Search results for: actionable pattern discovery

Authors: Shakila Singh

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This research was conducted at a selected South African university campus with women students who drink alcohol. The purpose of the study was to examine their perspectives on the role of alcohol in their lives, their understandings about women’s vulnerability to alcohol-related sexual risk and their strategies against these. The study draws on feminist principles and practices to challenge gendered inequalities that legitimate and facilitate violence against women. Recognising the danger of focusing on risk management in ways that place the burden of responsibility entirely on young women to prevent their violation, this article focuses on women students’ agency in managing risk while taking up opportunities for self-discovery. Participation was voluntary, and a student-researcher administered an open-ended questionnaire to 55 participants. The findings suggest that young women position alcohol- use as a common activity at university, and that it gives them much pleasure. They recognise that it is riskier for women and articulate valuable strategies to manage the risk to their sexual safety when drinking. These include drinking within supportive networks, avoiding financial dependence, and managing their alcohol intake. This article argues that alcohol at university is an integral part of expressions of gender and sexuality and that risk-taking is a normal part of university students’ lives. Consequently, arguments about equality need to consider risk-taking as part of young people’s lives and promote ways of managing alcohol-related risks, rather than imagining that alcohol can be avoided entirely.

Keywords: alcohol-related sexual risk, drinking at university, managing risk, women students

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Authors: Azazhu Wassie

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This study tried to analyze and identify the drainage pattern and catchment characteristics of the river basin and assess the impact of the hydrologic parameters (catchment area, rainfall intensity, runoff coefficient, land use, and soil type) on the referenced study area. Since there is no river gauging station near the road, even for large rivers, rainfall-runoff models are adopted for flood estimation, i.e., for catchment areas less than 50 ha, the rational method is used; for catchment areas, less than 65 km², the SCS unit hydrograph method is used; and for catchment areas greater than 65 km², HEC-HMS is adopted for flood estimation.

Keywords: Arc GIS, catchment area, land use/land cover, peak flood, rainfall intensity

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: Rinaldi Ikhram, R. A. Julia Satriani

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The discovery of historical objects in Indonesia, especially in the area around Bandung and Priangan zone in general, have been inventorized and recorded by Dutch geologists during the colonial time. Among artefacts such as axes made of chalcedony and quartzite; arrowheads, knives, shrivel, and drill bit all made from obsidian; grindstones, even bracelet from stones. Ceramic mold for smelting bronze or iron were also found. The abundance of artefacts inspired DR. W. Docters van Leeuwen and his colleagues to initiate the establishment of Sunda Open-air Museum "Soenda Openlucht Museum" in 1917, located in the hills of North Bandung area, the site of pre-historic settlements that needs conservation. Unfortunately, this plan was not implemented because shortly after, World War II occurred. The efforts of heritage conservation is one of our responsibilities as a geologist today. Open-air Museum may be one of the solutions of heritage conservation for historic sites around the world. In this paper, the study of the development of Open-air Museum will be focused on the area of Dago, North Bandung. Method used is data analysis of field surveys, and data analysis of the remaining artefacts stored at both the National Museum in Jakarta, and the Bandung Museum of Geology. The museum is based on Geotourism and further research on pre-historic culture, while its purpose is to give people a common interest and to motivate them to participate in the research and conservation of pre-historic relics. This paper will describe more details about the concept, form, and management of the geopark and the Open-air Museum within.

Keywords: geoparks, heritage conservation, open-air museum, sustainable tourism

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Authors: Jeongyeob Hong, Myeonghoon Park, Taeson Yoon

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After the advent of Achaeans which utilize different metabolism pathway and contain conspicuously different cellular structure, they have been recognized as possible materials for developing quality of human beings. Among diverse Achaeans, in this paper, we compared 16s RNA Sequences of four different species of Thermococcus: Achaeans genus specialized in sulfur-dealing metabolism. Four Species, Barophilus, Kodakarensis, Hydrothermalis, and Onnurineus, live near the hydrothermal vent that emits extreme amount of sulfur and heat. By comparing ribosomal sequences of aforementioned four species, we found similarities in their sequences and expressed protein, enabling us to expect that certain ribosomal sequence or proteins are vital for their survival. Apriori algorithms and Decision Tree were used. for comparison.

