Search results for: regression test

Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Aksentijević M. Snežana

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Samples of tap and wastewater were collected in three offset printing facilities in Novi Sad, Serbia. Ten physicochemical parameters were analyzed within all collected samples: pH, conductivity, m - alkalinity, p - alkalinity, acidity, carbonate concentration, hydrogen carbonate concentration, active oxygen content, chloride concentration and total alkali content. All measurements were conducted using the standard analytical and instrumental methods. Comparing the obtained results for tap water and wastewater, a clear quality difference was noticeable, since all physicochemical parameters were significantly higher within wastewater samples. The study also involves the application of simple linear regression analysis on the obtained dataset. By using software package ORIGIN 5 the pH value was mutually correlated with other physicochemical parameters. Based on the obtained values of Pearson coefficient of determination a strong positive correlation between chloride concentration and pH (r = -0.943), as well as between acidity and pH (r = -0.855) was determined. In addition, statistically significant difference was obtained only between acidity and chloride concentration with pH values, since the values of parameter F (247.634 and 182.536) were higher than F_critical (5.59). In this way, results of statistical analysis highlighted the most influential parameter of water contamination in offset printing, in the form of acidity and chloride concentration. The results showed that variable dependence could be represented by the general regression model: y = a₀ + a₁x+ k, which further resulted with matching graphic regressions.

Keywords: pollution, printing industry, simple linear regression analysis, wastewater

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Authors: Kartika Marta Budiana

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Low competence in speaking for the students of Non English native speakers have been crucial so far for the teachers in language teaching in Indonesia. This study attempts to explore the effect of video using in teaching speaking onstudents of non-native English speakers at STIE Perbanas Surabaya. This includes investigate the students` attitudes toward the video used in classroom. This is a quantitative research that is an experimental one based on analyses derived the concepts of from teaching speaking and the use of video. There are two classes observed, the experimental and the control one. The experimental consist of 28 students and the control class consists of 25 students. Before the treatment given, both of the group is given the pre-test to check their ability level. Then, after the treatment is given, the post-test is given to the both groups. Then, the students were given treatment how to conduct a meeting that they learnt from a video of business English. The post test was held after they undergone a treatment. The instruments to get the data are the oral test and questionnaire. The data of this study is students` score and from the tests` score it can be seen there is a positive significant difference in the experimental group. The t-test to test hypothesize also shows that it is accepted which said that there is an improvement on the students` speaking competence achievement. In conclusion, the video effects on the significant difference on the students speaking competence achievement.

Keywords: video, teaching, speaking, Indonesia

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Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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Authors: Kehinde Peter Oyeduntan, Kayode Oshinubi

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The west African ports have been experiencing large inflow and outflow of containerized cargo in the last decades, and this has created a quest amongst the countries to attain the status of hub port for the sub-region. This study analyzed the relationship between the container throughput and Gross Domestic Products (GDP) of nine west African countries, using Simple Linear Regression (SLR), Polynomial Regression Model (PRM) and Support Vector Machines (SVM) with a time series of 20 years. The results showed that there exists a high correlation between the GDP and container throughput. The model also predicted the container throughput in west Africa for the next 20 years. The findings and recommendations presented in this research will guide policy makers and help improve the management of container ports and terminals in west Africa, thereby boosting the economy.

Keywords: container, ports, terminals, throughput

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Authors: Thanawat Chuleekiat

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Socketing of bored piles in rock is always seen as a matter of debate on construction sites between consultants and contractors. The socketing depth normally depends on the type of rock, depth at which the rock is available below the pile cap and load carrying capacity of the pile. In this paper, the review of field load test data of drilled shaft socketed in weathered limestone conducted using conventional static pile load test and dynamic pile load test was made to evaluate a unit shaft friction for the bored piles socketed in weathered limestone (weak rock). The borehole drilling data were also reviewed in conjunction with the pile test result. In addition, the back-calculated unit shaft friction was reviewed against various empirical methods for bored piles socketed in weak rock. The paper concludes with an estimated ultimate unit shaft friction from the case study in Qatar for preliminary design.

