Search results for: real number sequences

Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

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Authors: Deepanjali Gurav, Kun Qian

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In-vitro metabolic diagnosis relies on designed materials-based analytical platforms for detection of selected metabolites in biological samples, which has a key role in disease detection and therapeutic evaluation in clinics. However, the basic challenge deals with developing a simple approach for metabolic analysis in bio-samples with high sample complexity and low molecular abundance. In this work, we report a designer plasmonic nanoshells based platform for direct detection of small metabolites in clinical samples for in-vitro metabolic diagnostics. We first synthesized a series of plasmonic core-shell particles with tunable nanoshell structures. The optimized plasmonic nanoshells as new matrices allowed fast, multiplex, sensitive, and selective LDI MS (Laser desorption/ionization mass spectrometry) detection of small metabolites in 0.5 μL of bio-fluids without enrichment or purification. Furthermore, coupling with isotopic quantification of selected metabolites, we demonstrated the use of these plasmonic nanoshells for disease detection and therapeutic evaluation in clinics. For disease detection, we identified patients with postoperative brain infection through glucose quantitation and daily monitoring by cerebrospinal fluid (CSF) analysis. For therapeutic evaluation, we investigated drug distribution in blood and CSF systems and validated the function and permeability of blood-brain/CSF-barriers, during therapeutic treatment of patients with cerebral edema for pharmacokinetic study. Our work sheds light on the design of materials for high-performance metabolic analysis and precision diagnostics in real cases.

Keywords: plasmonic nanoparticles, metabolites, fingerprinting, mass spectrometry, in-vitro diagnostics

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Authors: Babak Moradi, Hassan Zare-Maivan

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A greenhouse investigation has been conducted to study the effect of crude oil on morphology and protein content of Avicennia marina plant. Avicennia marina seeds were sown in different concentrations of the crude oil mixed soil (i.e., 2.5, 5, 7.5, and 10 w/w). Controls and replicates were also set up. Morphological traits were recorded 4 months after plantation. Avicennia marina seedlings could tolerate up to 10% (w/w). Results demonstrated that there was a reduction in plant shoot and root biomass with the increase of crude oil concentration. Plant height, total leaf number and length reduced significantly with increase of crude oil contamination. Investigation revealed that there is a great impact of crude oil contamination on protein content of the roots of the experimental plant. Protein content of roots grown in different concentrations of crude oil were more than those of the control plant. Further, results also showed that protein content was increased with increased concentration of crude oil.

Keywords: Avicennia marina, morphology, oil contamination, protein content

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Authors: Mahmoud M. Zakaria, Omnia F. Elmoursi, Mahmoud M. Gabr, Camelia A. AbdelMalak, Mohamed A. Ghoneim

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Many protocols were publicized for differentiation of human mesenchymal stem cells (MSCS) into insulin-producing cells (IPCs) in order to excrete insulin hormone ingoing to treat diabetes disease. Our aim is to evaluate relative gene expression for each independent protocol. Human bone marrow cells were derived from three volunteers that suffer diabetes disease. After expansion of mesenchymal stem cells, differentiation of these cells was done by three different protocols (the one-step protocol was used conophylline protein, the two steps protocol was depending on trichostatin-A, and the three-step protocol was started by beta-mercaptoethanol). Evaluation of gene expression was carried out by real-time PCR: Pancreatic endocrine genes, transcription factors, glucose transporter, precursor markers, pancreatic enzymes, proteolytic cleavage, extracellular matrix and cell surface protein. Quantitation of insulin secretion was detected by immunofluorescence technique in 24-well plate. Most of the genes studied were up-regulated in the in vitro differentiated cells, and also insulin production was observed in the three independent protocols. There were some slight increases in expression of endocrine mRNA of two-step protocol and its insulin production. So, the two-step protocol was showed a more efficient in expressing of pancreatic endocrine genes and its insulin production than the other two protocols.

