Search results for: backbone

Authors: Mahdi Alkaeed, Adeel Ehsan

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Enterprise information systems (EIS) act as the backbone of organizations that belong to different domains. These systems not only play a major role in the efficient usage of resources and time but also throw light on the future roadmap for the enterprise. In today's rapidly expanding world of business and technology, enterprise systems from various heterogenous environments have to exchange information at some point, be it within the same organization or between different organizations. This reality strengthens the importance of interoperability between these systems, which is one of the key enablers of systems collaboration. Both information technology infrastructure and business processes have to be aligned with each other to achieve this effect. This will be difficult to attain if traditional tightly coupled architecture is used. Instead, a more loosely coupled service-oriented architecture has to be used. That would enable an effective interoperability level between different EIS. This paper discusses and presents the current work that has been done in the field of EIS interoperability. Along the way, it also discusses the challenges, solutions to tackle those challenges presented in the studied literature, and limitations, if any.

Keywords: enterprise systems interoperability, collaboration and integration, service-based architecture, open system architecture

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Authors: Massra M. Sabeima, Myriam lamolle, Mohamedade Farouk Nanne

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Adapting the learning resources of an e-learning system to the characteristics of the learners is an important aspect to consider when designing an adaptive e-learning system. However, this adaptation is not a simple process; it requires the extraction, analysis, and modeling of user information. This implies a good representation of the user's profile, which is the backbone of the adaptation process. Moreover, during the e-learning process, collaboration with similar users (same geographic province or knowledge context) is important. Productive collaboration motivates users to continue or not abandon the course and increases the assimilation of learning objects. The contribution of this work is the following: we propose an adaptive e-learning semantic platform to recommend learning resources to learners, using ontology to model the user profile and the course content, furthermore an implementation of a multi-agent system able to progressively generate the learning graph (taking into account the user's progress, and the changes that occur) for each user during the learning process, and to synchronize the users who collaborate on a learning object.

Keywords: adaptative learning, collaboration, multi-agent, ontology

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Authors: Esther Yemisi Akinjiola

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Mathematics has been regarded as the backbone of science and technological development, without which no nation can achieve any sustainable growth and development. Mathematics is a useful tool to simplify science by quantification of phenomena; hence physics and chemistry cannot be done without Calculus and Statistics. Mathematics is used in physical science to calculate the measurement of objects and their characteristics, as well as to show the relationship between different functions and properties. Mathematics is the building block for everything in our daily lives, including the use of mobile devices, architecture design, ancient arts, engineering sports, and. among others. Therefore the study of Mathematics is made compulsory at primary, basic, and secondary school levels. Thus, this paper discusses the concepts of Mathematics, science, and their relationships. Also, it discusses Mathematics contents needed to study science-oriented courses such as physics education, chemistry education, and biology education in the tertiary institution. The paper concluded that without adequate knowledge of Mathematics, it will be difficult, if not impossible, for science education students to cope in their field of study.

Keywords: mathematical knowledge, prerequisite, science education, tertiary institution

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Somayyeh Kalami, Mojgan Nejad

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Based on the source (softwood, hardwood or annual crop) and isolation method (kraft, organosolv, sulfite or pre-enzymatic treatment), there are significant variations in lignin structure and properties. The first step in using lignin as biobased feedstock is to make sure that specific lignin is suitable for intended application. Complete characterization of lignin and measuring its chemical, physical and thermal properties can help to predict its suitability. To replace 100% phenol portion of phenolic adhesive, lignin should have high reactivity toward formaldehyde. Theoretically, lignins with closer backbone structure to phenol should be better candidate for this application. In this study, a number of different lignins were characterized and used to formulate phenolic adhesive. One of the main findings was that lignin sample with higher percentage of hydroxyl-phenyl units was better candidate than lignin with more syringyl units. This could be explained by the fact that hydroxyl-phenyl lignin units have two available ortho positions for reaction with formaldehyde while in syringyl units all ortho and para positions are occupied, and there is no available site in lignin structure to react with formaldehyde.