Keywords: Achaeans, Thermococcus, apriori algorithm, decision tree

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: Astrid Bagireanu, Julio Bros-Williamson, Mila Duncheva, John Currie

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Digital Twins (DTs) have entered the built environment from more established industries like aviation and manufacturing, although there has never been a common goal for utilising DTs at scale. Defined as the cyber-physical integration of data between an asset and its virtual counterpart, DT has been identified in literature from an operational standpoint – in addition to monitoring the performance of a built asset. However, this has never been translated into how DTs should be implemented into a project and what responsibilities each project stakeholder holds in the realisation of a DT. What is needed is an approach to translate these requirements into actionable DT dimensions. This paper presents a foundation for an overarching framework specific to the built environment. For the purposes of this research, the UK widely used the Royal Institute of British Architects (RIBA) Plan of Work from 2020 is used as a basis for itemising project stages. The RIBA Plan of Work consists of eight stages designed to inform on the definition, briefing, design, coordination, construction, handover, and use of a built asset. Similar project stages are utilised in other countries; therefore, the recommendations from the interviews presented in this paper are applicable internationally. Simultaneously, there is not a single mainstream software resource that leverages DT abilities. This ambiguity meets an unparalleled ambition from governments and industries worldwide to achieve a national grid of interconnected DTs. For the construction industry to access these benefits, it necessitates a defined starting point. This research aims to provide a comprehensive understanding of the potential applications and ramifications of DT in the context of the built environment. This paper is an integral part of a larger research aimed at developing a conceptual framework for the Architecture, Engineering, and Construction (AEC) sector following a conventional project timeline. Therefore, this paper plays a pivotal role in providing practical insights and a tangible foundation for developing a stage-by-stage approach to assimilate the potential of DT within the built environment. First, the research focuses on a review of relevant literature, albeit acknowledging the inherent constraint of limited sources available. Secondly, a qualitative study compiling the views of 14 DT experts is presented, concluding with an inductive analysis of the interview findings - ultimately highlighting the barriers and strengths of DT in the context of framework development. As parallel developments aim to progress net-zero-centred design and improve project efficiencies across the built environment, the limited resources available to support DTs should be leveraged to propel the industry to reach its digitalisation era, in which AEC stakeholders have a fundamental role in understanding this, from the earliest stages of a project.

Keywords: digital twins, decision-making, design, net-zero, built environment

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Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

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Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

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Authors: Melkamu A. Zeru, Yamral M. Warkaw, Aweke A. Mitku, Muluwerk Ayele

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Introduction: Malaria is a severe health threat in the World, mainly in Africa. It is the major cause of health problems in which the risk of morbidity and mortality associated with malaria cases are characterized by spatial variations across the county. This study aimed to investigate the spatial patterns and predictors of malaria distribution in Ethiopia. Methods: A weighted sample of 15,239 individuals with rapid diagnosis tests was obtained from the Central Statistical Agency and Ethiopia malaria indicator survey of 2015. Global Moran's I and Moran scatter plots were used in determining the distribution of malaria cases, whereas the local Moran's I statistic was used in identifying exposed areas. In data manipulation, machine learning was used for variable reduction and statistical software R, Stata, and Python were used for data management and analysis. The auto logistics spatial binary regression model was used to investigate the predictors of malaria. Results: The final auto logistics regression model reported that male clients had a positive significant effect on malaria cases as compared to female clients [AOR=2.401, 95 % CI: (2.125 - 2.713)]. The distribution of malaria across the regions was different. The highest incidence of malaria was found in Gambela [AOR=52.55, 95%CI: (40.54-68.12)] followed by Beneshangul [AOR=34.95, 95%CI: (27.159 - 44.963)]. Similarly, individuals in Amhara [AOR=0.243, 95% CI:(0.1950.303],Oromiya[AOR=0.197,95%CI:(0.1580.244)],DireDawa[AOR=0.064,95%CI(0.049-0.082)],AddisAbaba[AOR=0.057,95%CI:(0.044-0.075)], Somali[AOR=0.077,95%CI:(0.059-0.097)], SNNPR[OR=0.329, 95%CI: (0.261- 0.413)] and Harari [AOR=0.256, 95%CI:(0.201 - 0.325)] were less likely to had low incidence of malaria as compared with Tigray. Furthermore, for a one-meter increase in altitude, the odds of a positive rapid diagnostic test (RDT) decrease by 1.6% [AOR = 0.984, 95% CI :( 0.984 - 0.984)]. The use of a shared toilet facility was found as a protective factor for malaria in Ethiopia [AOR=1.671, 95% CI: (1.504 - 1.854)]. The spatial autocorrelation variable changes the constant from AOR = 0.471 for logistic regression to AOR = 0.164 for auto logistics regression. Conclusions: This study found that the incidence of malaria in Ethiopia had a spatial pattern that is associated with socio-economic, demographic, and geographic risk factors. Spatial clustering of malaria cases had occurred in all regions, and the risk of clustering was different across the regions. The risk of malaria was found to be higher for those who live in soil floor-type houses as compared to those who live in cement or ceramics floor type. Similarly, households with thatched, metal and thin, and other roof-type houses have a higher risk of malaria than ceramic tiles roof houses. Moreover, using a protected anti-mosquito net reduced the risk of malaria incidence.