Keywords: mesenchymal stem cells, insulin producing cells, conophylline protein, trichostatin-A, beta-mercaptoethanol, gene expression, immunofluorescence technique

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Authors: Mark Berry

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A number of studies have identified several factors involved in the malignant progression of cancer cells. The Primary modulator in driving inflammation to these transformed cells has been identified as the transcription factor known as nuclear factor-κB. This essential regulator of inflammation and the development of cancer, combined with a microenvironment of inflammation and signaling molecules, plays a major role in the malignant progression of cancer, and this progression is the result of the mutagenic predisposition of persistent substances that combat infection at tumor sites and other areas of chronic inflammation. Inflammation-induced tumors, and their inflammatory cells and regulators may be the primary source of metastasis of tumor cells through angiogenesis. Previous research on cytokines and chemokines, including their downstream targets, has been the focus of the cancer/inflammation connection. The identification of the biological mechanisms of other proteins vital to the inflammation cascade and their interactions are crucial to novel and effective therapeutic protocols for the treatment of inflammation-induced cancers. The Ancelim HSRP Protocol is just such a therapeutic intervention.

Keywords: ancelim, cancer, inflammation, tumor

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Authors: Abdellah Hanafi, G. M. Mostafa, Mohamed Mortada, Ahmed Hamed

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The steam ejectors are the heart of most of the desalination systems that employ vacuum. The systems that employ low grade thermal energy sources like solar energy and geothermal energy use the ejector to drive the system instead of high grade electric energy. The jet-ejector is used to create vacuum employing the flow of steam or air and using the severe pressure drop at the outlet of the main nozzle. The present work involves developing a one dimensional mathematical model for designing jet-ejectors and transform it into computer code using Engineering Equation solver (EES) software. The model receives the required operating conditions at the inlets and outlet of the ejector as inputs and produces the corresponding dimensions required to reach these conditions. The one-dimensional model has been validated using an existed model working on Abu-Qir power station. A prototype has been designed according to the one-dimensional model and attached to a special test bench to be tested before using it in the solar desalination pilot plant. The tested ejector will be responsible for the startup evacuation of the system and adjusting the vacuum of the evaporating effects. The tested prototype has shown a good agreement with the results of the code. In addition a numerical analysis has been applied on one of the designed geometry to give an image of the pressure and velocity distribution inside the ejector from a side, and from other side, to show the difference in results between the two-dimensional ideal gas model and real prototype. The commercial edition of ANSYS Fluent v.14 software is used to solve the two-dimensional axisymmetric case.

Keywords: solar energy, jet ejector, vacuum, evaporating effects

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Authors: Mohamad H. Atyeh, Ahmad Khaldi

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The main objective of this research is to measure the relationship between the Kuwait stock Exchange (KSE) index and its two marketing sectors after the new market classification. The findings of this research are important for Public economic policy makers as they need to know if the new system (new classification) is efficient and to what level, to monitor the markets and intervene with appropriate measures. The data used are the daily index of the whole Kuwaiti market and the daily closing price, number of deals and volume of shares traded of two marketing sectors (consumer goods and consumer services) for the period from the 13th of May 2012 till the 12th of December 2016. The results indicate a positive direct impact of the closing price, volume and deals indexes of the consumer goods and the consumer services companies on the overall KSE index, volume and deals of the Kuwaiti stock market (KSE).

Keywords: correlation, market capitalization, Kuwait Stock Exchange (KSE), marketing sectors, stock performance

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Authors: Aline Valverde Arroteia, Tatiana Gondim do Amaral, Silvio Burrattino Melhado

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During the last twenty years, the construction field in Brazil has evolved significantly in response to its market growing and competitiveness. However, this evolving path has faced many obstacles such as cultural barriers and the lack of efforts to achieve quality at the construction site. At the same time, the greatest amount of information generated on the designing or construction phases is lost due to the lack of an effective coordination of these activities. Face this problem, the aim of this research was to implement a French method named PEO which means preparation for building construction (in Portuguese) seeking to understand the design management process and its interface with the building construction phase. The research method applied was qualitative, and it was carried out through two case studies in the city of Goiania, in Goias, Brazil. The research was divided into two stages called pilot study at Company A and implementation of PEO at Company B. After the implementation; the results demonstrated the PEO method's effectiveness and feasibility while a booster on the quality improvement of design management. The analysis showed that the method has a purpose to improve the design and allow the reduction of failures, errors and rework commonly found in the production of buildings. Therefore, it can be concluded that the PEO is feasible to be applied to real estate and building companies. But, companies need to believe in the contribution they can make to the discovery of design failures in conjunction with other stakeholders forming a construction team. The result of PEO can be maximized when adopting the principles of simultaneous engineering and insertion of new computer technologies, which use a three-dimensional model of the building with BIM process.