Keywords: lignin, phenolic adhesive, biobased, sustainable

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Authors: Min-Hwa Lim, Mi-Jeong Park, Ho-Young Jung

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Imidazolium-brominated polyphenylene oxide (Im-bPPO) is based on the functionalization of bromomethylated poly(2,6-dimethyl-1,4-phenylene oxide) (BPPO) using 1-Methylimdazole. For the purpose of long cycle life of vanadium redox battery (VRB), the chemical stability of Im-bPPO, sPPO (sulfonated 2,6-dimethyl-1,4-phenylene oxide) and Fumatech membranes were evaluated firstly in the 0.1M vanadium (V) solution dissolved in 3M sulfuric acid (H2SO4) for 72h, and UV analyses of the degradation products proved that ether bond in PPO backbone was vulnerable to be attacked by vanadium (V) ion. It was found that the membranes had slightly weight loss after soaking in 2 ml distilled water included in STS pressure vessel for 1 day at 200◦C. ATR-FT-IR data indicated before and after the degradation of the membranes. Further evaluation on the degradation mechanism of the menbranes were carried out in Fenton’s reagent solution for 72 h at 50 ◦C and analyses of the membranes before and after degradation confirmed the weight loss of the membranes. The Fumatech membranes exhibited better performance than AEM and CEM, but Nafion 212 still suffers chemical degradation.

Keywords: vanadium redox flow battery, ion exchange membrane, permeability, degradation, chemical stability

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Authors: Ma Lei-Lei, Zhou You

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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

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Authors: Rajeshwari Madli, Santhosh Hebbar, Vishwanath Heddoori, G. V. Prasad

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Agriculture is the major occupation in India and forms the backbone of Indian economy in which irrigation plays a crucial role for increasing the quality and quantity of crop yield. In spite of many revolutionary advancements in agriculture, there has not been a dramatic increase in agricultural performance. Lack of irrigation infrastructure and agricultural knowledge are the critical factors influencing agricultural performance. However, by using advanced agricultural equipment, the effect of these factors can be curtailed.  The presented system aims at increasing the yield of crops by using an intelligent irrigation controller that makes use of wireless sensors. Sensors are used to monitor primary parameters such as soil moisture, soil pH, temperature and humidity. Irrigation decisions are taken based on the sensed data and the type of crop being grown. The system provides a mobile application in which farmers can remotely monitor and control the irrigation system. Also, the water pump is protected against damages due to voltage variations and dry running.

Keywords: android application, Bluetooth, wireless sensors, irrigation, temperature, soil pH

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Authors: Christy Rosaline, Rathankar Roa, Waheeta Hopper

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Persistence of tuberculosis, emergence of multidrug-resistance and extensively drug-resistant forms of the disease, has increased the interest in developing new antitubercular drugs. Developing inhibitors for 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase from Mycobacterium tuberculosis (MtbDAH7Ps), an enzyme involved in shikimate pathway, gives a selective target for antitubercular agents. MtbDAH7Ps was screened against ZINC database, and shortlisted compounds were subjected to induce fit docking. Prime/Molecular Mechanics Generalized Born Surface Area calculation was used to validate the binding energy of ligand-protein complex. Molecular Dynamics analysis for of the lead compounds–MtbDAH7Ps complexes showed that the backbone of MtbDAH7Ps in their complexes were stable. These results suggest that the shortlisted lead compounds ZINC04097114, ZINC15163225, ZINC16857013, ZINC06275603, and ZINC05331260 could be developed into novel drug leads to inhibit DAH7Ps in Mycobacterium tuberculosis.

Keywords: MtbDAH7Ps, Mycobacterium tuberculosis, HTVS, molecular dynamics

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Authors: Bendjelloul Meriem, Elandaloussi El Hadj

