Search results for: Consumer Price Index

Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: artificial neural network, load estimation, regional survey, rural electrification

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Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu

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First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.

Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model

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Authors: Dekie Rawung, Abdul L. Abadi, Toto Himawan, Siegfried Berhimpon

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A case study on consumer' knowledge, attitude, and behavior on food safety issue related to pesticide residues in cabbage was conducted in the area of Manado and Tomohon city, North Sulawesi. A sample of 150 consumers were selected randomly on location (open market and supermarket) while they were purchasing vegetables. The data on consumers’ perception, knowledge, attitude and behavior on food safety issue regarding pesticide residues were collected using a 5-point, two-section Likert-Scale questionnaire, and the relationship of knowledge, attitude, and behavior on food safety issues were analyzed using Structural Equation Modeling (SEM). It was found that, among many food safety issues, the illegal, non-food chemical preservatives were considered the most important one (by more than 35% respondents), followed by high cholesterol content and textile coloring chemical (> 27% respondents). The pesticide residues issue was only in the 4th place. The same results were seen on the issue of quality factors that determine the product selection during purchasing. The pesticide-free and organic products labels were considered much less important quality factors as compared with freshness and nutrition value which were considered the most and the second most important quality factors (almost 65% of respondents). SEM analysis showed that only knowledge and attitude on food safety that had the significant relation (coefficient value of 0.38), whereas those with behaviors were not significant.

Keywords: cabbage, consumer, food safety, pesticide residues

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Authors: Patel Darshan Shaileshkumar, M. G. Vanza

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Black cotton soil is problematic soil for any construction work. Black cotton soil contains montmorillonite in its structure. Due to this mineral, black cotton soil will attain maximum swelling and shrinkage. Due to these volume changes, it is necessary to stabilize black cotton soil before the construction of the road. For soil stabilization use of pozzolanic waste is found to be a good solution by some researchers. The palm kernel shell ash (PKSA) is a pozzolanic material that can be used for soil stabilization. Basically, PKSA is a waste material, and it is available at a cheap cost. Palm kernel shell is a waste material generated in palm oil mills. Then palm kernel shell is used in industries instead of coal for power generation. After the burning of a palm kernel shell, ash is formed; the ash is called palm kernel shell ash (PKSA). The PKSA contains a free lime content that will react chemically with the silicate and aluminate of black cotton soil and forms a C-S-H and C-A-H gel which will bines soil particles together and reduce the plasticity of the soil. In this study, the PKSA is added to the soil. It was found that with the addition of PKSA content in the soil, the liquid limit of the soil is decreased, the plastic limit of the soil is increased, and the plasticity of the soil is decreased. The group index value of the soil is evaluated, and it was found that with the addition of PKSA GI value of the soil is decreased, which indicates the strength of the soil is improved.

Keywords: palm kernel shell ash, black cotton soil, liquid limit, group index, plastic limit, plasticity index

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Authors: Simon Ayorinde Okanlawon

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This study examines residents’ assessment of with infrastructural facilities in the urban fringe of Ibadan, Nigeria. Random sampling technique was used in selecting four Local Government Areas out of the six suburban LGAs of the city. Google earth and ground trotting were used in capturing and selecting seven hundred and forty-two new houses. The questionnaires administered on house owners were harvested on the spot. The information collected includes socio-economic and demographic characteristics of residents as well as characteristics of infrastructural facilities. The study utilised both descriptive and inferential statistical analyses; Facility Availability Index (FAI) Facility Functionality Index (FFI) and Residents’ Satisfactions Index (RSI) were used to compare respectively residents’ perceived levels of availability of, the functionality of, and satisfaction with facilities across Local Government Areas. The study shows that levels of both availability of, and satisfaction with infrastructural facilities are low with respective overall FAI (0.8) and RSI (0.05), while the functionality of the facilities is generally very poor IFFI = - 0.58). Strategies were proposed to enhance the good, livable, and healthy environment.