Keywords: communication, design and construction interface management, preparation for building construction (PEO), proactive coordination (CPA)

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Authors: Abderrahmane Khiat, Moussa Benaissa

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Due to the increasing number of sources of information available on the web and their distribution and heterogeneity, ontology alignment became a very important and inevitable problem to ensure semantic interoperability. Instance-based ontology alignment is based on the comparison of the extensions of concepts; and represents a very promising technique to find semantic correspondences between entities of different ontologies. In practice, two situations may arise: ontologies that share many common instances and ontologies that share few or do not share common instances. In this paper, we describe an approach to manage the latter case. This approach exploits the reasoning on ontologies in order to create a corpus of common instances. We show that it is theoretically powerful because it is based on description logics and very useful in practice. We present the experimental results obtained by running our approach on ontologies of OAEI 2012 benchmark test. The results show the performance of our approach.

Keywords: description logic inference, instance-based ontology alignment, semantic interoperability, semantic web

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Authors: Mark Edward S. Paulo

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This study was conducted to determine the extent of constructivist learning in science classes of the college department of Southville International School and Colleges. This explores the students’ assessment of their learning when professors would give lecture and various activities in the classroom and at the same time their perception on how their professors maintain a constructivist learning environment. In this study, a total of 185 students participated. These students were enrolled in Science courses offered in the first semester of AY 2014 to 2015. Descriptive correlational method was used in this study while simple random sampling technique was utilized in getting the number of target population. The results revealed that student often observed that their professors apply constructivist approach when teaching sciences. A positive correlation was found between students’ level of learning and extent of constructivism.

Keywords: college teaching, constructivism, pedagogy, student-centered approach

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Authors: Qiang Fu, Abu Saleh

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Research studies are highly fragmented when an innovation management framework is being discussed. With the aim to identify an innovation management framework/assessment tool suitable for small & medium enterprises (SMEs) in the service industry, this researcher critically reviewed existing innovation management frameworks and assessment models/tools and discovered a number of literature gaps. It is established that existing literature lacks generally agreed innovation management dimensions, commonly accepted knowledge creation through empirical studies on innovation management in SMEs, effective innovation management performance measurements, and studies on innovation management in the service industry, in particular in retail SMEs. As such, there is a dire need to develop an appropriate firm-level innovation management framework suitable for SMEs in the service industry for a future research project and further study. In addition, this researcher also discussed the significance of establishing such an innovation management framework.

Keywords: innovation management, innovation management framework, innovation management assessment tools, SMEs, service industry

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Authors: Ishani Majumdar, Jaishree Paul

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Introduction: Ulcerative Colitis (UC) is an inflammatory disease of the colon resulting from an autoimmune response towards individual’s own microbiota. Excessive inflammation is characterized by hyper-activation of NFkB, a transcription factor regulating expression of various pro-inflammatory genes. The ubiquitin editing complex consisting of TNFAIP3, ITCH, RNF11 and TAX1BP1 maintains homeostatic levels of active NFkB through feedback inhibition and assembles in response to various stimuli that activate NFkB. TNFAIP3 deubiquitinates key signaling molecules involved in NFkB activation pathway. ITCH, RNF11 and TAX1BP1 provide substrate specificity, acting as adaptors for TNFAIP3 function. Aim: This study aimed to find expression of members of the ubiquitin editing complex at the transcript level in inflamed colon tissues of UC patients. Materials and Methods: Colonic biopsy samples were collected from 30 UC patients recruited at Department of Gastroenterology, AIIMS (New Delhi). Control group (n= 10) consisted of individuals undergoing examination for functional disorders. Real Time PCR was used to determine relative expression with GAPDH as housekeeping gene. Results: Expression of members of the ubiquitin editing complex was significantly altered during active disease. Expression of TNFAIP3 was upregulated while concomitant decrease in expression of ITCH, RNF11, TAX1BP1 was seen in UC patients. Discussion: This study reveals that increase in expression of TNFAIP3 was unable to control inflammation during active UC. Further, insufficient upregulation of ITCH, RNF11, TAX1BP1 may limit the formation of the ubiquitin complex and contribute to pathogenesis of UC.