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In this work, we studied the effectiveness of a lignocellulosic waste (wood sawdust) for the removal of cadmium Cd (II) in aqueous solution. The adsorbent material SBO-CH2-CO2Na has been prepared by alkaline pretreatment of wood sawdust followed by a chemical modification with sodium salt of chloroacetic acid. The characterization of the as-prepared material by FTIR has proven that the grafting of acetate spacer took actually place in the lignocellulosic backbone by the appearance of characteristic band of carboxylic groups in the IR spectrum. The removal study of Cd2+ by SBO-CH2-CO2Na material at the solid-liquid interface was carried out by kinetics, sorption isotherms, effect of temperature and thermodynamic parameters were evaluated. The last part of this work was dedicated to assess the regenerability of the adsorbent material after three reuse cycles. The results indicate that SBO-CH2-CO2Na matrix possesses a high effectiveness in removing Cd (II) with an adsorption capacity of 222.22 mg/g, yet a better value that those of many low-cost adsorbents so far reported in the literature. The results found in the course of this study suggest that ionic exchange is the most appropriate mechanism involved in the removal of cadmium ions.

Keywords: adsorption, cadmium, isotherms, lignocellulosic, regenerability

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Authors: Onyeka Nkwonta, Theo Haupt, Karana Padayachee

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This study aims primarily to identify potential causes of the bottlenecks in the public sector that affect delivery and formulate evidence-based interventions to improve delivery and management of infrastructure projects. An initial literature review was carried out on infrastructural development and delivery in South Africa, with the aim to formulate evidence-based interventions to improve delivery within the sector. The infrastructure delivery management model was developed to map out best practice delivery processes. These will become the backbone on which improvement initiatives that will be developed within participating stakeholders. The model will, in turn, support a range of methodologies, including the risk system and a knowledge management framework. It will also look at key challenges facing departments with the ability to ensure knowledge and skills transfer at various sectors. The research is limited because the findings were based on existing literature. This study adopted an indirect approach for infrastructure management by focussing on the challenges faced and approaches adopted to overcome these challenges. This may narrow the consideration of some of the viewpoints, thereby limiting the richness of experience available to this research.

Keywords: infrastructure, management, challenges, South Africa

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Authors: Oladapo Tolulope Ibitoye

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Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

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Authors: Ali Jamshidi, Kiyofumi Kurumisawa, Toyoharu Nawa

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Transportation infrastructure assets can be considered as backbone of transportation system. They are routinely developed and or maintained which can be used effectively for movement of passengers, commodities and providing vital services. However, the infrastructure assets construction, maintenance and rehabilitation significantly depend on non-renewable natural resources, such as carbon-based energy carriers and aggregate materials. In this study, effects of thermal properties of aggregate materials were characterized for production of hot-mix asphalt in Japan, as a case study. The results indicated that incorporation of the aggregate with lower required heat energy significantly reduces fuel consumption greenhouse gas emission, irrespective of physical property of aggregate. The results also clearly showed that as 75% high-energy limestone is replaced with low-energy limestone in producing an asphalt mixture at 180 °C, 97,879 Japanese households would be energized per annum using the saved energy without any modification in the current asphalt mixing plants.

Keywords: zero energy infrastructure, sustainable development, greenhouse gas emission, asphalt pavement

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Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

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Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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Authors: Samiul Islam Hazarika, Domngam Boje, Ananta Kumar Atta

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It is well familiar that solvents play a significant role in modern chemistry. Solvents can change the reactivity and physicochemical properties of molecules in a solution. Keeping this in mind, we have designed and synthesized a mono-triazolyl-linked pyrenyl-appended xylofuranose derivative for the detection of metal ions with changing solvent systems. The incorporation of a sugar backbone in the sensor increases the water solubility and biocompatibility. The experimental study revealed that the xylofuranose-based fluorescence probe did not exhibit any specific selectivity towards metal ions in acetonitrile (CH₃CN) solvent. Whereas, we revealed that triazole-linked pyrenyl-appended xylofuranose-based fluorescent sensor would exhibit high selectivity and sensitivity towards Au³⁺ ions in CH₃CN-H₂O (1/1, v/v) system. This observation might be explained by the viscosity and polarity differences of CH₃CN and CH₃CN-H₂O solvent systems. The formation of the sensor-Au³⁺ complex was also established by high-resolution mass spectrometry (HRMS) data of the complex.