Keywords: piled foundation, weathered limestone, shaft friction, rock socket, pile load test

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Authors: Abdu Zakari, Sai’d Jibril, Adoum A. Omar

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The leaves of Combretum molle was selected on the basis of its uses in folk medicine as insecticides. The leave extracts of Combretum molle was tested against the larvae of Artemia salina, i.e. Brine Shrimp Lethality Test (BST), Culex quinquefasciatus Say (Filaria disease vector) i.e. Larvicidal Test, using crude ethanol, n-hexane, chloroform, ethyl acetate, and methanol extracts. The methanolic extract proved to be the most effective in inducing complete lethality at minimum doses both in the BST and the Larvicidal activity test. The LC50¬ values obtained are 24.85 µg/ml and 0.4µg/ml respectively. The bioactivity-guided column chromatography afforded the pure compound ACM–3. ACM-3 was not active in the BST with LC50 value >1000µg/ml, but was active in the Larvicidal activity test with LC50 value 4.0µg/ml. ACM-3 was proposed to have the structure I, (Cholesta-β-D-Glucopyranoside).

Keywords: toxicity, larvicidal, Combretum molle, Artemia salina, Culex quinquefasciatus Say.

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Authors: Mustafa Gok, Sair Kahraman, Mustafa Fener

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In rock engineering applications, determining uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and basic index properties such as density, porosity, and water absorption is crucial for the design of both underground and surface structures. However, obtaining reliable samples for direct testing, especially from rocks that weather quickly and have low strength, is often challenging. In such cases, indirect methods provide a practical alternative to estimate the physical and mechanical properties of these rocks. In this study, tuff samples collected from the Cappadocia region (Nevşehir) in Turkey were subjected to indirect testing methods. Over 100 tests were conducted, using needle penetrometer index (NPI), point load strength index (PLI), and disc shear index (BPI) to estimate the uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), density, and water absorption index of the tuffs. The relationships between the results of these indirect tests and the target physical properties were evaluated using simple and multiple regression analyses. The findings of this research reveal strong correlations between the indirect methods and the mechanical properties of the tuffs. Both uniaxial compressive strength and Brazilian tensile strength could be accurately predicted using NPI, PLI, and BPI values. The regression models developed in this study allow for rapid, cost-effective assessments of tuff strength in cases where direct testing is impractical. These results are particularly valuable for geological engineering applications, where time and resource constraints exist. This study highlights the significance of using indirect methods as reliable predictors of the mechanical behavior of weak rocks like tuffs. Further research is recommended to explore the application of these methods to other rock types with similar characteristics. Further research is required to compare the results with those of established direct test methods.

Keywords: brazilian tensile strength, disc shear strength, indirect methods, tuffs, uniaxial compressive strength

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Authors: Barry D. Kyle, Jessica Boyd, Robin Pickersgill, Nicole Squires, Cynthia Balion

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Background-Aim: Fentanyl is a highly-potent synthetic μ-opioid receptor agonist used for exceptional pain management. Its main metabolite, norfentanyl, is typically present in urine at significantly high concentrations (i.e. ~20%) representing an effective targeting molecule for immunoassay detection. Here, we evaluated the NCS^TM One Step Fentanyl Test Device© and the BTNX Rapid Response^TM Single Drug Test Strip© point of care (POC) test strips targeting norfentanyl (20 ng/ml) and fentanyl (100 ng/ml) molecules for potential risperidone interference. Methods: POC tests calibrated against norfentanyl (20 ng/ml) used [immunochromatographic] lateral flow devices to provide qualitative results within five minutes of urine sample contact. Results were recorded as negative if lines appeared in the test and control regions according to manufacturer’s instructions. Positive results were recorded if no line appeared in the test region (i.e., control line only visible). Pooled patient urine (n=20), that screened negative for drugs of abuse (using NCS One Step Multi-Line Screen) and fentanyl (using BTNX Rapid Response Strip) was used for spiking studies. Urine was spiked with risperidone alone and with combinations of fentanyl, norfentanyl and/or risperidone to evaluate cross-reactivity in each test device. Results: A positive screen result was obtained when 8,000 ng/mL of risperidone was spiked into drug free urine using the NCS test device. Positive screen results were also obtained in spiked urine samples containing fentanyl and norfentanyl combinations below the cut-off concentrations when 4000 ng/mL risperidone was present using the NCS testing device. There were no screen positive test results using the BTNX test strip with up to 8,000 ng/mL alone or in combination with concentrations of fentanyl and norfentanyl below the cut-off. Both devices screened positive when either fentanyl or norfentanyl exceeded the cut-off threshold in the absence and presence of risperidone. Conclusion: We report that urine samples containing risperidone may give a false positive result using the NCS One Step Fentanyl Test Device.