Keywords: altered expression, inflammation, ubiquitin editing complex, ulcerative colitis

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Authors: Nadjiba Mahfoudi, Abdelhafid Moummi , Mohammed El Ganaoui

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Thermal applications are drawing increasing attention in the solar energy research field, due to their high performance in energy storage density and energy conversion efficiency. In these applications, solar collectors and thermal energy storage systems are the two core components. This paper presents a thermal analysis of the transient behavior and storage capability of a sensible heat storage device in which sand is used as a storage media. The TES unit with embedded charging tubes is connected to a solar air collector. To investigate it storage characteristics a 3D-model using no linear coupled partial differential equations for both temperature of storage medium and heat transfer fluid (HTF), has been developed. Performances of thermal storage bed of capacity of 17 MJ (including bed temperature, charging time, energy storage rate, charging energy efficiency) have been evaluated. The effect of the number of charging tubes (3 configurations) is presented.

Keywords: design, thermal modeling, heat transfer enhancement, sand, sensible heat storage

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Authors: Kanika Taneja, V. K. Soni, Kafeel Ahmad, Shamshad Ahmad

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A severe dust storm generated from a western disturbance over north Pakistan and adjoining Afghanistan affected the north-west region of India between May 28 and 31, 2014, resulting in significant reductions in air quality and visibility. The air quality of the affected region degraded drastically. PM10 concentration peaked at a very high value of around 1018 μgm-3 during dust storm hours of May 30, 2014 at New Delhi. The present study depicts aerosol optical properties monitored during the dust days using ground based multi-wavelength Sky radiometer over the National Capital Region of India. High Aerosol Optical Depth (AOD) at 500 nm was observed as 1.356 ± 0.19 at New Delhi while Angstrom exponent (Alpha) dropped to 0.287 on May 30, 2014. The variation in the Single Scattering Albedo (SSA) and real n(λ) and imaginary k(λ) parts of the refractive index indicated that the dust event influences the optical state to be more absorbing. The single scattering albedo, refractive index, volume size distribution and asymmetry parameter (ASY) values suggested that dust aerosols were predominant over the anthropogenic aerosols in the urban environment of New Delhi. The large reduction in the radiative flux at the surface level caused significant cooling at the surface. Direct Aerosol Radiative Forcing (DARF) was calculated using a radiative transfer model during the dust period. A consistent increase in surface cooling was evident, ranging from -31 Wm-2 to -82 Wm-2 and an increase in heating of the atmosphere from 15 Wm-2 to 92 Wm-2 and -2 Wm-2 to 10 Wm-2 at top of the atmosphere.

Keywords: aerosol optical properties, dust storm, radiative transfer model, sky radiometer

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Authors: Matevž Breška, Iztok Peruš, Vlado Stankovski

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Systematic overview of existing Ground Motion Prediction Equations (GMPEs) has been published by Douglas. The number of earthquake recordings that have been used for fitting these equations has increased in the past decades. The current PF-L database contains 3550 recordings. Since the GMPEs frequently model the peak ground acceleration (PGA) the goal of the present study was to refit a selection of 44 of the existing equation models for PGA in light of the latest data. The algorithm Levenberg-Marquardt was used for fitting the coefficients of the equations and the results are evaluated both quantitatively by presenting the root mean squared error (RMSE) and qualitatively by drawing graphs of the five best fitted equations. The RMSE was found to be as low as 0.08 for the best equation models. The newly estimated coefficients vary from the values published in the original works.

Keywords: Ground Motion Prediction Equations, Levenberg-Marquardt algorithm, refitting PF-L database, peak ground acceleration

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Authors: Ghadeer Jalloul, Nour Hijazi, Cassia Boyadjian, Hussein Awala, Mohammad N. Ahmad, ‎Ahmad Albadarin