Keywords: malaria, Ethiopia, auto logistics, spatial model, spatial clustering

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Authors: Zhao Bin, Yan Dan Lei

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In this paper, a multi-pattern parallel PRBS generator and a dedicated parallel BER tester is proposed for the 8-Gbps On-chip interconnection testing. A unique full-parallel PRBS checker is also proposed. The proposed design, together with the custom-designed high-speed parallel-to-serial and the serial-to-parallel circuit, will be used to test different on-chip interconnection transceivers. The design is implemented in TSMC 28nm CMOS technology with working voltage at 1.0 V. The serial to parallel ratio is 8:1 so the parallel PRBS generation and BER Tester can be run at lower speed.

Keywords: PRBS, BER, high speed, generator

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Authors: Arun Prabhakar

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Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

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Authors: Muhammad Shahid, Muhammad Mansoor

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Increasing demands of contemporary applications for high strength and lightweight materials prompted the development of metal-matrix composites (MMCs). After the discovery of carbon nanotubes (CNTs) in 1991 (revealing an excellent set of mechanical properties) became one of the most promising strengthening materials for MMC applications. Additionally, the relatively low density of the nanotubes imparted high specific strengths, making them perfect strengthening material to reinforce MMCs. In the present study, aluminum-multiwalled carbon nanotubes (Al-MWCNTs) composite was prepared in an air induction furnace. The dispersion of the nanotubes in molten aluminum was assisted by inherent string action of induction heating at 790°C. During the fabrication process, multifunctional fluxes were used to avoid oxidation of the nanotubes and molten aluminum. Subsequently, the melt was cast in to a copper mold and cold rolled to 0.5 mm thickness. During metallographic examination using a scanning electron microscope, it was observed that the nanotubes were effectively dispersed in the matrix. The mechanical properties of the composite were significantly increased as compared to pure aluminum specimen i.e. the yield strength from 65 to 115 MPa, the tensile strength from 82 to 125 MPa and hardness from 27 to 30 HV for pure aluminum and Al-CNTs composite, respectively. To recognize the associated strengthening mechanisms in the nanocomposites, three foremost strengthening models i.e. shear lag model, Orowan looping and Hall-Petch have been critically analyzed; experimental data were found to be closely satisfying the shear lag model.

Keywords: carbon nanotubes, induction melting, strengthening mechanism, nanocomposite

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Authors: Elmira Ghanbari, Jan Van Esch, Stephen J. Picken, Sahil Aggarwal

