Search results for: Information Systems Education

Authors: Marita Pigłowska, Beata Kurc, Maciej Galiński

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The application of carbon materials in the branches of the electrochemical industry shows an increasing tendency each year due to the many interesting properties they possess. These are, among others, a well-developed specific surface, porosity, high sorption capacity, good adsorption properties, low bulk density, electrical conductivity and chemical resistance. All these properties allow for their effective use, among others in supercapacitors, which can store electric charges of the order of 100 F due to carbon electrodes constituting the capacitor plates. Coals (including expanded graphite, carbon black, graphite carbon fibers, activated carbon) are commonly used in electrochemical methods of removing oil derivatives from water after tanker disasters, e.g., phenols and their derivatives by their electrochemical anodic oxidation. Phenol can occupy practically the entire surface of carbon material and leave the water clean of hydrophobic impurities. Regeneration of such electrodes is also not complicated, it is carried out by electrochemical methods consisting in unblocking the pores and reducing resistances, and thus their reactivation for subsequent adsorption processes. Graphite is commonly used as an anode material in lithium-ion cells, while due to the limited capacity it offers (372 mAh g-1), new solutions are sought that meet both capacitive, efficiency and economic criteria. Increasingly, biodegradable materials, green materials, biomass, waste (including agricultural waste) are used in order to reuse them and reduce greenhouse effects and, above all, to meet the biodegradability criterion necessary for the production of lithium-ion cells as chemical power sources. The most common of these materials are cellulose, starch, wheat, rice, and corn waste, e.g., from agricultural, paper and pharmaceutical production. Such products are subjected to appropriate treatments depending on the desired application (including chemical, thermal, electrochemical). Starch is a biodegradable polysaccharide that consists of polymeric units such as amylose and amylopectin that build an ordered (linear) and amorphous (branched) structure of the polymer. Carbon is also used as a catalyst. Elemental carbon has become available in many nano-structured forms representing the hybridization combinations found in the primary carbon allotropes, and the materials can be enriched with a large number of surface functional groups. There are many examples of catalytic applications of coal in the literature, but the development of this field has been hampered by the lack of a conceptual approach combining structure and function and a lack of understanding of material synthesis. In the context of catalytic applications, the integrity of carbon environmental management properties and parameters such as metal conductivity range and bond sequence management should be characterized. Such data, along with surface and textured information, can form the basis for the provision of network support services.

Keywords: carbon materials, catalysis, BET, capacitors, lithium ion cell

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Authors: Tatsuya Kasuga, Hidehisa Shimada, Kimio Oguchi

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Recent rapid progress in ICT (Information and Communication Technology) has advanced the penetration of sensor networks (SNs) and their attractive applications. Agriculture is one of the fields well able to benefit from ICT. Plant factories control several parameters related to plant growth in closed areas such as air temperature, humidity, water, culture medium concentration, and artificial lighting by using computers and AI (Artificial Intelligence) is being researched in order to obtain stable and safe production of vegetables and medicinal plants all year anywhere, and attain self-sufficiency in food. By providing isolation from the natural environment, a plant factory can achieve higher productivity and safe products. However, the biggest issue with plant factories is the return on investment. Profits are tenuous because of the large initial investments and running costs, i.e. electric power, incurred. At present, LED (Light Emitting Diode) lights are being adopted because they are more energy-efficient and encourage photosynthesis better than the fluorescent lamps used in the past. However, further cost reduction is essential. This paper introduces experiments that reveal which color of LED lighting best enhances the growth of cultured radish sprouts. Radish sprouts were cultivated in the experimental environment formed by a hydroponics kit with three cultivation shelves (28 samples per shelf) each with an artificial lighting rack. Seven LED arrays of different color (white, blue, yellow green, green, yellow, orange, and red) were compared with a fluorescent lamp as the control. Lighting duration was set to 12 hours a day. Normal water with no fertilizer was circulated. Seven days after germination, the length, weight and area of leaf of each sample were measured. Electrical power consumption for all lighting arrangements was also measured. Results and discussions: As to average sample length, no clear difference was observed in terms of color. As regards weight, orange LED was less effective and the difference was significant (p < 0.05). As to leaf area, blue, yellow and orange LEDs were significantly less effective. However, all LEDs offered higher productivity per W consumed than the fluorescent lamp. Of the LEDs, the blue LED array attained the best results in terms of length, weight and area of leaf per W consumed. Conclusion and future works: An experiment on radish sprout cultivation under 7 different color LED arrays showed no clear difference in terms of sample size. However, if electrical power consumption is considered, LEDs offered about twice the growth rate of the fluorescent lamp. Among them, blue LEDs showed the best performance. Further cost reduction e.g. low power lighting remains a big issue for actual system deployment. An automatic plant monitoring system with sensors is another study target.