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In this study, we applied Fe-sensitized TiO₂ supported over embryonic Beta zeolite (BEA) zeolite ‎for the photocatalytic degradation of Tetracycline (TC) antibiotic under visible light. Four different ‎samples having 20, 40, 60, and 100% w/w as a ratio of TiO₂/BEA were prepared. The ‎immobilization of solgel TiO₂ (33 m²/g) over BEA (390 m²/g) increased its surface area to (227 ‎m²/g) and enhanced its adsorption capacity from 8% to 19%. To expand the activity of TiO₂ ‎photocatalyst towards the visible light region (λ>380 nm), we explored two different metal ‎sensitization techniques with Iron ions (Fe³⁺). In the ion-exchange method, the substitutional cations ‎in the zeolite in TiO₂/BEA were exchanged with (Fe³⁺) in an aqueous solution of FeCl₃. In the ‎doping technique, solgel TiO₂ was doped with (Fe³⁺) from FeCl₃ precursor during its synthesis and ‎before its immobilization over BEA. (Fe-TiO₂/BEA) catalysts were characterized using SEM, XRD, ‎BET, UV-VIS DRS, and FTIR. After testing the performance of the various ion-exchanged catalysts ‎under blue and white lights, only (Fe-TiO₂/BEA 60%) showed better activity as compared to pure ‎TiO₂ under white light with 100 ppm initial catalyst concentration and 20 ppm TC concentration. As ‎compared to ion-exchanged (Fe-TiO₂/BEA), doped (Fe-TiO₂/BEA) resulted in higher photocatalytic ‎efficiencies under blue and white lights. The 3%-Fe-doped TiO₂/BEA removed 92% of TC ‎compared to 54% by TiO₂ under white light. The catalysts were also tested under real solar ‎irradiations. This improvement in the photocatalytic performance of TiO₂ was due to its higher ‎adsorption capacity due to BEA support combined with the presence of Iron ions that enhance the ‎visible light absorption and minimize the recombination effect by the charge carriers. ‎

Keywords: Tetracycline, photocatalytic degradation, immobilized TiO₂, zeolite, iron-doped TiO₂, ion-exchange

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Authors: Saltanat Zhilkibayeva, Muratulla Utenov, Nurzhan Utenov

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The distributed inertia forces of complex nature appear in links of rod mechanisms within the motion process. Such loads raise a number of problems, as the problems of destruction caused by a large force of inertia; elastic deformation of the mechanism can be considerable, that can bring the mechanism out of action. In this work, a new analytical approach for the definition of internal forces in links of robotic systems and mechanisms with statically indeterminate and determinate structures taking into account the distributed inertial and concentrated forces is proposed. The relations between the intensity of distributed inertia forces and link weight with geometrical, physical and kinematic characteristics are determined in this work. The distribution laws of inertia forces and dead weight make it possible at each position of links to deduce the laws of distribution of internal forces along the axis of the link, in which loads are found at any point of the link. The approximation matrixes of forces of an element under the action of distributed inertia loads with the trapezoidal intensity are defined. The obtained approximation matrixes establish the dependence between the force vector in any cross-section of the element and the force vector in calculated cross-sections, as well as allow defining the physical characteristics of the element, i.e., compliance matrix of discrete elements. Hence, the compliance matrixes of an element under the action of distributed inertial loads of trapezoidal shape along the axis of the element are determined. The internal loads of each continual link are unambiguously determined by a set of internal loads in its separate cross-sections and by the approximation matrixes. Therefore, the task is reduced to the calculation of internal forces in a final number of cross-sections of elements. Consequently, it leads to a discrete model of elastic calculation of links of rod mechanisms. The discrete model of the elements of mechanisms and robotic systems and their discrete model as a whole are constructed. The dynamic equilibrium equations for the discrete model of the elements are also received in this work as well as the equilibrium equations of the pin and rigid joints expressed through required parameters of internal forces. Obtained systems of dynamic equilibrium equations are sufficient for the definition of internal forces in links of mechanisms, which structure is statically definable. For determination of internal forces of statically indeterminate mechanisms (in the way of determination of internal forces), it is necessary to build a compliance matrix for the entire discrete model of the rod mechanism, that is reached in this work. As a result by means of developed technique the programs in the MAPLE18 system are made and animations of the motion of the fourth class mechanisms of statically determinate and statically indeterminate structures with construction on links the intensity of cross and axial distributed inertial loads, the bending moments, cross and axial forces, depending on kinematic characteristics of links are obtained.

Keywords: distributed inertial forces, internal forces, statically determinate mechanisms, statically indeterminate mechanisms

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Poonam Khurana, Mikelsh Prasad Yadav

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All human beings are virtue by God as they get controlling mind and an attitude towards something with the help of which they can experience spirituality. People have different psychological thoughts and beliefs relating to god. Some people feel the immense pleasure in performing religious activities while some believe in the thought “Ahem Brahmasmi” i.e I am part of the divine and they feel pleasure in activities which motivate them to achieve peace. Religion in psychology is considered as a specific fundamental set of beliefs, thoughts and practices generally agreed and controlled by a number of person. It is the psychology of a person which commands their mind in deciding at which path they can attain the eternal feelings of the universe and accordingly they will develop their behavior towards religion and spirituality. Keeping the same in mind, the present study is based much on literature and a brief analysis of 50 teachers in Delhi and NCR colleges and makes an attempt to study the relationship of spiritual quotient and effective teaching and suggest spiritual quotient as a considerable predictor to make the workplace accessible.

