations (p<0.05). The acute toxicity results showed that the LD50 of the extracts was ˃5000 mg/body weight, indicating no toxicity. The antibacterial activities of the extract mixtures and roots on the isolates confirmed the use of C. albidum in folk medicine for the treatment of CAUTIs, hence indicating its antibacterial potential for use in novel antibiotic production.

Keywords: antimicrobials, susceptibility, minimum inhibitory concentration, extracts

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Nagendra P. Luitel, Mark J. D. Jordans

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Globally, there is a significant gap between the number of individuals in need of mental health care and those who actually receive treatment. The evidence is accumulating that mental health services can be delivered effectively by primary health care workers through community-based programs and task-sharing approaches. Changing the role of specialist mental health workers from service delivery to building clinical capacity of the primary health care (PHC) workers could help in reducing treatment gap in low and middle-income countries (LMICs). We developed a comprehensive mental health care plan in 2012 and evaluated its feasibility and effectiveness over the past three years. Initially, a mixed method formative study was conducted for the development of mental health care plan (MHCP). Routine monitoring and evaluation data, including client flow and reports of satisfaction, were obtained from beneficiaries (n=135) during the pilot-testing phase. Repeated community survey (N=2040); facility detection survey (N=4704) and the cohort study (N=576) were conducted for evaluation of the MHCP. The resulting MHCP consists of twelve packages divided over the community, health facility, and healthcare organization platforms. Detection of mental health problems increased significantly after introducing MHCP. Service implementation data support the real-life applicability of the MHCP, with reasonable treatment uptake. Currently, MHCP has been implemented in the entire Chitwan district where over 1400 people (438 people with depression, 406 people with psychosis, 181 people with epilepsy, 360 people with alcohol use disorder and 51 others) have received mental health services from trained health workers. Key barriers were identified and addressed, namely dissatisfaction with privacy, perceived burden among health workers, high drop-out rates and continue the supply of medicines. The results indicated that involvement of PHC workers in detection and management of mental health problems is an effective strategy to minimize treatment gap on mental health care in Nepal.

Keywords: mental health, Nepal, primary care, treatment gap

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

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Authors: Tuba Zahra, Aakash Parekh

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Hyperspectral remote sensing refers to imaging of objects or materials in narrow conspicuous spectral bands. Hyperspectral images (HSI) enable the extraction of spectral signatures for objects or materials observed. These images contain information about the reflectance of each pixel across the electromagnetic spectrum. It enables the acquisition of data simultaneously in hundreds of spectral bands with narrow bandwidths and can provide detailed contiguous spectral curves that traditional multispectral sensors cannot offer. The contiguous, narrow bandwidth of hyperspectral data facilitates the detailed surveying of Earth's surface features. This would otherwise not be possible with the relatively coarse bandwidths acquired by other types of imaging sensors. Hyperspectral imaging provides significantly higher spectral and spatial resolution. There are several use cases that represent the commercial applications of hyperspectral remote sensing. Each use case represents just one of the ways that hyperspectral satellite imagery can support operational efficiency in the respective vertical. There are some use cases that are specific to VNIR bands, while others are specific to SWIR bands. This paper discusses the different commercially viable use cases that are significant for HSI application areas, such as agriculture, mining, oil and gas, defense, environment, and climate, to name a few. Theoretically, there is n number of use cases for each of the application areas, but an attempt has been made to streamline the use cases depending upon economic feasibility and commercial viability and present a review of literature from this perspective. Some of the specific use cases with respect to agriculture are crop species (sub variety) detection, soil health mapping, pre-symptomatic crop disease detection, invasive species detection, crop condition optimization, yield estimation, and supply chain monitoring at scale. Similarly, each of the industry verticals has a specific commercially viable use case that is discussed in the paper in detail.

Keywords: agriculture, mining, oil and gas, defense, environment and climate, hyperspectral, VNIR, SWIR

Procedia PDF Downloads 81

Authors: A. Bahieldin, A. Atef, S. Edris, N. O. Gadalla, S. M. Hassan, M. A. Al-Kordy, A. M. Ramadan, A. S. M. Al- Hajar, F. M. El-Domyati

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The idea of this work is based on a natural exciting phenomenon suggesting that suppression of genes related to the program cell death (or PCD) mechanism might help the plant cells to efficiently tolerate abiotic stresses. The scope of this work was the detection of PCD-related transcription factors (TFs) that might also be related to salt stress tolerance in plant. Two model plants, e.g., tobacco and Arabidopsis, were utilized in order to investigate this phenomenon. Occurrence of PCD was first proven by Evans blue staining and DNA laddering after tobacco leaf discs were treated with oxalic acid (OA) treatment (20 mM) for 24 h. A number of 31 TFs up regulated after 2 h and co-expressed with genes harboring PCD-related domains were detected via RNA-Seq analysis and annotation. These TFs were knocked down via virus induced gene silencing (VIGS), an RNA interference (RNAi) approach, and tested for their influence on triggering PCD machinery. Then, Arabidopsis SALK knocked out T-DNA insertion mutants in selected TFs analogs to those in tobacco were tested under salt stress (up to 250 mM NaCl) in order to detect the influence of different TFs on conferring salt tolerance in Arabidopsis. Involvement of a number of candidate abiotic-stress related TFs was investigated.