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Low-molecular-weight organogelators form gels by self-assembly into the crystalline network which immobilizes the organic solvent. For single bisamide organogelator systems, the effect of the molecular structure on the molecular interaction and their self-assembly behavior has been explored. The spatial arrangement of bisamide molecules in the gel-state is driven by a combination of hydrogen bonding and Van der Waals interactions. The hydrogen-bonding pattern between the amide groups of bisamide molecules is regulated by the number of methylene spacers; the even number of methylene spacers between two amide groups, in even-spaced bisamides, leads to the antiparallel position of amide groups within a molecule. An even-spaced bisamide molecule with antiparallel amide groups can make two pairs of hydrogen bonding with the molecules on the same plane. The odd-spaced bisamide with a parallel directionality of amide groups can form four independent hydrogen bonds with four other bisamide molecules on different planes. The arrangement of bisamide molecules in the crystalline state and the interaction of these molecules depends on the molecular structure, particularly the parity of the spacer length between the amide groups in the bisamide molecule. In this study, the directionality of amide groups has been exploited as a structural characteristic to affect the arrangement of molecules in the crystalline state and produce different binary bisamide gelators with different degrees of crystallinities. Single odd- and even-spaced single bisamides were synthesized and blended to produce binary bisamide organogelators to be characterized in order to understand the effect of the different directionality of amide groups on the molecular interaction in the crystalline state. The pattern of molecular interactions between these blended molecules, mixing or phase separation, has been monitored via differential scanning calorimetry (DSC) and crystallography techniques; X-ray powder diffraction (XRD) and Small-angle X-ray scattering (SAXS). The formation of lamellar structures for odd- and even-spaced bisamide gelators was confirmed by using SAXS and XRD techniques. DSC results have shown that binary bisamide organogelators with different parity of methylene spacers (odd-even binary blends) have a higher tendency for phase separation compared to the binary bisamides with the same parity (odd-odd or even-even binary blends). Phase separation in binary odd-even bisamides was confirmed by the presence of individual (100) reflections of odd and even lamellar structures. The structural characteristic of bisamide organogelators, the parity of spacer length in binary systems, is a promising tool to control the arrangement of molecules and their crystalline structure.

Keywords: binary bisamide organogelators, crystalline structure, phase separation, self-assembly behavior

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Anatoly D. Pluzhnikov, Elena N. Pribludova, Alexander G. Ryndyk

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In conjunction with the problem of the target selection on a clutter background, the analysis of the scanning rate influence on the spatial-temporal signal structure, the generalized multivariate correlation function and the quality of the resolution with the increase pulse repetition frequency is made. The possibility of the object space-distance resolution, which is conditioned by the range-to-angle conversion with an increased scanning rate, is substantiated. The calculations for the real cylindrical array at high scanning rate are presented. The high scanning rate let to get the signal to noise improvement of the order of 10 dB for the space-time signal processing.

Keywords: antenna pattern, array, signal processing, spatial resolution

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Authors: Deepika Saini, Sandeep Jain, Ajay Kumar

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The quinoline scaffold is one of the most widely studied in the discovery of derivatives with various heterocyclic moieties due to its potential antimalarial activities. In the present study, a chalcone series of quinoline derivatives clubbed with pyrazole were synthesized to evaluate their antimalarial property by in vitro schizont maturation inhibition assay against both chloroquine sensitive, 3D7 and chloroquine resistant, RKL9 strain of Plasmodium falciparum. Further, top five compounds were studied for in vivo preclinical study for antimalarial potential against P. berghei in Swiss albino mice. To understand the mechanism of synthesized analogues, they were screened computationally by molecular docking techniques. Compounds were docked into the active site of a protein receptor, Plasmodium falciparum Cysteine Protease Falcipain-2. The compounds were successfully synthesized, and structural confirmation was performed by FTIR, 1H-NMR, mass spectrometry and elemental analysis. In vitro study suggested that the compounds 5b, 5g, 5l, 5s and 5u possessed best antimalarial activity and further tested for in vivo screening. Compound 5u (CH₃ on both rings) with EC₅₀ 0.313 & 0.801 µg/ml against CQ-S & CQ-R strains of P. falciparum respectively and 78.01% suppression of parasitemia. The molecular docking studies of the compounds helped in understanding the mechanism of action against falcipain-2. The present study reveals the binding signatures of the synthesized ligands within the active site of the protein, and it explains the results from in vitro study in their EC₅₀ values and percentage parasitemia.

Keywords: antimalarial activity, chalcone, docking, quinoline

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Sergey A. Burikov, Tatiana A. Dolenko, Kirill A. Gushchin, Sergey A. Dolenko

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The paper presents the results of clusterization by Kohonen self-organizing maps (SOM) applied for analysis of array of Raman spectra of multi-component solutions of inorganic salts, for determination of types of salts present in the solution. It is demonstrated that use of SOM is a promising method for solution of clusterization and classification problems in spectroscopy of multi-component objects, as attributing a pattern to some cluster may be used for recognition of component composition of the object.