Keywords: effectiveness, quotient, teaching, spiritual

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Keiwoma Mark Yila, Mathew Lamrana Siaffa Gboku, Mohamed Sahr Lebbie, Lamin Ibrahim Kamara

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Rainfall and temperature are the important variables which are often used to trace climate variability and change. A perception study and analysis of climatic data were conducted to assess the changes in rainfall and temperature and their impact on crop production in Moyamba district, Sierra Leone. For the perception study, 400 farmers were randomly selected from farmer-based organizations (FBOs) in 4 chiefdoms, and 30 agricultural extension workers (AWEs) in the Moyamba district were purposely selected as respondents. Descriptive statistics and Kendall’s test of concordance was used to analyze the data collected from the farmers and AEWs. Data for the analysis of variability and trends of rainfall and temperature from 1991 to 2020 were obtained from the Sierra Leone Meteorological Agency and Njala University and grouped into monthly, seasonal and annual time series. Regression analysis was used to determine the statistical values and trend lines for the seasonal and annual time series data. The Mann-Kendall test and Sen’s Slope Estimator were used to analyze the trends' significance and magnitude, respectively. The results of both studies show evidence of climate change in the Moyamba district. A substantial number of farmers and AEWs perceived a decrease in the annual rainfall amount, length of the rainy season, a late start and end of the rainy season, an increase in the temperature during the day and night, and a shortened harmattan period over the last 30 years. Analysis of the meteorological data shows evidence of variability in the seasonal and annual distribution of rainfall and temperature, a decreasing and non-significant trend in the rainy season and annual rainfall, and an increasing and significant trend in seasonal and annual temperature from 1991 to 2020. However, the observed changes in rainfall and temperature by the farmers and AEWs partially agree with the results of the analyzed meteorological data. The majority of the farmers perceived that; adverse weather conditions have negatively affected crop production in the district. Droughts, high temperatures, and irregular rainfall are the three major adverse weather events that farmers perceived to have contributed to a substantial loss in the yields of the major crops cultivated in the district. In response to the negative effects of adverse weather events, a substantial number of farmers take no action due to their lack of knowledge and technical or financial capacity to implement climate-sensitive agricultural (CSA) practices. Even though few farmers are practising some CSA practices in their farms, there is an urgent need to build the capacity of farmers and AEWs to adapt to and mitigate the negative impacts of climate change. The most priority support needed by farmers is the provision of climate-resilient crop varieties, whilst the AEWs need training on CSA practices.

Keywords: climate change, crop productivity, farmer’s perception, rainfall, temperature, Sierra Leone

Procedia PDF Downloads 62

Authors: Gorazd Karer

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When performing a diagnostic procedure or surgery in general anesthesia (GA), a proper introduction and dosing of anesthetic agents are one of the main tasks of the anesthesiologist. However, depth of anesthesia (DoA) also seems to be a suitable process for closed-loop control implementation. To implement such a system, one must be able to acquire the relevant signals online and in real-time, as well as stream the calculated control signal to the infusion pump. However, during a procedure, patient monitors and infusion pumps are purposely unable to connect to an external (possibly medically unapproved) device for safety reasons, thus preventing closed-loop control. The paper proposes a conceptual solution to the aforementioned problem. First, it presents some important aspects of contemporary clinical practice. Next, it introduces the closed-loop-control-system structure and the relevant information flow. Focusing on transferring the data from the patient to the computer, it presents a non-invasive image-based system for signal acquisition from a patient monitor for online depth-of-anesthesia assessment. Furthermore, it introduces a UDP-based communication method that can be used for transmitting the calculated anesthetic inflow to the infusion pump. The proposed system is independent of a medical device manufacturer and is implemented in Matlab-Simulink, which can be conveniently used for DoA control implementation. The proposed scheme has been tested in a simulated GA setting and is ready to be evaluated in an operating theatre. However, the proposed system is only a step towards a proper closed-loop control system for DoA, which could routinely be used in clinical practice.