Keywords: VIGS, PCD, RNA-Seq, transcription factors

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Authors: Eka Maulana, Sholeh Hadi Pramono, Dody Fanditya, M. Julius

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In this paper, extract of papaya leaves are used as a natural dye and combined by variations of solvent concentration applied on DSSC (Dye-Sensitized Solar Cell). Indonesian geographic located on the equator line occasions the magnitude of the potential to develop organic solar cells made from extracts of chlorophyll as a substitute for inorganic materials or synthetic dye on DSSC material. Dye serves as absorbing photons which are then converted into electrical energy. A conductive coated glass layer called TCO (Transparent Conductive Oxide) is used as a substrate of electrode. TiO2 nanoparticles as binding dye molecules, redox couple iodide/ tri-iodide as the electrolyte and carbon as the counter electrode in the DSSC are used. TiO2 nanoparticles, organic dyes, electrolytes and counter electrode are arranged and combined with the layered structure of the photo-catalyst absorption layer. Dye absorption measurements using a spectrophotometer at 200-800 nm light spectrum produces a total amount of chlorophyll 80.076 mg/l. The test cell at 7 watt LED light with 5000 lux luminescence were obtained Voc and Isc of 235.5 mV and 14 μA, respectively.

Keywords: DSSC (Dye-Sensitized Solar Cell), natural dye, chlorophyll, absorption

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Authors: Zaoui Ismahene, Bahri Sidi Mohamed, Abbassa Nadira

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Diabetic Retinopathy (DR) is a leading cause of vision impairment and blindness among individuals with diabetes. Early diagnosis is crucial for effective treatment, yet current diagnostic methods rely heavily on manual analysis of retinal images, which can be time-consuming and prone to subjectivity. This research proposes an automated system for the detection of DR using Jacobi wavelet-based feature extraction combined with Support Vector Machines (SVM) for classification. The integration of wavelet analysis with machine learning techniques aims to improve the accuracy, efficiency, and reliability of DR diagnosis. In this study, retinal images are preprocessed through normalization, resizing, and noise reduction to enhance the quality of the images. The Jacobi wavelet transform is then applied to extract both global and local features, effectively capturing subtle variations in retinal images that are indicative of DR. These extracted features are fed into an SVM classifier, known for its robustness in handling high-dimensional data and its ability to achieve high classification accuracy. The SVM classifier is optimized using parameter tuning to improve performance. The proposed methodology is evaluated using a comprehensive dataset of retinal images, encompassing a range of DR severity levels. The results show that the proposed system outperforms traditional wavelet-based methods, demonstrating significantly higher accuracy, sensitivity, and specificity in detecting DR. By leveraging the discriminative power of Jacobi wavelet features and the robustness of SVM, the system provides a promising solution for the automatic detection of DR, which could assist ophthalmologists in early diagnosis and intervention, ultimately improving patient outcomes. This research highlights the potential of combining wavelet-based image processing with machine learning for advancing automated medical diagnostics.

Keywords: iabetic retinopathy (DR), Jacobi wavelets, machine learning, feature extraction, classification

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Authors: Florina Dutt, Subhajit Das, Matthew Swartz

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Lighting design and its impact on indoor comfort conditions are an integral part of good interior design. Impact of lighting in an interior space is manifold and it involves many sub components like glare, color, tone, luminance, control, energy efficiency, flexibility etc. While other components have been researched and discussed multiple times, this paper discusses the research done to understand the glare component from an artificial lighting source in an indoor space. Consequently, the paper discusses a parametric model to convey real time glare level in an interior space to the designer/ architect. Our end users are architects and likewise for them it is of utmost importance to know what impression the proposed lighting arrangement and proposed furniture layout will have on indoor comfort quality. This involves specially those furniture elements (or surfaces) which strongly reflect light around the space. Essentially, the designer needs to know the ramification of the ‘discomfortable glare’ at the early stage of design cycle, when he still can afford to make changes to his proposed design and consider different routes of solution for his client. Unfortunately, most of the lighting analysis tools that are present, offer rigorous computation and analysis on the back end eventually making it challenging for the designer to analyze and know the glare from interior light quickly. Moreover, many of them do not focus on glare aspect of the artificial light. That is why, in this paper, we explain a novel approach to approximate interior glare data. Adding to that we visualize this data in a color coded format, expressing the implications of their proposed interior design layout. We focus on making this analysis process very fluid and fast computationally, enabling complete user interaction with the capability to vary different ranges of user inputs adding more degrees of freedom for the user. We test our proposed parametric model on a case study, a Computer Lab space in our college facility.