Keywords: infrastructural facilities, infrastructural perception index, residents’ satisfaction, urban fringe of Ibadan

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Authors: Nour Mohamad Fayad

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Complex and extensively researched, the impact of corruption on economic growth seems to be intricate. Many experts believe that corruption reduces economic development. However, counterarguments have suggested that corruption either promotes growth and development or has no significant impact on economic performance. Clearly, there is no consensus in the economics literature regarding the possible relationship between corruption and economic development. Corruption's complex and clandestine nature, which makes it difficult to define and measure, is one of the obstacles that must be overcome when investigating its effect on an economy. In an attempt to contribute to the ongoing debate, this study examines the impact of corruption on economic growth in the Middle East and North Africa (MENA) region between 2000 and 2021 using a Customized Corruption Index-CCI and panel data on MENA countries. These countries were selected because they are understudied in the economic literature, and despite the World Bank's recent emphasis on corruption in the developing world, the MENA countries have received little attention. The researcher used Cobb-Douglas functional form to test corruption in MENA using a customized index known as Customized Corruption Index-CCI to track corruption over almost 20 years, then used the dynamic panel data. The findings indicate that there is a positive correlation between corruption and economic growth, but this is not consistent across all MENA nations. First, the relatively recent lack of data from MENA nations. This issue is related to the inaccessibility of data for many MENA countries, particularly regarding the returns on resources, private malfeasance, and other variables in Gulf countries. In addition, the researcher encountered several restrictions, such as electricity and internet outages, due to the fact that he is from Lebanon, a country whose citizens have endured difficult living conditions since the Lebanese crisis began in 2019. Demonstrating a customized index known as Customized Corruption Index-CCI that suits the characteristics of MENA countries to peculiarly measure corruption in this region, the outcome of the Customized Corruption Index-CCI is then compared to the Corruption Perception Index-CPI and Control of Corruption from World Governance Indicator-CC from WGI.

Keywords: corruption, economic growth, corruption measurements, empirical review, impact of corruption

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Authors: Hung-Chu Chen, Han Qi, Bauke de Vries

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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.

Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics

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Authors: Shih-Pin Chen, Shih-Syuan You

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Fuzzy regression models are useful for investigating the relationship between explanatory variables and responses in fuzzy environments. To overcome the deficiencies of previous models and increase the explanatory power of fuzzy data, the graded mean integration (GMI) representation is applied to determine representative crisp regression coefficients. A fuzzy regression model is constructed based on the modified dissemblance index (MDI), which can precisely measure the actual total error. Compared with previous studies based on the proposed MDI and distance criterion, the results from commonly used test examples show that the proposed fuzzy linear regression model has higher explanatory power and forecasting accuracy.

Keywords: dissemblance index, fuzzy linear regression, graded mean integration, mathematical programming

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Authors: Karim Kootahi, Seyed Abolhasan Naeini

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The soil-water characteristic curve (SWCC), which represents the relationship between suction and water content (or degree of saturation), is an important property of unsaturated soils. The conventional method for determining SWCC is through specialized testing procedures. Since these procedures require specialized unsaturated soil testing apparatus and lengthy testing programs, several index properties-based correlations have been developed for estimating the SWCC of fine-grained soils. There are, however, considerable inconsistencies among the published correlations and there is no validation study on the predictive ability of existing correlations. In the present study, all existing index properties-based correlations are evaluated using a high quality worldwide database. The performances of existing correlations are assessed both graphically and quantitatively using statistical measures. The results of the validation indicate that most of the existing correlations provide unacceptable estimates of degree of saturation but the most recent model appears to be promising.

Keywords: SWCC, correlations, index properties, validation

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Authors: Yeliz Mert Kantar, İsmail Yeni̇lmez, Ibrahim Arik

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In this study, the efficiency measurement of the top fifty Turkish Universities has been conducted. The top fifty Turkish Universities are listed by The Scientific and Technological Research Council of Turkey (TÜBITAK) according to the Entrepreneur and Innovative University Index every year. The index is calculated based on four components since 2018. Four components are scientific and technological research competency, intellectual property pool, cooperation and interaction, and economic and social contribution. The four components consist of twenty-three sub-components. The 2021 list announced in January 2022 is discussed in this study. Efficiency analysis have been carried out using the Stochastic Frontier Model. Statistical significance of the sub-components that make up the index with certain weights has been examined in terms of the efficiency measurement calculated through the Stochastic Frontier Model. The relationship between the efficiency ranking estimated based on the Stochastic Frontier Model and the Entrepreneur and Innovative University Index ranking is discussed in detail.