Keywords: closed-loop control, depth of anesthesia (DoA), modeling, optical signal acquisition, patient state index (PSi), UDP communication protocol

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Authors: Trapti Sharma, Devesh Kumar Srivastava

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This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

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Authors: D. M. S. Bandara, Yunqi Lei, Ye Luo

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Fingerprints are suitable as long-term markers of human identity since they provide detailed and unique individual features which are difficult to alter and durable over life time. In this paper, we propose an algorithm to encrypt and decrypt fingerprint images by using a specially designed Elliptic Curve Cryptography (ECC) procedure based on block ciphers. In addition, to increase the confusing effect of fingerprint encryption, we also utilize a chaotic-behaved method called Arnold Cat Map (ACM) for a 2D scrambling of pixel locations in our method. Experimental results are carried out with various types of efficiency and security analyses. As a result, we demonstrate that the proposed fingerprint encryption/decryption algorithm is advantageous in several different aspects including efficiency, security and flexibility. In particular, using this algorithm, we achieve a margin of about 0.1% in the test of Number of Pixel Changing Rate (NPCR) values comparing to the-state-of-the-art performances.

Keywords: arnold cat map, biometric encryption, block cipher, elliptic curve cryptography, fingerprint encryption, Koblitz’s encoding

Procedia PDF Downloads 191

Authors: C. Rana, S. K. Jain

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The enormous amount of Web data has challenged its usage in efficient manner in the past few years. As such, a range of techniques are applied to tackle this problem; prominent among them is personalization and recommender system. In fact, these are the tools that assist user in finding relevant information of web. Most of the e-commerce websites are applying such tools in one way or the other. In the past decade, a large number of recommendation algorithms have been proposed to tackle such problems. However, there have not been much research in the evaluation criteria for these algorithms. As such, the traditional accuracy and classification metrics are still used for the evaluation purpose that provides a static view. This paper studies how the evolution of user preference over a period of time can be mapped in a recommender system using a new evaluation methodology that explicitly using time dimension. We have also presented different types of experimental set up that are generally used for recommender system evaluation. Furthermore, an overview of major accuracy metrics and metrics that go beyond the scope of accuracy as researched in the past few years is also discussed in detail.

Keywords: collaborative filtering, data mining, evolutionary, clustering, algorithm, recommender systems

Procedia PDF Downloads 398

Authors: Saulutė Juzelėnienė, Skirmantė Šarkauskienė

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In this paper, it is aimed to analyse the multimodal representations of the concepts of LOVE and PASSION in Lithuanian graphic novel “Gertrūda”, by Gerda Jord. The research is based on the earlier findings by Forceville (2005), Eerden (2009) as well as insights made by Shihara and Matsunaka (2009) and Kövecses (2000). The domains of target and source of LOVE and PASSION metaphors in comics are expressed by verbal and non-verbal cues. The analysis of non-verbal cues adopts the concepts of rune and indexes. A pictorial rune is a graphic representation of an object that does not exist in reality in comics, such as lines, dashes, text "balloons", and pictorial index – a graphically represented object of reality, a real symptom expressing a certain emotion, such as a wide smile, furrowed eyebrows, etc. Indexes are often hyperbolized in comics. The research revealed that most frequent source domains are CLOSINESS/UNITY, NATURAL/ PHYSICAL FORCE, VALUABLE OBJECT, PRESSURE. The target is the emotion of LOVE/PASSION which belongs to a more abstract domain of psychological experience. In this kind of metaphor, the picture can be interpreted as representing the emotion of happiness. Data are taken from Lithuanian comic books and Internet sites, where comics have been presented. The data and the analysis we are providing in this article aims to reveal that there are pictorial metaphors that manifest conceptual metaphors that are also expressed verbally and that methodological framework constructed for the analysis in the papers by Forceville at all is applicable to other emotions and culture specific pictorial manifestations.

Keywords: multimodal metaphor, conceptual metaphor, comics, graphic novel, concept of love/passion