Keywords: computational geometry, glare impact in interior space, info visualization, parametric lighting analysis

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Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

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Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: raman spectroscopy, mars-analog, beta-carotene, PAHs

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Authors: Indu Verma, Santanu Kumar Pal

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Interactions between DNA and adsorbed Poly (L-lysine) (PLL) on liquid crystal (LC) droplets were investigated using polarizing optical microcopy (POM) and epi-fluorescence microscopy. Earlier, we demonstrated that adsorption of PLL to the LC/aqueous interface resulted in homeotropic orientation of the LC and thus exhibited a radial configuration of the LC confined within the droplets. Subsequent adsorption of DNA (single stranded DNA/double stranded DNA) at PLL coated LC droplets was found to trigger a LC reorientation within the droplets leading to pre-radial/bipolar configuration of those droplets. To our surprise, subsequent exposure of complementary ssDNA (c-ssDNA) to ssDNA/ adsorbed PLL modified LC droplets did not cause the LC reorientation. This is likely due to the formation of polyplexes (DNA-PLL complex) as confirmed by fluorescence microscopy and atomic force microscopy. In addition, dsDNA adsorbed PLL droplets have been found to be effectively used to displace (controlled release) propidium iodide (a model drug) encapsulated within dsDNA over time. These observations suggest the potential for a label free droplet based LC detection system that can respond to DNA and may provide a simple method to develop DNA-based drug nano-carriers.

Keywords: DNA biosensor, drug delivery, interfaces, liquid crystal droplets

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Authors: Mohd Sukri Hassan, Ahlam Inayatullah Badrul Munir, M. Husaini A. Rahman

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Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10^-1 to 10^-5 ng/µl were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.

Keywords: halal, real-time PCR, gelatine, chemometrics

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Authors: F. J. Puertas, M. Castro, A. Tebar, P. J. Fito, R. Gadea, J. M. Monzó, R. J. Colom

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There is a great diversity of diseases that affect the integrity of the walls of the esophagus, generally of a digestive nature. Among them, gastroesophageal reflux is a common disease in the general population, affecting the patient's quality of life; however, there are still unmet diagnostic and therapeutic issues. The consequences of untreated or asymptomatic acid reflux on the esophageal mucosa are not only pain, heartburn, and acid regurgitation but also an increased risk of esophageal cancer. Currently, the diagnostic methods to detect problems in the esophageal tract are invasive and annoying, as 24-hour impedance-pH monitoring forces the patient to be uncomfortable for hours to be able to make a correct diagnosis. In this work, the development of a sensor able to measure in depth is proposed, allowing the detection of liquids circulating in the esophageal tract. The multisensor detection system is based on radiofrequency photospectrometry. At an experimental level, consumers representative of the population in terms of sex and age have been used, placing the sensors between the trachea and the diaphragm analyzing the measurements in vacuum, water, orange juice and saline medium. The results obtained have allowed us to detect the appearance of different liquid media in the esophagus, segregating them based on their ionic content.

Keywords: bioimpedance, dielectric spectroscopy, gastroesophageal reflux, GERD

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Authors: René Vieroth, Christian Dils, M. V. Krshiwoblozki, Christine Kallmayer, Martin Schneider-Ramelow, Klaus-Dieter Lang

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Green urban mobility in commercial and private contexts is one of the great challenges for the continuously growing cities all over the world. Bicycle based solutions are already and since a long time the key to success. Modern developments like e-bikes and high-end cargo-bikes complement the portfolio. Weight, aerodynamic drag, and security for the transported goods are the key factors for working solutions. Recent achievements in the field of smart-textiles allowed the creation of a totally new generation of intelligent textile cargo containers, which fulfill those demands. The fusion of technical textiles, design and electrical engineering made it possible to create an ecological solution which is very near to become a product. This paper shows all the details of this solution that includes an especially developed sensor textile for cut detection, a protective textile layer for intrusion prevention, an universal-charging-unit for energy harvesting from diverse sources and a low-energy alarm system with GSM/GPRS connection, GPS location and RFID interface.