Keywords: fentanyl, interferences, point of care test, Risperidone

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Authors: İsmail İnce

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The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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Authors: Rakesh C. Mathad, G. Y. Lokesh, Basavegowda

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In agriculture using quality seeds of improved varieties is very important to ensure higher productivity thereby food security and sustainability. To ensure good productivity, seeds should have characters as described by the breeder. To know whether the characters as described by the breeder are expressing in a variety such as genuineness or genetic purity, field grow out test (GOT) is done. In pigeon pea which is long durational crop, conducting a GOT may take very long time and expensive also. Since in pigeon pea flower character is a most distinguishing character from the contaminants, conducting a field grow out test require 120-130 days or till flower emergence, which may increase cost of storage and seed production. This will also delay the distribution of seed inventory to the pigeon pea growing areas. In this view during 2014-15 with financial support of Govt. of Karnataka, India, a project to develop a molecular genetic test for newly developed variety of pigeon pea cv.TS3R was commissioned at Seed Unit, UAS, Raichur. A molecular test was developed with the help SSR markers to identify pure variety from possible off types in newly released pigeon pea variety TS3R. In the investigation, 44 primer pairs were screened to identify the specific marker associated with this variety. Pigeon pea cv. TS3R could be clearly identified by using the primer CCM 293 based on the banding pattern resolved on gel electrophoresis and PCR reactions. However some of the markers like AHSSR 46, CCM 82 and CCM 57 can be used to test other popular varieties in the region like Asha, GRG-811 and Maruti respectively. Further to develop this in to a lab test, the seed sample size was standardized to 200 seeds and a grow out matrix was developed. This matrix was used to sample 12 days old leaves to extract DNA. The lab test results were validated with actual field GOT test results and found variations within the acceptable limit of 1%. This molecular method can now be employed to test the genetic purity in pigeon pea cv TS3R which reduces the time and can be a cheaper alternative method for field GOT.

Keywords: genuineness, grow-out matrix, molecular genetic purity, SSR markers

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

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Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: Babatunde Akeem Lawal

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In any organization, the primary aim is to maximize profit, but the major challenges facing them is the increase in cost of operation because of this there is increase in cost of production that could lead to inevitable cost control and cost reduction scheme which make it difficult for most organizations to operate at the cost efficient frontier. The study aims to critically examine and evaluate the application of cost control and cost reduction in organization performance and also to review budget as an effective tool of cost control and cost reduction. A descriptive survey research was adopted. A total number of 40 respondent retrieved were used for the study. The analysis of data collected was undertaken by applying appropriate statistical tools. Regression analysis was used to test the hypothesis with the use of SPSS. Based on the findings; it was evident that cost control has a positive impact on organizational performance and also the style of management has a positive impact on organizational performance.

Keywords: organization, cost reduction, cost control, performance, budget, profit

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Authors: Jaemoon Lim

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To construct the lumped spring-mass model considering the occupants for the offset frontal crash, the SISAME software and the NHTSA test data were used. The data on 56 kph 40% offset frontal vehicle to deformable barrier crash test of a MY2007 Mazda 6 4-door sedan were obtained from NHTSA test database. The overall behaviors of B-pillar and engine of simulation models agreed very well with the test data. The trends of accelerations at the driver and passenger head were similar but big differences in peak values. The differences of peak values caused the large errors of the HIC36 and 3 ms chest g’s. To predict well the behaviors of dummies, the spring-mass model for the offset frontal crash needs to be improved.