Keywords: triazole, furanose, fluorometric, solvent dependent

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Authors: Van Tran Thi Thuy, Cheol Won Lim, Dukjoon Kim

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A series of biodegradable copolymers based on polyaspartamide (PASPAM) were synthesized by grafting hydrophilic O-(2-aminoethyl)-O'-methylpoly(ethylene glycol) (MPEG), hydrophobic cholic acid (CA), and pH-sensitive hydrazine (Hyd) segments on a PASPAM backbone. The hydrazine group was effectively cleaved to release doxorubicin (DOX) conjugated on PASPAM in an acidic environment. The chemical structure of the polymer and the degree of substitution of each graft segment were analyzed using FT-IR and 1H-NMR spectroscopy. The size of the MPEG/Hyd/CA-g-PASPAM copolymer self-aggregates was examined by dynamic light scattering (DLS) and transmission electron microscope (TEM). The mean diameter of the self - aggregates increased from 125 to 200 nm at pH 7.4, as the degree of substitution of CA increased from 10 to 20 %. The release kinetics of DOX was strongly affected by the pH of the releasing medium. While less than 30% of the DOX-loaded was released in about 30 h at pH 7.4, more than 60% was released at pH 5.0 within the same time. The viability tests of human breast cancer cells (MCF-7) and human embryonic kidney cells (293T) show the potential application of MPEG/Hyd/CA-g-PASPAM copolymer self-aggregates in the controlled intracellular delivery for cancer treatments.

Keywords: pH-sensitive, drug delivery, polyaspartamide, self-assembly, nano-aggregates

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Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: Isam M. Arafa, Mazin Y. Shatnawi, Yaser A. Yousef, Batool Zaid Al-Momani

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The present work describes the preparation, characterization, and luminescence of a series of fluorenone (FL) based luminophores grafted onto modified cellulose microfibers. The FL is condensed onto cellulose aldehyde using three diamine spacers (H₂N-NH₂, H₂N(CH₂)₂NH₂ and H₂N(CH₂)₃NH₂) to afford Cell=Spacer=FL. The obtained products were characterized by spectroscopic (FT-IR, UV–Vis), thermal gravimetric analysis (TGA), and microscopic (Optical, SEM) techniques. The UV-Vis spectra of the FL=N(CH₂)ₓNH₂ (x = 0, 2, 3) moieties show that they are transparent in the 375- 800 nm region while they exhibit intense absorption band below 350 nm attributed to n-π* and π-π* transitions. The solid-state photoluminescence (PLs-s) of the cold-pressed pellets of the FL=N(CH₂)ₓNH₂ and Cell=Spacer=FL placed in a quartz cuvette show strong emission in the 500-550 nm region upon irradiation with Xe lamp light (λex = 320 nm). The PLs-s green emission of the grafted Cell=Spacer=FL was evaluated relative to that of the FL-based precursor. These grafted conjugated products have the potential to be used as analyte sensors for typical nitroaromatics/aromatic amines and be further extended to immunoassay studies for aromatic amino acids such as phenylalanine and histidine.

Keywords: luminescence, cellulose, fluorenone, grafting, solid state

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Authors: Alexander Kelisek, Stanislava Strelcova

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Developing of business in small and medium-sized enterprises (SMEs) is a specific especially for its flexibility and rapid adaptation to the conditions of turbulent market environment compared to large enterprises. Therefore, an importance of SMEs is growing rapidly in Slovakia but also in other EU countries. Small and medium enterprises are characterized by transparent organizational structure, as it allows the realization of direct management and information flow without significant negative aspects. In the national economy small and medium-sized enterprises represent a significant potential when performs a several important functions (e.g. social, economic, export-import, etc.) The significance of these enterprises is not only at national, but also at transnational level. Importance of SMEs is also aware of the EU, which declared this statement in a key document for SMEs called Small Business Act. In this document, SMEs are characterized, as the backbone of the EU economy and also as a key source of jobs opportunities. In addition to these aspects, SMEs attaches high innovation and development potential. The authors of the article are dealing with the current status of SMEs development in the Slovak Republic and highlight the current challenges that entrepreneurs face in their small and medium enterprises.