Keywords: Electric power consumption, LED color, LED lighting, plant factory.

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Authors: S. Aziz, B. Alexander, C. Gengnagel, S. Weinzierl

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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the Building Information Modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: Acoustical design, additive manufacturing, computational design, multimodal optimization.

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Authors: Meghna Maiti, Utpal Roy

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In India, till today, malaria is considered to be one of the significant infectious diseases. Most of the cases regional geographical factors are the principal elements to let the places a unique identity. The incidence and intensity of infectious diseases are quite common and affect different places differently across the nation. The present study aims to identify spatial clusters of hot spots and cold spots of malaria incidence and their seasonal variation during the three periods of 2012-2014, 2015-2017 and 2018-20 in the state of West Bengal in India. As malaria is a vector-borne disease, numbers of positive test results are to be reported by the laboratories to the Department of Health, West Bengal (through the National Vector Borne Disease Control Programme). Data on block-wise monthly malaria positive cases are collected from Health Management Information System (HMIS), Ministry of Health and Family Welfare, Government of India. Moran’s I statistic is performed to assess the spatial autocorrelation of malaria incidence. The spatial statistical analysis mainly Local Indicators of Spatial Autocorrelation (LISA) cluster and Local Geary Cluster are applied to find the spatial clusters of hot spots and cold spots and seasonal variability of malaria incidence over the three periods. The result indicates that the spatial distribution of malaria is clustered during each of the three periods of 2012-2014, 2015-2017 and 2018-20. The analysis shows that in all the cases, high-high clusters are primarily concentrated in the western (Purulia, Paschim Medinipur districts), central (Maldah, Murshidabad districts) and the northern parts (Jalpaiguri, Kochbihar districts) and low-low clusters are found in the lower Gangetic plain (central-south) mainly and northern parts of West Bengal during the stipulated period. Apart from this seasonal variability inter-year variation is also visible. The results from different methods of this study indicate significant variation in the spatial distribution of malaria incidence in West Bengal and high incidence clusters are primarily persistently concentrated over the western part during 2012-2020 along with a strong seasonal pattern with a peak in rainy and autumn. By applying the different techniques in identifying the different degrees of incidence zones of malaria across West Bengal, some specific pockets or malaria hotspots are marked and identified where the incidence rates are quite harmonious over the different periods. From this analysis, it is clear that malaria is not a disease that is distributed uniformly across the state; some specific pockets are more prone to be affected in particular seasons of each year. Disease ecology and spatial patterns must be the factors in explaining the real factors for the higher incidence of this issue within those affected districts. The further study mainly by applying empirical approach is needed for discerning the strong relationship between communicable disease and other associated affecting factors.

Keywords: Malaria, infectious diseases, spatial statistics, spatial autocorrelation, LISA.

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Authors: Steven W. Carruthers

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The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Keywords: Effectiveness, equipercentile equating, IRT, learning games, linear equating, mean-sigma equating.