Keywords: cargo-bike, cut-detection, e-bike, energy-harvesting, green urban mobility, logistics, smart-textiles, textile-integrity sensor

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Authors: Maali-Amel Mersel, Lajos Fodor, Otto Horvath

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Photocatalytic H₂ production by H₂S decomposition is regarded to be an environmentally friendly process to produce carbon-free energy through direct solar energy conversion. For this purpose, sulphide-based materials, as photocatalysts, were widely used due to their excellent solar spectrum responses and high photocatalytic activity. The loading of proper co-catalysts that are based on cheap and earth-abundant materials on those semiconductors was shown to play an important role in the improvement of their efficiency. In this research, CdS-ZnS composite was studied because of its controllable band gap and excellent performance for H₂ evolution under visible light irradiation. The effects of the modification of this photocatalyst with different types of materials and the influence of the preparation parameters on its H₂ production activity were investigated. The CdS-ZnS composite with an enhanced photocatalytic activity for H₂ production was synthesized from ammine complexes. Two types of modification were used: compounds of Ni-group metals (NiS, PdS, and Pt) were applied as co-catalyst on the surface of CdS-ZnS semiconductor, while NiS, MnS, CoS, Ag₂S, and CuS were used as a dopant in the bulk of the catalyst. It was found that 0.1% of noble metals didn’t remarkably influence the photocatalytic activity, while the modification with 0.5% of NiS was shown to be more efficient in the bulk than on the surface. The modification with other types of metals results in a decrease of the rate of H₂ production, while the co-doping seems to be more promising. The preparation parameters (such as the amount of ammonia to form the ammine complexes, the order of the preparation steps together with the hydrothermal treatment) were also found to highly influence the rate of H₂ production. SEM, EDS and DRS analyses were made to reveal the structure of the most efficient photocatalysts. Moreover, the detection of the conduction band electron on the surface of the catalyst was also investigated. The excellent photoactivity of the CdS-ZnS catalysts with and without modification encourages further investigations to enhance the hydrogen generation by optimization of the reaction conditions.

Keywords: H₂S, photoactivity, photocatalytic H₂ production, CdS-ZnS

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Authors: Natarajan Tirupattur Srinivasan

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Quantum mechanics( QM) and (special) relativity (SR) have indeed revolutionized the very thinking of physicists, and the spectacular successes achieved over a century due to these two theories are mind-boggling. However, there is still a strong disquiet among some physicists. While the mathematical structure of these two theories has been established beyond any doubt, their physical interpretations are still being contested by many. Even after a hundred years of their existence, we cannot answer a very simple question, “What is an electron”? Physicists are struggling even now to come to grips with the different interpretations of quantum mechanics with all their ramifications. However, it is indeed strange that the (special) relativity theory of Einstein enjoys many orders of magnitude of “acceptance”, though both theories have their own stocks of weirdness in the results, like time dilation, mass increase with velocity, the collapse of the wave function, quantum jump, tunnelling, etc. Here, in this paper, it would be shown that by postulating an intrinsic internal motion to these enigmatic electrons, one can build a fairly consistent picture of reality, revealing a very simple picture of nature. This is also evidenced by Schrodinger’s ‘Zitterbewegung’ motion, about which so much has been written. This leads to a helical trajectory of electrons when they move in a laboratory frame. It will be shown that the helix is a three-dimensional wave having all the characteristics of our familiar 2D wave. Again, the helix, being a geodesic on an imaginary cylinder, supports ‘quantization’, and its representation is just the complex exponentials matching with the wave function of quantum mechanics. By postulating the instantaneous velocity of the electrons to be always ‘c’, the velocity of light, the entire relativity comes alive, and we can interpret the ‘time dilation’, ‘mass increase with velocity’, etc., in a very simple way. Thus, this model unifies both QM and SR without the need for a counterintuitive postulate of Einstein about the constancy of the velocity of light for all inertial observers. After all, if the motion of an inertial frame cannot affect the velocity of light, the converse that this constant also cannot affect the events in the frame must be true. But entire relativity is about how ‘c’ affects time, length, mass, etc., in different frames.

Keywords: quantum reconstruction, special theory of relativity, quantum mechanics, zitterbewegung, complex wave function, helix, geodesic, Schrodinger’s wave equations

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Authors: Banu Hatice Gürcüm, Pınar Arslan, Mahmut Yalçın