Keywords: chest g’s, HIC36, lumped spring-mass model, offset frontal impact, SISAME

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Authors: Svetlana Pushkar

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Eco-indicator 99 (EI99) considers fundamental life cycle assessment (LCA) uncertainties via egalitarian/egalitarian (e/e), hierarchist/hierarchist (h/h), individualist/individualist (i/i), individualist/average (i/a), egalitarian/average (e/a), and hierarchist/average (h/a) methodological options. The objective of this study is to provide a reliable two-stage nested mixed balanced Analysis of Variance (ANOVA) test as a supplemental test to EI99 to address the problematic combination of similarly and not similarly produced materials usually found in building technologies. The robustness of the test was determined from both the “EI99 (all options)” stage (including e/e, i/i, h/h, e/a, i/a, and h/a - all methodological options) and the “EI99 (perspectives)” stage (including e/e, i/i, and h/h methodological options of EI99 - the methodological options with their particular weighting set or e/a, i/a, and h/a methodological options of EI99 - the methodological options with the average weighting set) of evaluating building technologies.

Keywords: building technologies, LCA uncertainty, Eco-indicator 99, two-stage nested mixed ANOVA test

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Authors: Naushad Mamode Khan

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The Com-Poisson (CMP) model is one of the most popular discrete generalized linear models (GLMS) that handles both equi-, over- and under-dispersed data. In longitudinal context, an integer-valued autoregressive (INAR(1)) process that incorporates covariate specification has been developed to model longitudinal CMP counts. However, the joint likelihood CMP function is difficult to specify and thus restricts the likelihood based estimating methodology. The joint generalized quasilikelihood approach (GQL-I) was instead considered but is rather computationally intensive and may not even estimate the regression effects due to a complex and frequently ill conditioned covariance structure. This paper proposes a new GQL approach for estimating the regression parameters (GQLIII) that are based on a single score vector representation. The performance of GQL-III is compared with GQL-I and separate marginal GQLs (GQL-II) through some simulation experiments and is proved to yield equally efficient estimates as GQL-I and is far more computationally stable.

Keywords: longitudinal, com-Poisson, ill-conditioned, INAR(1), GLMS, GQL

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Authors: Sadeq Al Yaari, Nassr Almaflehi, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari

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Background: Assessment of language-related functional activities (ALFA) is of vital importance in assessing aphasics’ performance of both sexes. However, the validity and reliability of this language therapeutic test has never been validated in the Arabic medical literature. Purpose: The aim of this study was to validate the test by assessing the language-related functional activities of 100 gender aphasics based in a medical faculty. Design: ALFA Pre-and-posttest was administered twice in three weeks to test the language-related functional activities of 100 gender aphasics. Settings: Al Khars hospital in Al Ahsa’a, Kingdom of Saudi Arabia (KSA). Participants: Sixteen to eight-year-old participants (N = 100 men and women) were enrolled in this experiment. Again, the purpose was to assess their language-related functional activities using ALFA. Procedures: The first step was to translate the English version of ALFA test into the mother tongue of the patients (Arabic). Secondly, the translated text is reviewed and edited by three specialists of Arabic language. Having the test standardized, the third step was to assess language-related functional activities of the participants in natural environment. Assessment took place in three weeks. In the first week, a pre-test was administered to the participants at hand and after two weeks, a post-test was administered to identify whether or not significant differences between the two tests (pre-and-posttest) could be observed. Interventions: Outcomes of the results obtained from the analyses were broadly discussed. Linguistic and statistical comparisons were held to illustrate the findings of this study. Main outcomes and Results: The analysis of the obtained results indicated that the performance of the aphasic participants in the post-test did not differ from that of the pre-test (, respectively). Conclusions & Implications: ALFA was proved to be a valid and reliable test. Moreover, outlined results pointed out the importance of assessing not only gender aphasics’ language, but also their language-related functional activities. Further research is needed to explore how gender aphasics’ verbal and non-verbal performances interact.

Keywords: ALFA, language test, Arab aphasics, validity, reliability, psychoneurolinguistics.