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Authors: Sotirios Raptis

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Health and Social care (HSc) services planning and scheduling are facing unprecedented challenges, due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven approaches can help to improve policies, plan and design services provision schedules using algorithms that assist healthcare managers to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as Classification and Regression Trees (CART), Random Forests (RF), and Logistic Regression (LGR). The significance tests Chi-Squared and Student’s test are used on data over a 39 years span for which data exist for services delivered in Scotland. The demands are associated using probabilities and are parts of statistical hypotheses. These hypotheses, as their NULL part, assume that the target demand is statistically dependent on other services’ demands. This linking is checked using the data. In addition, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus, groups of services. Statistical tests confirmed ML coupling and made the prediction statistically meaningful and proved that a target service can be matched reliably to other services while ML showed that such marked relationships can also be linear ones. Zero padding was used for missing years records and illustrated better such relationships both for limited years and for the entire span offering long-term data visualizations while limited years periods explained how well patients numbers can be related in short periods of time or that they can change over time as opposed to behaviours across more years. The prediction performance of the associations were measured using metrics such as Receiver Operating Characteristic (ROC), Area Under Curve (AUC) and Accuracy (ACC) as well as the statistical tests Chi-Squared and Student. Co-plots and comparison tables for the RF, CART, and LGR methods as well as the p-value from tests and Information Exchange (IE/MIE) measures are provided showing the relative performance of ML methods and of the statistical tests as well as the behaviour using different learning ratios. The impact of k-neighbours classification (k-NN), Cross-Correlation (CC) and C-Means (CM) first groupings was also studied over limited years and for the entire span. It was found that CART was generally behind RF and LGR but in some interesting cases, LGR reached an AUC = 0 falling below CART, while the ACC was as high as 0.912 showing that ML methods can be confused by zero-padding or by data’s irregularities or by the outliers. On average, 3 linear predictors were sufficient, LGR was found competing well RF and CART followed with the same performance at higher learning ratios. Services were packed only when a significance level (p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, low birth weights, alcoholism, drug abuse, and emergency admissions. The work found  that different HSc services can be well packed as plans of limited duration, across various services sectors, learning configurations, as confirmed by using statistical hypotheses.

Keywords: Class, cohorts, data frames, grouping, prediction, probabilities, services.

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Authors: P. C. Kutschera, Elena C. Tesoro, Mary Grace Talamera-Sandico, Jose Maria G. Pelayo III

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Second generation military Filipino Amerasians comprise a formidable contemporary segment of the estimated 250,000-plus biracial Amerasians in the Philippines today. Overall, they are a stigmatized and socioeconomically marginalized diaspora; historically, they were abandoned or estranged by U.S. military personnel fathers assigned during the century-long Colonial, Post- World War II and Cold War Era of permanent military basing (1898- 1992). Indeed, U.S. military personnel are assigned in smaller numbers in the Philippines today. This inquiry is an outgrowth of two recent small sample studies. The first surfaced the impact of the U.S. military prostitution system on formation of the ‘Derivative Amerasian Family Construct’ on first generation Amerasians; a second, qualitative case study suggested the continued effect of the prostitution systems' destructive impetuous on second generation Amerasians. The intent of this current qualitative, multiple-case study was to actively seek out second generation sex industry toilers. The purpose was to focus further on this human phenomenon in the postbasing and post-military prostitution system eras. As background, the former military prostitution apparatus has transformed into a modern dynamic of rampant sex tourism and prostitution nationwide. This is characterized by hotel and resorts offering unrestricted carnal access, urban and provincial brothels (casas), discos, bars and pickup clubs, massage parlors, local barrio karaoke bars and street prostitution. A small case study sample (N = 4) of female and male second generation Amerasians were selected. Sample formation employed a non-probability ‘snowball’ technique drawing respondents from the notorious Angeles, Metro Manila, Olongapo City ‘AMO Amerasian Triangle’ where most former U.S. military installations were sited and modern sex tourism thrives. A six-month study and analysis of in-depth interviews of female and male sex laborers, their families and peers revealed a litany of disturbing, and troublesome experiences. Results showed profiles of debilitating human poverty, history of family disorganization, stigmatization, social marginalization and the ghost of the military prostitution system and its harmful legacy on Amerasian family units. Emerging were testimonials of wayward young people ensnared in a maelstrom of deep economic deprivation, familial dysfunction, psychological desperation and societal indifference. The paper recommends that more study is needed and implications of unstudied psychosocial and socioeconomic experiences of distressed younger generations of military Amerasians require specific research. Heretofore apathetic or disengaged U.S. institutions need to confront the issue and formulate activist and solution-oriented social welfare, human services and immigration easement policies and alternatives. These institutions specifically include academic and social science research agencies, corporate foundations, the U.S. Congress, and Departments of State, Defense and Health and Human Services, and Homeland Security (i.e. Citizen and Immigration Services) It is them who continue to endorse a laissez-faire policy of non-involvement over the entire Filipino Amerasian question. Such apathy, the paper concludes, relegates this consequential but neglected blood progeny to the status of humiliating destitution and exploitation. Amerasians; thus, remain entrapped in their former colonial, and neo-colonial habitat. Ironically, they are unwitting victims of a U.S. American homeland that fancies itself geo-politically as a strong and strategic military treaty ally of the Philippines in the Western Pacific.

Keywords: Asian Americans, Filipino Amerasians, diaspora, military prostitution, stigmatization.

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