Keywords: small and medium enterprises (SMEs), business support, SMEs development, SMEs funding

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Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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Rivers are the backbone of human civilization as well as one of the most important components of nature. In this paper, a method for predicting lateral depth-averaged velocity distribution in a two-flow braided compound channel is proposed. Experiments were conducted to study the boundary shear stress in the tip of the two flow path. The cross-section of the channel is divided into several panels to study the flow phenomenon on both the main channel and the flood plain. It can be inferred from the study that the flow coefficients get affected by boundary shear stress. In this study, the analytical solution of Shiono and knight (SKM) for lateral distributions of depth-averaged velocity and bed shear stress has been taken into account. The SKM is based on hydraulic parameters, which signify the bed friction factor (f), lateral eddy viscosity, and depth-averaged flow. While applying the SKM to different panels, the equations are solved considering the boundary conditions between panels. The boundary shear stress data, which are obtained from experimentation, are compared with CES software, which is based on quasi-one-dimensional Reynold's Averaged Navier-Stokes (RANS) approach.

Keywords: boundary shear stress, lateral depth-averaged velocity, two-flow braided compound channel, velocity distribution

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Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: Amarjyoti Das Mahapatra, Umesh Kumar, Bhaskar Datta

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A pseudo peptide can mimic the biological or structural properties of natural peptides. They have become an increasing attention in medicinal chemistry because of their interesting advantages like more bioavailability and less biodegradation than compare to the physiologically active native peptides which increase their therapeutic applications. Many biologically active compounds contain urea as functional groups, and they have improved pharmacokinetic properties because of their bioavailability and metabolic stability. Recently we have reported a single-step synthesis of sulfonyl urea and sulfonyltriuret from sulfonyl chloride and sodium cyanate. But the yield of sulfonyltriuret was less around 40-60% because of the formation of other products like sulfonamide and sulfonylureas. In the present work, we mainly focused on the selective synthesis of sulfonyltriuret using tetrabutylammonium cyanate and sulfonyl chloride. More precisely, we are interested in the controlled synthesis of oligomeric urea mainly sulfonyltriuret as a new class of pseudo peptide and their application as protease modulators. The distinctive architecture of these molecules in the form of their pseudo-peptide backbone offers promise as a potential pharmacophore. The synthesized molecules have been screened on trypsin enzyme, and we observed that these molecules are the efficient modulator of trypsin enzyme.

Keywords: pseudo peptide, pharmacophore, sulfonyltriuret, trypsin

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Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Lawrence Mzukisi Madikizela, Luke Chimuka

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Removal of organics from wastewater offers a better water quality, therefore, the purpose of this work was to investigate the use of molecularly imprinted polymer (MIP) for the elimination of selected organics from water. A multi-template MIP for the adsorption of naproxen, ibuprofen and diclofenac was synthesized using a bulk polymerization method. A MIP was synthesized at 70°C by employing 2-vinylpyridine, ethylene glycol dimethacrylate, toluene and 1,1’-azobis-(cyclohexanecarbonitrile) as functional monomer, cross-linker, porogen and initiator, respectively. Thermogravimetric characterization indicated that the polymer backbone collapses at 250°C and scanning electron microscopy revealed the porous and roughness nature of the MIP after elution of templates. The performance of the MIP in aqueous solutions was evaluated by optimizing several adsorption parameters. The optimized adsorption conditions were 50 mg of MIP, extraction time of 10 min, a sample pH of 4.6 and the initial concentration of 30 mg/L. The imprinting factors obtained for naproxen, ibuprofen and diclofenac were 1.25, 1.42, and 2.01, respectively. The order of selectivity for the MIP was; diclofenac > ibuprofen > naproxen. MIP showed great swelling in water with an initial swelling rate of 2.62 g/(g min). The synthesized MIP proved to be able to adsorb naproxen, ibuprofen and diclofenac from contaminated deionized water, wastewater influent and effluent.