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Authors: Marji Umil, Miane Karyle Urolaza, Ian Winston Dale Uy, John Charle Magne Valdez, Karen Elizabeth Valdez, Ervin Charles Valencia, Cheryleen Tan-Chua

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Objective: Distraction techniques can be successful in reducing the anxiety of children during medical procedures. Dental procedures, in particular, are associated with dental anxiety which has been identified as a significant and common problem in children, however, only limited studies were conducted to address such problem. Thus, this study determined the effectiveness of computer video games on the levels of anxiety of children between 5-12 years old scheduled for tooth extraction. Methods: A pre-test post-test quasi-experimental study was conducted involving 30 randomly-assigned subjects, 15 in the experimental and 15 in the control. Subjects in the experimental group played computer video games for a maximum of 15 minutes, however, no intervention was done on the control. The modified Yale Pre-operative Anxiety Scale (m-YPAS) with a Cronbach’s alpha of 0.9 was used to assess anxiety at two different points: upon arrival in the clinic (pre-test anxiety) and 15 minutes after the first measurement (post-test anxiety). Paired t-test and ANCOVA were used to analyze the gathered data. Results: Results showed that there is a significant difference between the pre-test and post-test anxiety scores of the control group (p=0.0002) which indicates an increased anxiety. A significant difference was also noted between the pre-test and post-test anxiety scores of the experimental group (p=0.0002) which indicates decreased anxiety. Comparatively, the experimental group showed lower anxiety score (p=<0.0001) than the control. Conclusion: The use of computer video games is effective in reducing the pre-operative anxiety among children and can be an alternative non-pharmacological management in giving pre-operative care.

Keywords: play therapy, preoperative anxiety, tooth extraction, video games

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Authors: Jerry Fiave, Dacosta Aboagye, Stephen Ayisi-Addo, Mabel Kissiwah Asafo, Felix Osei-Sarpong, Ebenezer Kye-Mensah, Renee Opare-Otoo

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Background: Acceptability and preference of social and behaviour change (SBC) materials by target audiences is an important determinant of effective health communication outcomes. In Ghana, however, pre-test and post-test studies on acceptability and preference of specific SBC materials for specific audiences are rare. The aim of this study was therefore to assess the acceptability and preference of printed posters on COVID-19 related stigma as suitable SBC materials for health workers to influence behaviours that promote uptake of HIV-focused services. Methods: A total of 218 health workers who provide HIV-focused services were purposively sampled in 16 polyclinics where the posters were distributed in the Greater Accra region of Ghana. Data was collected in March 2021 using an adapted self-administered questionnaire in Google forms deployed via WhatsApp to participants. The data were imported into SPSS version 27 where chi-square test and regression analyses were performed to establish association as well as strength of association between variables respectively. Results: A total of 142 participants (physicians, nurses, midwives, lab scientists, health promoters, diseases control officers) made up of 85(60%) females and 57(40%) males responded to the questionnaire, giving a response rate of 65.14%. Only 88 (61.97%) of the respondents were exposed to the posters. The majority of those exposed said the posters were informative [82(93.18%)], relevant [85(96.59%)] and attractive [83(94.32%)]. They [82(93.20%)] also rated the material as acceptable with no statistically significant association between category of health worker and acceptability of the posters (X =1.631, df=5, p=0.898). However, participants’ most preferred forms of material on COVID-19 related stigma were social media [38(26.76%)], television [33(23.24%)], SMS [19(13.38%)], and radio [18(12.70%)]. Clinical health workers were 4.88 times more likely to prefer online or electronic versions of SBC materials than nonclinical health workers [AOR= 4.88 (95% CI= 0.31-0.98), p=0.034]. Conclusions: Printed posters on COVID-19 related stigma are acceptable SBC materials in communicating behaviour change messages that target health workers in promoting uptake of HIV-focused services. Posters are however, not among the most preferred materials for health workers. It is therefore recommended that material assessment studies are conducted to inform the development of acceptable and preferred materials for target audiences.