Keywords: Kohonen self-organizing maps, clusterization, multi-component solutions, Raman spectroscopy

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Authors: E. A. Krasikov

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Dependence of the materials properties on neutron irradiation intensity (flux) is a key problem while usage data of the accelerated materials irradiation in test reactors for forecasting of their capacity for work in realistic (practical) circumstances of operation. Investigations of the reactor pressure vessel steel radiation degradation dependence on fast neutron fluence (embrittlement kinetics) at low flux reveal the instability in the form of the scatter of the experimental data and wave-like sections of embrittlement kinetics appearance. Disclosure of the steel degradation oscillating is a sign of the steel structure cyclic self-recovery transformation as it take place in self-organization processes. This assumption has received support through the discovery of the similar ‘anomalous’ data in scientific publications and by means of own additional experiments. Data obtained stimulate looking-for ways to management of the structural steel radiation stability (for example, by means of nano - structure modification for radiation defects annihilation intensification) for creation of the intelligent self-recovering material. Expected results: - radiation degradation theory and mechanisms development, - more adequate models of the radiation embrittlement elaboration, - surveillance specimen programs improvement, - methods and facility development for usage data of the accelerated materials irradiation for forecasting of their capacity for work in realistic (practical) circumstances of operation, - search of the ways for creating of the radiation stable self-recovery intelligent materials.

Keywords: degradation, radiation, steel, wave-like kinetics

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Authors: Kwan Hee Han, Jun Woo Lee, Sung Moon Bae, Twae Kyung Park

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ECA (Event-Condition-Action) languages are largely adopted for event processing since they are an intuitive and powerful paradigm for programming reactive systems. However, there are some limitations about ECA rules for processing of complex events such as coupling of event producer and consumer. The objective of this paper is to propose an ECA rule pattern to improve the current limitations of ECA rule, and to develop a prototype system. In this paper, conventional ECA rule is separated into 3 parts and each part is extended to meet the requirements of CEP. Finally, event processing logic is established by combining the relevant elements of 3 parts. The usability of proposed extended ECA rule is validated by a test scenario in this study.

Keywords: complex event processing, ECA rule, Event processing system, event-driven architecture, internet of things

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Authors: Rukminingsih Rukmi

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This paper addresses the issue of L2 teaching speaking to ESL students by fostering their active learning through project-based learning. Project-based learning was employed in classrooms where teachers support students by giving sufficient guidance and feedback. The students drive the inquiry, engage in research and discovery, and collaborate effectively with teammates to deliver the final work product. The teacher provides the initial direction and acts as a facilitator along the way. This learning approach is considered helpful for fostering students’ active learning. that the steps in implementing of project-based learning that fosters students’ critical thinking in TEFL class are in the following: (1) Discussing the materials about Speaking Class, (2) Working with the group to construct scenario of ways on speaking practice, (3) Practicing the scenario, (4) Recording the speaking practice into video, and (5) Evaluating the video product. This research is aimed to develop a strategy of teaching speaking by implementing project-based learning to improve speaking skill in the second Semester of English Department of STKIP PGRI Jombang. To achieve the purpose, the researcher conducted action research. The data of the study were gathered through the following instruments: test, observation checklists, and questionnaires. The result was indicated by the increase of students’ average speaking scores from 65 in the preliminary study, 73 in the first cycle, and 82 in the second cycle. Besides, the results of the study showed that project-based learning considered to be appropriate strategy to give students the same amount of chance in practicing their speaking skill and to pay attention in creating a learning situation.