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Fashion designers create lots of dresses, suits, shoes, and other clothing and accessories, which are purchased every year by consumers. Fashion trends, sketches of designs, accessories affect the apparel goods, but colors make the finishing touches to an outfit. In all fields of apparel men's, women's, and children's wear, including casual wear, suits, sportswear, formal wear, outerwear, maternity, and intimate apparel, color sells. Thus, specialization in color in apparel is a basic concern each season. The perception of color is the key to sales for every sector in textile business. Mechanism of color perception, cognition in brain and color emotion are unique subjects, which scientists have been investigating for many years. The parameters of color may not be corresponding to visual scales since human emotions induced by color are completely subjective. However, with a very few exception each manufacturer concern their top selling colors for each season through seasonal sales reports of apparel companies. This paper examines sensory and instrumental methods for quantifying color of fabrics and investigates the relationship between fabric color and sale numbers. 5 top selling colors for each season from 10 leading apparel companies in the same segment are taken. The compilation is based according to the sales of the companies for 5 to 10 years. The research’s main concern is the corelation with the magnitude of seasonal color selling figures and the CIE chromaticity coordinates. The colors are chosen from the globally accepted Pantone Textile Color System and the three-dimentional measurement system CIE L*a*b* (CIELAB) is used, L* representing the degree of lightness of color, a* the degree of color ranging from magenta to green, and b* the degree of color ranging from blue to yellow. The objective of this paper is to demonstrate the feasibility of relating color perceptance to a laboratory instrument yielding measurements in the CIELAB system. Our approach is to obtain a total of a hundred reference fabrics to be measured on a laboratory spectrophotometer calibrated to the CIELAB color system. Relationships between the CIE tristimulus (X, Y, Z) and CIELAB (L*, a*, b*) are examined and are reported herein.

Keywords: CIELAB, CIE tristimulus, color preference, fashion

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Authors: A. A. Abaker Omer, H. B. Mohamed Balh, W. Liu, A. Abas, J. Yu, S. Li, W. Ma, W. El Kolaly, Y. Y. Ahmed Abuker

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We have discovered an important technical solution that could make new approaches in the processing of wet silicon etching, especially in the production of photovoltaic cells. During its inferior light-trapping and structural properties, the inverted pyramid structure outperforms the conventional pyramid textures and black silicone. The traditional pyramid textures and black silicon can only be accomplished with more advanced lithography, laser processing, etc. Importantly, our data demonstrate the feasibility of an inverted pyramidal structure of silicon via one-step Cu-catalyzed chemical etching (CCCE) in Cu (NO₃)₂/HF/H₂O₂/H₂O solutions. The effects of etching time and reaction temperature on surface geometry and light trapping were systematically investigated. The conclusion shows that the inverted pyramid structure has ultra-low reflectivity of ~4.2% in the wavelength of 300~1000 nm; introduce of Cu particles can significantly accelerate the dissolution of the silicon wafer. The etching and the inverted pyramid structure formation mechanism are discussed. Inverted pyramid structure with outstanding anti-reflectivity includes useful applications throughout the manufacture of semi-conductive industry-compatible solar cells, and can have significant impacts on industry colleagues and populations.

Keywords: Cu-catalyzed chemical etching, inverted pyramid nanostructured, reflection, solar cells

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Authors: Haifeng Zhou, Tsungyang Liow, Xiaoguang Tu, Eujin Lim, Chao Li, Junfeng Song, Xianshu Luo, Ying Huang, Lianxi Jia, Lianwee Luo, Kim Dowon, Qing Fang, Mingbin Yu, Guoqiang Lo

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Several Germanium photodetectors (PD) built on silicon micro-disks are fabricated on the standard Si photonics multiple project wafers (MPW) and demonstrated to exhibit very low dark current, satisfactory operation bandwidth and moderate responsivity. Among them, a vertical p-i-n Ge PD based on a 2.0 µm-radius micro-disk has a dark current of as low as 35 nA, compared to a conventional PD current of 1 µA with an area of 100 µm2. The operation bandwidth is around 15 GHz at a reverse bias of 1V. The responsivity is about 0.6 A/W. Microdisk is a striking planar structure in integrated optics to enhance light-matter interaction and construct various photonics devices. The disk geometries feature in strongly and circularly confining light into an ultra-small volume in the form of whispering gallery modes. A laser may benefit from a microdisk in which a single mode overlaps the gain materials both spatially and spectrally. Compared to microrings, micro-disk removes the inner boundaries to enable even better compactness, which also makes it very suitable for some scenarios that electrical connections are needed. For example, an ultra-low power (≈ fJ) athermal Si modulator has been demonstrated with a bit rate of 25Gbit/s by confining both photons and electrically-driven carriers into a microscale volume.In this work, we study Si-based PDs with Ge selectively grown on a microdisk with the radius of a few microns. The unique feature of using microdisk for Ge photodetector is that mode selection is not important. In the applications of laser or other passive optical components, microdisk must be designed very carefully to excite the fundamental mode in a microdisk in that essentially the microdisk usually supports many higher order modes in the radial directions. However, for detector applications, this is not an issue because the local light absorption is mode insensitive. Light power carried by all modes are expected to be converted into photo-current. Another benefit of using microdisk is that the power circulation inside avoids any introduction of the reflector. A complete simulation model with all involved materials taken into account is established to study the promise of microdisk structures for photodetector by using finite difference time domain (FDTD) method. By viewing from the current preliminary data, the directions to further improve the device performance are also discussed.