Keywords: acceptability, AIDS, HIV, posters, preference, SBC, stigma, social and behaviour change communication

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Authors: Abdulmagid A. Khattabi, Ahmed A. Hablus, Osama Ab. M. Shafah

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The goal of this work is to understand how the thermal influence of combustion chamber deposits can be utilized to expand the operating range of HCCI combustion. In order to do this, two main objectives must first be met; tracking deposit formation trends in an HCCI engine and determining the sensitivity of HCCI combustion to CCD. This requires testing that demonstrates the differences in combustion between a clean engine and one with deposits coating the chamber. This will involve a long-term test that tracks the effects of CCD on combustion. The test will start with a clean engine. One baseline HCCI operating point is maintained for the duration of the test during which gradual combustion chamber deposit formation will occur. Combustion parameters, including heat release rates and emissions will be tracked for the duration and compared to the case of a clean engine. This work will begin by detailing the specifics of the test procedure and measurements taken throughout the test. Then a review of the effects of the gradual formation of deposits in the engine will be given.

Keywords: fuels, fuel atomization, pattern factor, alternate fuels combustion, efficiency gas turbine combustion, lean blow out, exhaust and liner wall temperature

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Authors: Seyed Sadegh Naseralavi, Najmeh Bemani

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In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.

Keywords: adaptive neuro fuzzy inference system, anticipate method, artificial neural network, concrete design code, multi-variable regression

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Authors: Eyup Dogan

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The number of research articles analyzing the integration properties of energy variables has rapidly increased in the energy literature for about a decade. The stochastic behaviors of energy variables are worth knowing due to several reasons. For instance, national policies to conserve or promote energy consumption, which should be taken as shocks to energy consumption, will have transitory effects in energy consumption if energy consumption is found to be stationary in one country. Furthermore, it is also important to know the order of integration to employ an appropriate econometric model. Despite being an important subject for applied energy (economics) and having a huge volume of studies, several known limitations still exist with the existing literature. For example, many of the studies use aggregate energy consumption and national level data. In addition, a huge part of the literature is either multi-country studies or solely focusing on the U.S. This is the first study in the literature that considers a form of energy consumption by sectors at sub-national level. This research study aims at investigating unit root properties of electricity consumption for 12 regions of Turkey by four sectors in addition to total electricity consumption for the purpose of filling the mentioned limits in the literature. In this regard, we analyze stationarity properties of 60 cases . Because the use of multiple unit root tests make the results robust and consistent, we apply Dickey-Fuller unit root test based on Generalized Least Squares regression (DFGLS), Phillips-Perron unit root test (PP) and Zivot-Andrews unit root test with one endogenous structural break (ZA). The main finding of this study is that electricity consumption is trend stationary in 7 cases according to DFGLS and PP, whereas it is stationary process in 12 cases when we take into account the structural change by applying ZA. Thus, shocks to electricity consumption have transitory effects in those cases; namely, agriculture in region 1, region 4 and region 7, industrial in region 5, region 8, region 9, region 10 and region 11, business in region 4, region 7 and region 9, total electricity consumption in region 11. Regarding policy implications, policies to decrease or stimulate the use of electricity have a long-run impact on electricity consumption in 80% of cases in Turkey given that 48 cases are non-stationary process. On the other hand, the past behavior of electricity consumption can be used to predict the future behavior of that in 12 cases only.

Keywords: unit root, electricity consumption, sectoral data, subnational data

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Authors: Neha Ahirwar

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In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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Authors: T. Nakkeran, C. Dhamodharan, Win Myint Soe , Ramasamy Deverajan, M. Ganesh Babu

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This manuscript presents the results of an experimental investigation performed to study the material and mechanical properties of two weld joints fabricated within close proximity. The experiment was designed using welded S355 D Z35 with distances between two parallel adjacent weld toes at 8 mm. These distances were less than the distance that has normally been recommended in standards, codes, and specifications. The main idea of the analysis is to determine any significant effects when welding the joints with the close proximity of 8mm using the SAW welding process of the one joint with high heat put and one joint welded with the FCAW welding process and evaluating the destructing and nondestructive testing between the welded joints. Further, we have evaluated the joints with Mechanical Testing for evaluating by performing Tensile test, bend testing, Macrostructure, Microstructure, Hardness test, and Impact testing. After evaluating the final outcome of the result, no significant changes were observed for welding the close proximity of weld of 8mm distance between the joints as compared to the specification minimum distance between the weldments of any design should be 50mm.