Keywords: active learning, project-based learning, speaking ability, L2 teaching speaking

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Authors: Mary H Moen, Lauren H. Mandel

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Creating a sense of community in online learning is important for student engagement and success. The integration of discussion forums within online learning environments presents an opportunity to explore how this computer mediated communications format can cultivate a sense of community among students in accelerated master’s degree programs. This research has two aims, to delve into the ways instructors utilize this communications technology to create community and to understand the feelings and experiences of graduate students participating in these forums in regard to its effectiveness in community building. This study is a two-phase approach encompassing qualitative and quantitative methodologies. The data will be collected at an online accelerated Master of Library and Information Studies program at a public university in the northeast of the United States. Phase 1 is a content analysis of the syllabi from all courses taught in the 2023 calendar year, which explores the format and rules governing discussion forum assignments. Four to six individual interviews of department faculty and part time faculty will also be conducted to illuminate their perceptions of the successes and challenges of their discussion forum activities. Phase 2 will be an online survey administered to students in the program during the 2023 calendar year. Quantitative data will be collected for statistical analysis, and short answer responses will be analyzed for themes. The survey is adapted from the Classroom Community Scale Short-Form (CSS-SF), which measures students' self-reported responses on their feelings of connectedness and learning. The prompts will contextualize the items from their experience in discussion forums during the program. Short answer responses on the challenges and successes of using discussion forums will be analyzed to gauge student perceptions and experiences using this type of communication technology in education. This research study is in progress. The authors anticipate that the findings will provide a comprehensive understanding of the varied approaches instructors use in discussion forums for community-building purposes in an accelerated MLIS program. They predict that the more varied, flexible, and consistent student uses of discussion forums are, the greater the sense of community students will report. Additionally, students’ and instructors’ perceptions and experiences within these forums will shed light on the successes and challenges faced, thereby offering valuable recommendations for enhancing online learning environments. The findings are significant because they can contribute actionable insights for instructors, educational institutions, and curriculum designers aiming to optimize the use of discussion forums in online accelerated graduate programs, ultimately fostering a richer and more engaging learning experience for students.

Keywords: accelerated online learning, discussion forums, LIS programs, sense of community, g

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Authors: Tayba Akram

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our main objective of this study is to work on the etiology of liver cirrhosis, to find basic reasons and causes of liver damage, and to find the pattern of liver cirrhosis in hepatic patients either suffering from hepatitis B/C or simple jaundice. We can evaluate medical treatment and the latest trends in patients suffering from liver cirrhosis. We can evaluate the side effects and adverse effects induced by drug therapy used to treat liver cirrhosis. The conclusion is based on the etiology of liver cirrhosis. The most common cause of liver cirrhosis is the viral Hepatitis C virus. Other common causes of liver cirrhosis that are estimated from our research are Hepatitis B virus, Diabetes Mellitus, Ascites, and very rarely found Hepatitis D virus.

Keywords: etiology, liver, cirrhosis, co-morbid diseases

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Authors: Shamim Mushtaq, Moazzam Shahid

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Breast cancer (BC) claims the lives of half a million women every year and is the most common cause of death in the developing world. In 2019, it was estimated that BC alone accounts for 15% of all cancer deaths in younger women (aged < 45 years old) with advanced-stage lung metastasis. According to the World Health Organization & International Union against Cancer, in Asia, a high number of cancer-related deaths will be observed in 2020, whereas the burden will be reduced in Western countries due to awareness about the disease, better health facilities and advanced treatments. In the last 15 years, it has been reported that the incidence of BC has increased by 1.1% among Asian compared to the US population from 2003 to 2012. To date, several BC biological subtypes have been reported so far, which are associated with different treatment responses. The heterogeneity and diversity of BC reflected these different subtypes, including Luminal A (23.7% prevalence) and B (38.8% prevalence) that have pathological estrogen receptor (ER+)-positive tumors, the human epidermal growth factor receptor 2 (HER2) (11.2% prevalence) and triple-negative breast cancer (TNBC) (25% prevalence). According to Shaukat Khanum Memorial Cancer Hospital and Research Centre – Pakistan, ten years of data showed that among 636 BC patients, 30.5% had TNBC who were <40 years of age, which is an extremely alarming situation. Therefore, there is a dire need to explore and develop therapeutic targets for the treatment of early TNBC. Since the last decade, unfortunately, there has been little success in understanding the complexity of TNBC and in discovering new biological therapeutic targets. However, conventional chemotherapy is the only choice of treatment for TNBC patients. Many investigators revealed advances in multi-omics (multiple "omes", e.g., genome, proteome, transcriptome, epigenome, and microbiome) which were later identified as actionable targets and increased prevalence in TNBC patients. However, various drugs have been identified so far which are related to a particular diagnostic and prognostic biomarker. For example, Epidermal growth factor receptor ( EGFR or ErbB-1), HER-2/neu (ErbB-2), HER-3 (ErbB-3), and HER-4 (ErbB-4). Protein Transglin-2 (TAGLN 2 ) and Profilins-1 (Pfn-1 ) are the ubiquitously expressed large family of proteins present in all eukaryotes, enabling actin cytoskeletal reorganization. It is known that the oncogenic transformation of cells is accompanied by alteration in the actin cytoskeleton. There are causal connections between altered expression of actin cytoskeletal regulators and cancer progression. Our case-control study identified TAGLN-2 and Pfn-1 proteins in TNBC blood by mass spectrometry. Both TAGLN-2 and Pfn-1 proteins are differentially expressed in early and advanced stages of TNBS patients, which could be potential predictors or therapeutic targets for TNBC.