Keywords: integrated optical devices, silicon photonics, micro-resonator, photodetectors

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Authors: P. Parthiban, J. Karthikeyan

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This paper deals with the performance of semi-light weight concrete, prepared by using wood ash pellets as coarse aggregates which were improved by partial replacement of cement with alccofine. Alccofine is a mineral admixture which contains high glass content obtained through the process of controlled granulation. This is finer than cement which carries its own pozzolanic property. Therefore, cement could be replaced by alccofine as 0%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, and 70% to enhance the strength and durability properties of concrete. High range water reducing admixtures (HRWA) were used in these mixes which were dosed up to 1.5% weight of the total cementitious content (alccofine & cement). It also develops the weaker transition zone into more impermeable layer. Specimens were subjected in both the accelerated curing method as well as conventional curing method. Experimental results were compared and reported, in that the maximum compressive strength of 32.6 MPa was achieved on 28^th day with 30% replacement level in a density of 2200 kg/m³ to a conventional curing, while in the accelerated curing, maximum compressive strength was achieved at 40% replacement level. Rapid chloride penetration test (RCPT) output results for the conventional curing method at 0% and 70% give 3296.7 and 545.6 coulombs.

Keywords: Alccofine, compressive strength, RCPT, wood ash pellets

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Leonard Tiong, Sonit Singh, Kevin Ho Shon, Sarah Lewis

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Investigation into the use of artificial intelligence in radiology continues to develop at a rapid rate. During the coronavirus pandemic, the combination of an exponential increase in chest x-rays and unpredictable staff shortages resulted in a huge strain on the department's workload. There is a World Health Organisation estimate that two-thirds of the global population does not have access to diagnostic radiology. Therefore, there could be demand for a program that could detect acute changes in imaging compatible with infection to assist with screening. We generated a conventional neural network and tested its efficacy in recognizing changes compatible with coronavirus infection. Following ethics approval, a deidentified set of 77 normal and 77 abnormal chest x-rays in patients with confirmed coronavirus infection were used to generate an algorithm that could train, validate and then test itself. DICOM and PNG image formats were selected due to their lossless file format. The model was trained with 100 images (50 positive, 50 negative), validated against 28 samples (14 positive, 14 negative), and tested against 26 samples (13 positive, 13 negative). The initial training of the model involved training a conventional neural network in what constituted a normal study and changes on the x-rays compatible with coronavirus infection. The weightings were then modified, and the model was executed again. The training samples were in batch sizes of 8 and underwent 25 epochs of training. The results trended towards an 85.71% true positive/true negative detection rate and an area under the curve trending towards 0.95, indicating approximately 95% accuracy in detecting changes on chest X-rays compatible with coronavirus infection. Study limitations include access to only a small dataset and no specificity in the diagnosis. Following a discussion with our programmer, there are areas where modifications in the weighting of the algorithm can be made in order to improve the detection rates. Given the high detection rate of the program, and the potential ease of implementation, this would be effective in assisting staff that is not trained in radiology in detecting otherwise subtle changes that might not be appreciated on imaging. Limitations include the lack of a differential diagnosis and application of the appropriate clinical history, although this may be less of a problem in day-to-day clinical practice. It is nonetheless our belief that implementing this program and widening its scope to detecting multiple pathologies such as lung masses will greatly assist both the radiology department and our colleagues in increasing workflow and detection rate.

Keywords: artificial intelligence, COVID, neural network, machine learning

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Authors: Mohamed Al-Hazmi, Abdullah Al-Arfaj, Moussa Ihab

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Raw, unpasteurized milk can carry dangerous bacteria such as Salmonella, E. coli, and Listeria, which are responsible for causing numerous foodborne illnesses. The objective of this study was molecular characterization of shiga toxogenic E. coli in raw milk collected from different Egyptian governorates by multiplex PCR. During the period of 25th May to 25th October 2012, a total of 320 bulk-tank milk samples were collected from 10 cow farms located in different Egyptian governorates. Bacteriological examination of milk samples revealed the presence of E. coli organisms in 65 samples (20.3%), serotyping of the E. coli isolates revealed, 35 strains (10.94%) O111, 15 strains (4.69%) O157: H7, 10 strains (3.13%) O128 and 5 strains (1.56%) O119. Multiplex PCR for detection of shiga toxin type 2 and intimin genes revealed positive amplification of 255 bp fragment of shiga toxin type 2 gene and 384 bp fragment of intimin gene from all E. coli serovar O157: H7, while from serovar O111 were 25 (71.43%), 20 (57.14%) and from serovar O128 were 6 (60%), 8 (80%), respectively. The results of multiplex PCR assay are useful for identification of STEC possessing the eaeA and stx2 genes.