Keywords: adsorption, molecularly imprinted polymer, multi template, pharmaceuticals

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Authors: Todor Bačkalić, Marinko Maslarić, Milosav Georgijević, Sanja Bojić

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Water transport could be the backbone of the future European combined transport system. The future transport policy in landlocked countries from the Danube Region has to be based on inland waterway transport (IWT). The development of the container transport on inland waterways depends directly on technical-exploitative characteristics of the network of inland waterways. Research of navigational abilities of inland waterways is the basic step in transport planning. The size of the vessel’s draught (T) is the limiting value in project tasks and it depends on the depth of the waterway. Navigation characteristics of rivers have to be determined as precise as possible, especially from the aspect of determination of the possible draught of vessels. This article outlines a rationale, why it is necessary to develop competence about infrastructure risk in water transport. Climate changes are evident and require special attention and global monitoring. Current risk assessment methods for Inland waterway transport just consider some dramatic events. We present a new method for the assessment of risk and vulnerability of inland waterway transport where river depth represents a crucial part. The analysis of water level changes in the lower Danube was done for two significant periods (1965-1979 and 1998-2012).

Keywords: container vessel, draught, probability, the Danube

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Somayeh Sadat Hashemi Kamangar, Fatemeh Bakouie, Shahriar Gharibzadeh

Abstract:

In this study, we target to exploit Maximum Spanning Trees (MST) of children's semantic networks to investigate their language development. To do so, we examine the graph-theoretic properties of word-embedding networks. The networks are made of words children learn prior to the age of 30 months as the nodes and the links which are built from the cosine vector similarity of words normatively acquired by children prior to two and a half years of age. These networks are weighted graphs and the strength of each link is determined by the numerical similarities of the two words (nodes) on the sides of the link. To avoid changing the weighted networks to the binaries by setting a threshold, constructing MSTs might present a solution. MST is a unique sub-graph that connects all the nodes in such a way that the sum of all the link weights is maximized without forming cycles. MSTs as the backbone of the semantic networks are suitable to examine developmental changes in semantic network topology in children. From these trees, several parameters were calculated to characterize the developmental change in network organization. We showed that MSTs provides an elegant method sensitive to capture subtle developmental changes in semantic network organization.

Keywords: maximum spanning trees, word-embedding, semantic networks, language development

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Authors: Ismail Sualman, Mohd Khairuddin Othman

Abstract:

General Election has been the backbone of democracy that permits people to choose their representatives as they deem fit. The support preferences of the voter differ from one to another, particularly in a plural society like Malaysia. The turning up of high numbers of young voters during the Malaysia 14th General Election has been said to have been caused by social media including Facebook, Twitter, WhatsApp, Instagram, YouTube and Telegram, WeChat and SMS/MMs. It has been observed that, besides using social media as an interaction tool among social friends, it is also an important source of information to know about issues, politics and politicians. This paper exhibits the role of social media in providing political information to young voters, before an election and during the election campaign. This study examines how this information is being translated into election support. A total of 799 Malay young respondents in Selangor have been surveyed and interviewed. This study revealed that social media has become the source of political information among Malay young voters. This research suggested that social media had a significant effect on the support during the election. Social media plays an important role in carrying information such as current issues, voting trends, candidate imagery and matters that may influence the view of young voters. The information obtained from social media has been translated into a voting decision.

Keywords: social media, political behaviour, voters’ choice, election.

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Authors: Muhammad Umar

Abstract:

Safety and Assets management is considering a backbone of every department. GIS in the Railway become very important to Manage Assets and Security through Digital Maps and Web based GIS Maps. It provides a complete frame of work to the organization for the management of assets. Pakistan Railway is the most common and safest mode of traveling in Pakistan. Due to ever-increasing demand of transporting huge amount of information generated from various sources and this information must be accurate. This creates problems for Passengers and Administration that causes finical and time loss. GIS Solve this problem by Digital Maps & Database. It provides you a real time Spatial and Statistical analysis that helps you to communicate and exchange the information in a sophisticated way to the users. GIS Based Web system provides a facility to different end user to make query at a time as per requirements. This GIS System provides an advancement in an organization for a complete Monitoring, Safety and Decision System for tracks, Stations and Junctions that further use for the Analysis of different areas i.e. analysis of tracks, junctions and Stations in case of reconstruction, Rescue for rail accidents and Natural disasters .This Research work helps to reduce the financial loss and reduce human mistakes helps you provide a complete security and Management system of assets.

Keywords: Geographical Information System (GIS) for assets management, geo spatial database, railway assets management, Pakistan

Procedia PDF Downloads 493