Keywords: S355 carbon steel, weld proximity, SAW process, FCAW process, heat input, bend test, tensile test, hardness test, impact test, macro and microscopic examinations

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Authors: Harrison Gideon Maghra

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The study was conducted on the challenges in the use of ICT in Agricultural Education and Training in Colleges of Education in Adamawa State. Three objectives guided the study, and the objectives were translated into three research questions and the research questions translated into two null hypotheses. Frequency and percentage were used to answer research question one, mean and standard deviation were used to answer research questions two and three, and t-test statistic was used to test the null hypotheses at 0.05 level of significance. The study was descriptive research and a questionnaire was used to solicit responses from the respondent. The instrument for data collection was subjected to face and content validity by 1 expert in the Department of Vocational Education, Modibbo Adama University, Yola and 3 experts from the Department of Vocational and Technical Education, Adamawa State University, Mubi. Pearson Product Moment Correlation Coefficient was used to test the reliability of the instrument and a reliability coefficient of 0.76 was obtained through the test re-test test method. Results from the study revealed that ICT facilities are not available in state-owned colleges of education. Agricultural Education lecturers have a positive attitude toward the use of ICT in teaching agricultural education and training. Based on the findings of the study, recommendations were made, among which: Colleges of Education in the state should organize training on the use of ICT for all lecturers, including those in the Agricultural Education program.

Keywords: challenges, ICT, agricultural education, colleges of education

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Authors: Donna H. Gabor

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This study aimed to develop and validate an electronic module in physics for first-year college students of Iloilo and find out if there would be a significant difference in the performance of students before and after using the electronic module. The e-module was composed of one topic with two sub-lessons in linear motion (kinematics). The participants of the study were classified into three groups: the subject matter experts who are physics instructors who suggested the content, physical appearance, and limitations of the e-module; the IT experts who are active both in teaching and developing computer programs; and 28 students divided into two groups, 15 in the pilot group and 13 in the final test group. A researcher created 30 items checklist form (difficulty of a sample problem, comprehension, application, and definition of terms) was prepared and validated by the experts in subject matter for gathering data. To test the difference in student performance in physics, the researcher prepared an achievement test containing 25 items, multiple choices. The findings revealed that there was an increase in the performance of students in the pretest and post-test. T-test results revealed that there was a significant difference in the test scores of the students before and after using the module which can be used as a future reference for linear motion as an additional teaching tool in physics.

Keywords: electronic module, kinematics, linear motion, physics

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Priyanka Sharma

Abstract:

The women voter turnout in India is increasing. The rising female voter turnout is explained in part by men intimidating women in the household to vote. Women are more likely than men to be guided before voting. What is perhaps more significant is that the gender gap has shrunk significantly over the years. However, there are layers and categories of women voters in India. Some women are much more likely than the average woman to follow advice. Against this backdrop, this paper investigates the variation among women voters during the national elections of 2019 in India. The central question of this research paper is whether or not the development of greater political opinion among women would offset guided voting and allow them to emerge as more independent voters. So the independent variable of the study is Indian women’s opinion on politics, and the dependent variable is their voting behavior. The methodology used in this paper is both quantitative and qualitative. This study investigated and examined Lokniti’s election survey data. The sample size used in this survey is 11568. The analysis of this study has revealed that there is a considerable impact of women having a political opinion on their voting behavior. The Bivariate analysis of the variables states that 83% of Indian women who have opinions on political issues do not seek advice while going to vote. This proves the hypothesis of this paper that women with an opinion on politics are more likely to be independent voters. To check the statistical significance of the finding, a chi-square test was done and the p-value found is 0.009737, which shows it is statistically significant. Furthermore, a regression test has been done by controlling certain variables like age, educational qualification, caste, and financial position of the women to probe the influence on the dependent variable. The findings provide worthwhile insights into the relationship between these control variables and the women voting behavior in India.

Keywords: dependent voter, independent voter, political opinion, voting behavior, women voter

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