Keywords: raw milk, E. coli, multiplex PCR, Shiga toxin type 2, intimin gene

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Authors: T. Garba, T. O. Quddus, Y. Y. Babanyara, M. A. Modibbo

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Desertification is define as the changing of productive land into a desert as the result of ruination of land by man-induced soil erosion, which forces famers in the affected areas to move migrate or encourage into reserved areas in search of a fertile land for their farming activities. This study therefore used remote sensing imageries to determine the level of changes in the vegetative areas. To achieve that Normalized Difference of the Vegetative Index (NDVI), classified imageries and image slicing derived from landsat TM 1986, land sat ETM 1999 and Nigeria sat 1 2007 were used to determine changes in vegetations. From the Classified imageries it was discovered that there a more natural vegetation in classified images of 1986 than that of 1999 and 2007. This finding is also future in the three NDVI imageries, it was discovered that there is increased in high positive pixel value from 0.04 in 1986 to 0.22 in 1999 and to 0.32 in 2007. The figures in the three histogram also indicted that there is increased in vegetative areas from 29.15 Km2 in 1986, to 60.58 Km2 in 1999 and then to 109 Km2 in 2007. The study recommends among other things that there is need to restore natural vegetation through discouraging of farming activities in and around the natural vegetation in the study area.

Keywords: vegetative index, classified imageries, change detection, landsat, vegetation

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Authors: Mona Hamdy, Iman Shaheen, Hadeel Seif Eldin, Basma Ali, Omnia Abdeldayem

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Summary: Bone involvement of sickle cell disease (SCD) patients varies from acute clinical manifestations of painful vaso-occlusive crises or osteomyelitis to more chronic affection of bone mineral density (BMD) and debilitating osteonecrosis and osteoporosis. Secreted klotho protein is involved in calcium (Ca) reabsorption in the kidney. This study aimed to measure serum klotho levels in children with SCD to determine the possibility of using it as a marker of low BMD in children with SCD in correlation with a dual-energy radiograph absorptiometry scan. This study included 60 sickle disease patients and 30 age-matched and sex-matched control participants without SCD. A highly statistically significant difference was found between patients with normal BMD and those with low BMD, with serum Ca and klotho levels being lower in the latter group. Klotho serum level correlated positively with both serum Ca and BMD. Serum klotho level showed 94.9% sensitivity and 95.2% specificity in the detection of low BMD. Both serum Ca and klotho serum levels may be useful markers for detection of low BMD related to SCD with high sensitivity and specificity; however, klotho may be a better indicator as it is less affected by the nutritional and endocrinal status of patients or by intake of Ca supplements.

Keywords: sickle cell disease, BMD, osteoporosis, DEXA, klotho

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Authors: Ibrahim Musa, Guy Raffin, Marie Hangouet, Nadia Zine, Nicole Jaffrezic-Renault, Abdelhamid Errachid

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Due to its application in different domains, such as fuel cell configuration and adulteration of alcoholic beverages, a miniaturized sensor for methanol detection is urgently required. A conductometric microsensor for measuring volatile organic compounds (VOC) was conceived, based on electrospun composite nanofibers of polyvinyl chloride (PVC) doped with nickel phthalocyanine(NiPc) deposited on interdigitated electrodes (IDEs) used transducers. The nanofiber's shape, structure, percent atomic content and thermal properties were studied using analytical techniques, including scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), respectively. The methanol sensor showed good sensitivity (505µS/cm(v/v) ⁻¹), low LOD (15 ppm), short response time (13 s), and short recovery time (15 s). The sensor was 4 times more sensitive to methanol than to ethanol and 19 times more sensitive to methanol than to acetone. Furthermore, the sensor response was unaffected by the interfering water vapor, making it more suitable for VOC sensing in the presence of humidity. The sensor was applied for conductometric detection of methanol in rubbing alcohol.

Keywords: composite, methanol, conductometric sensor, electrospun, nanofiber, nickel phthalocyanine, PVC

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Authors: M. Amo, A. Alvaro, A. Astudillo, R. Mc Culloch, J. C. del Castillo, M. Gómez, J. M. Martín