Procedia PDF Downloads 55

Authors: Erickson Bernardo, Caridad Pineda

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The project Adolescent Reproductive Health Information and Services (ARHIS) is a nine-month pilot project which intends to bridge the existing gap between reproductive health information and services, particularly with regard to family planning and HIV, among adolescent boys and girls aged 10-19 years in the 2nd Congressional District of Quezon City, in the Philippines. It aims to increase adolescents' and young people's awareness about their reproductive health concerns and at the same time make a wide range of reproductive health (RH) services accessible and available to them. A number of methodologies were utilized in the implementation of the project. At the onset, a baseline survey was conducted by community mobilizers to gather a situational analysis of adolescents' and young people's issues and concerns. The results of this survey were then presented in a multi-stakeholders' meeting to gather community support and foster their involvement. Further, interactive learning sessions (ILS) on a variety of reproductive health topics, among young people, parents and community leaders based on the results of the baseline survey was conducted. With regard to reproductive health service provision, both facility-based delivery and conduct of outreach activities were employed. In the span of nine months, the project was able to yield the following results: • A total of 521 adolescents and youth (AY) were reached by ILS on puberty, responsible relationships, teenage pregnancy, family planning, as well as HIV & AIDS. • A total of 218 parents and community leaders were informed of AY RH-related issues and concerns. • More than 350 AYs availed of a wide range of FP services including pills – both combined oral and progestin-only, and progestin-only injectables and implants. • More than 380 AYs availed of condoms as means of STI and HIV prevention. A noble initiative of the project is the utilization of a "condom distributor", a youth leader who has been educated about STI and HIV prevention as well as correct condom use, as the focal point for condom access in the community. • A total of 25 young people, parents, and community leaders were identified as ARHIS champions who have been instrumental in the achievement of project deliverables through their dedication and commitment to support the project. The concept of adolescent sexual and reproductive health (ASRH) remains to be a major challenge in the Philippine context. This is due to the fact that majority of Filipinos are still not keen on discussing issues and concerns related to ASRH, albeit the alarming number of teenage pregnancies and the rapid increase of HIV cases among 15- 24 year olds. In addition, Republic Act 10354 or the Responsible Parenthood and Reproductive Health Act of 2012, requires minor adolescents to present a written parental consent prior to accessing RH services. However, with the involvement and support of parents and key community stakeholders, these barriers may be addressed. The project has demonstrated how adolescents and young people yearn for reproductive health information and services.

Keywords: adolescent sexual reproductive health, barriers to access, reproductive health information and services, teenage pregnancies

Procedia PDF Downloads 159

Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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World-wide spread of coronavirus grows the concern about planning for the excess demand of hospital services in response to COVID-19 pandemic. The surge in the hospital services demand beyond the current capacity leads to shortage of ICU beds and ventilators in some parts of US. In this study, we forecast the required number of hospital beds and possible shortage of beds in US during COVID-19 pandemic to be used in the planning and hospitalization of new cases. In this paper, we used a data on COVID-19 deaths and patients’ hospitalization besides the data on hospital capacities and utilization in US from publicly available sources and national government websites. we used a novel ensemble modelling of deep learning networks, based on stacking different linear and non-linear layers to predict the shortage in hospital beds. The results showed that our proposed approach can predict the excess hospital beds demand very well and this can be helpful in developing strategies and plans to mitigate this gap.

Keywords: COVID-19, deep learning, ensembled models, hospital capacity planning

Procedia PDF Downloads 142

Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

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Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

Procedia PDF Downloads 188

Authors: Adam Y. Sulaiman, Gerard I.Obasi, Roma Chang, Hussein Sayed Moghaieb, Ming J. Huang, Neil J. Hewitt

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Residential air-conditioning units are essential for quality indoor comfort in hot climate countries. Nevertheless, because of their non-renewable energy sources and the contribution of ecologically unfriendly working fluids, these units are a major source of CO2 emissions in these countries. The utilisation of sustainable technologies nowadays is essential to reduce the adverse effects of CO2 emissions by replacing conventional technologies. This paper investigates the feasibility of running an off-grid solar-powered air-conditioning bed unit using three low GWP refrigerants (R32, R290, and R600a) to supersede conventional refrigerants.A prototype air conditioning unit was built to supply cold air to a canopy that was connected to it. The assembled unit was designed to distribute cold air to a canopy connected to it. This system is powered by two 400 W photovoltaic panels, with battery storage supplying power to the unit at night-time. Engineering Equation Solver (EES) software is used to mathematically model the vapor compression cycle (VCC) and predict the unit's energetic and exergetic performance. The TRNSYS software was used to simulate the electricity storage performance of the batteries, whereas the IES-VE was used to determine the amount of solar energy required to power the unit. The article provides an analytical design guideline, as well as a comprehensible process system. Combining a renewable energy source to power an AC based-VCC provides an excellent solution to the real problems of high-energy consumption in warm-climate countries.

Keywords: air-conditioning, refrigerants, PV panel, energy storages, VCC, exergy

Procedia PDF Downloads 164