Keywords: TNBC, blood biomarkers, mass spectrometry, qPCR, ELISA

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Authors: Khaled M. Khan, Armstrong Nhlabatsi

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This article attempts to analyse behavioural traits of lone-wolves who struck and killed innocents in six different attacks in Europe in last nine months. The main objective of this study is to develop a profiling template in order to capture commonality of characteristics of these attackers. This study tries to understand the homogeneity of lone-wolves in terms of their social background and state of mind. The commonality among them can possibly be used to build a profiling template that could help detecting vulnerable persons who are prone to be self-radicalised or radicalised by someone else. The result of this study provides us an understanding of their commonality in terms of their state of mind and social characteristics.

Keywords: behavioral pattern, terrorism, profiling, commonality

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Authors: Keivan Jamshidi, Fateme Behbahani, Sara Omidi, Nadia Shahi, Alireza Farkhonde

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Amyloidosis represents a heterogenous group of diseases that have in common the deposition of fibrils composed of proteins of beta-pleated sheet structure, which can be specifically identified by histochemistry using the Congo red or similar stains. Between October 2013 to April 2014 (6 months) different patterns of renal amyloidosis was diagnosed on histopathological examination of kidneys belong to 196 out of 7065 slaughtered sheep subjected to postmortem examination. Microscopic examination of renal tissue sections stained with H&E and CR staining techniques revealed 3 patterns of renal amyloid deposition; including glomerular (22.72%), medullary (68.18%), and vascular (9.09%) were recognized. Renal medullary amyloidosis (RMA) was detected as the most prevalence pattern of renal amyloidosis in domestic sheep.

Keywords: sheep, amyloidosis, kidney, slaughterhouse

Procedia PDF Downloads 375

Authors: Jahanshah Saleh, Hossein Ghasemi, Ali Shahriari, Faezeh Alizadeh, Yaaghoob Hosseini

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Cadmium and chromium are toxic to most organisms and different mechanisms have been developed for overcoming with the toxic effects of these heavy metals. We studied the uptake and distribution of cadmium and chromium in different organs of tomato (Lycopersicon esculentum L.) plants in nine heavy metal polluted soils in western Hormozgan province, Iran. The accumulation of chromium was in increasing pattern of fruit peel

Keywords: cadmium, chromium, phytoextraction, phytostabilization, tomato

Procedia PDF Downloads 347

Authors: Alireza Karimi

Abstract:

Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Abbas Hani, Maryam Jassasizadeh

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The concentrations of Cd, Pb, and Ni were determined from 40 soil samples collected in surface soils of Khark Island. Geostatistic methods and GIS were used to identify heavy metal sources and their spatial pattern. Principal component analysis coupled with correlation between heavy metals showed that level of mentioned heavy metal was lower than the standard level. Then the data obtained from the soil analyzing were studied for the purposes of normal distribution. The best way of interior finding for cadmium and nickel was ordinary kriging and the best way of interpolation of lead was inverse distance weighted. The result of this study help us to understand heavy metals distribution and make decision for remediation of soil pollution.

Keywords: geostatistics, ordinary kriging, heavy metals, GIS, Khark

Procedia PDF Downloads 167