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Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) of course comprise a range of highly toxic compounds that may exist as particulates within the air or accumulate within water supplies, soil, or vegetation. They may be created either ubiquitously or naturally within the environment as a product of forest fires or volcanic eruptions. It is only since the industrial revolution, however, that it has become necessary to closely monitor their generation as a byproduct of manufacturing/combustion processes, in an effort to mitigate widespread contamination events. Of course, the environmental concentrations of these toxins are expected to be extremely low, therefore highly sensitive and accurate methods are required for their determination. Since ionization of non-polar compounds through electrospray and APCI is difficult and inefficient, we evaluate the performance of a novel low-flow Atmospheric Pressure Photoionization (APPI) source for the trace detection of various dioxins and furans using rapid Mass Spectrometry workflows. Air, soil and biota (vegetable matter) samples were collected monthly during one year from various locations within the vicinity of an industrial incinerator in Spain. Analytes were extracted and concentrated using soxhlet extraction in toluene and concentrated by rotavapor and nitrogen flow. Various ionization methods as electrospray (ES) and atmospheric pressure chemical ionization (APCI) were evaluated, however, only the low-flow APPI source was capable of providing the necessary performance, in terms of sensitivity, required for detecting all targeted analytes. In total, 10 analytes including 2,3,7,8-tetrachlorodibenzodioxin (TCDD) were detected and characterized using the APPI-MS method. Both PCDDs and PCFDs were detected most efficiently in negative ionization mode. The most abundant ion always corresponded to the loss of a chlorine and addition of an oxygen, yielding [M-Cl+O]- ions. MRM methods were created in order to provide selectivity for each analyte. No chromatographic separation was employed; however, matrix effects were determined to have a negligible impact on analyte signals. Triple Quadrupole Mass Spectrometry was chosen because of its unique potential for high sensitivity and selectivity. The mass spectrometer used was a Sciex´s Qtrap3200 working in negative Multi Reacting Monitoring Mode (MRM). Typically mass detection limits were determined to be near the 1-pg level. The APPI-MS2 technology applied to the detection of PCDD/Fs allows fast and reliable atmospheric analysis, minimizing considerably operational times and costs, with respect other technologies available. In addition, the limit of detection can be easily improved using a more sensitive mass spectrometer since the background in the analysis channel is very low. The APPI developed by SEADM allows polar and non-polar compounds ionization with high efficiency and repeatability.

Keywords: atmospheric pressure photoionization-mass spectrometry (APPI-MS), dioxin, furan, incinerator

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Authors: Jamal R. Elbergali

Abstract:

Multiple Input Multiple Output (MIMO) systems are wireless systems with multiple antenna elements at both ends of the link. Wireless communication systems demand high data rate and spectral efficiency with increased reliability. MIMO systems have been popular techniques to achieve these goals because increased data rate is possible through spatial multiplexing scheme and diversity. Spatial Multiplexing (SM) is used to achieve higher possible throughput than diversity. In this paper, we propose a Zero-Forcing (ZF) detection using a combination of Ordered Successive Interference Cancellation (OSIC) and Zero Forcing using Interference Cancellation (ZF-IC). The proposed method used an OSIC based on Signal to Noise Ratio (SNR) ordering to get the estimation of last symbol (x ̃_(N_T )), then the estimated last symbol is considered to be an input to the ZF-IC. We analyze the Bit Error Rate (BER) performance of the proposed MIMO system over Rayleigh Fading Channel, using Binary Phase Shift Keying (BPSK) modulation scheme. The results show better performance than the previous methods.

Keywords: SNR, BER, BPSK, MIMO, modulation, zero forcing (ZF), OSIC, ZF-IC, spatial multiplexing (SM)

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Authors: Narayana Murthy Akurathi, Vijaya Lakshmi Marella

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The literature is reviewed with regard to online Super critical fluid extraction (SFE) coupled directly with supercritical fluid chromatography (SFC) -mass spectrometry that have typically more sensitive than conventional LC-MS/MS and GC-MS/MS. It is becoming increasingly interesting to use on-line techniques that combine sample preparation, separation and detection in one analytical set up. This provides less human intervention, uses small amount of sample and organic solvent and yields enhanced analyte enrichment in a shorter time. The sample extraction is performed under light shielding and anaerobic conditions, preventing the degradation of thermo labile analytes. It may be able to analyze compounds over a wide polarity range as SFC generally uses carbon dioxide which was collected as a by-product of other chemical reactions or is collected from the atmosphere as it contributes no new chemicals to the environment. The diffusion of solutes in supercritical fluids is about ten times greater than that in liquids and about three times less than in gases which results in a decrease in resistance to mass transfer in the column and allows for fast high resolution separations. The drawback of SFC when using carbon dioxide as mobile phase is that the direct introduction of water samples poses a series of problems, water must therefore be eliminated before it reaches the analytical column. Hundreds of compounds analysed simultaneously by simple enclosing in an extraction vessel. This is mainly applicable for pharmaceutical industry where it can analyse fatty acids and phospholipids that have many analogues as their UV spectrum is very similar, trace additives in polymers, cleaning validation can be conducted by putting swab sample in an extraction vessel, analysing hundreds of pesticides with good resolution.

Keywords: super critical fluid extraction (SFE), super critical fluid chromatography (SFC), LCMS/MS, GCMS/MS

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30dB SNR as a reference for voice activity.

Keywords: atomic decomposition, gabor, gammatone, matching pursuit, voice activity detection

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