Keywords: efficiency, entrepreneur and innovative universities, turkish universities, stochastic frontier model, tübi̇tak

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Authors: Hidefumi Kawakatsu, Dong Li, Kosuke Kato

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In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.

Keywords: amelioration, deterioration, small sized poultry farmers, optimal price

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Authors: R. Bouhennache, T. Bouden, A. A. Taleb, A. Chaddad

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In this paper we propose a method to map the urban areas. The method uses an arithmetic calculation processed from the land features indexes and Tasseled cap transformation TC of multi spectral Thematic Mapper Landsat TM image. For this purpose the derived indexes image from the original image such SAVI the soil adjusted vegetation index, UI the urban Index, and EBBI the enhanced built up and bareness index were staked to form a new image and the bands were uncorrelated, also the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification approaches were first applied on the new image TM data using the reference spectra of the spectral library and subsequently the four urban, vegetation, water and soil land cover categories were extracted with their accuracy assessment.The urban features were represented using a logic calculation applied to the brightness, UI-SAVI, NDBI-greenness and EBBI- brightness data sets. The study applied to Blida and mentioned that the urban features can be mapped with an accuracy ranging from 92 % to 95%.

Keywords: EBBI, SAVI, Tasseled Cap Transformation, UI

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Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

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Authors: Nicola Rubino

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This paper presents an analysis of a group of commodity exporting countries' nominal exchange rate movements in relationship to the US dollar. Using a series of Unrestricted Self-exciting Threshold Autoregressive models (SETAR), we model and evaluate sixteen national CPI price differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is evaluated through calculation of mean absolute error measures on the basis of two-hundred and fifty-three months rolling window forecasts and extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive non linear autoregressive model (AAR) and a simple linear Neural Network model (NNET). Our preliminary results confirm presence of some form of TAR non linearity in the majority of the countries analyzed, with a relatively higher goodness of fit, with respect to the linear AR(1) benchmark, in five countries out of sixteen considered. Although no model appears to statistically prevail over the other, our final out-of-sample forecast exercise shows that SETAR models tend to have quite poor relative forecasting performance, especially when compared to alternative non-linear specifications. Finally, by analyzing the implied half-lives of the > coefficients, our results confirms the presence, in the spirit of arbitrage band adjustment, of band convergence with an inner unit root behaviour in five of the sixteen countries analyzed.

Keywords: transition regression model, real exchange rate, nonlinearities, price differentials, PPP, commodity points

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Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: Sukhbaatar Dorj, Erdenebaatar Altangerel

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As alternative to existing e-government measuring models, here proposed a new customer centric, service oriented, simple approach for measuring countries e-Governments. If successfully implemented, built infrastructure will provide a single e-government index number for countries. Main schema is as follows. Country CIO or equal position government official, at the beginning of each year will provide to United Nations dedicated web site 4 numbers on behalf of own country: 1) Ratio of available online public services, to total number of public services, 2) Ratio of interagency inter ministry online public services to total number of available online public services, 3) Ratio of total number of citizen and business entities served online annually to total number of citizen and business entities served annually online and physically on those services, 4) Simple index for geographical spread of online served citizen and business entities. 4 numbers then combined into one index number by mathematical Average function. In addition to 4 numbers 5th number can be introduced as service quality indicator of online public services. If in ordering of countries index number is equal, 5th criteria will be used. Notice: This approach is for country’s current e-government achievement assessment, not for e-government readiness assessment.

Keywords: countries e-government index, e-government, infrastructure for measuring e-government, measuring e-government

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Authors: Mathewos Temesgen, Lemi Geleta

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Lake Koka is one of the Ethiopian Central Rift Valleys lakes, where the absorbance of domestic, agricultural, and industrial waste from the nearby industrial and agro-industrial activities is very common. The aim of this research was to assess the heavy metal bioaccumulation in edible parts of common carp (Cyprinus carpio) in Lake Koka and the health risks associated with the dietary intake of the fish. Three sampling sites were selected randomly for primary data collection. Physicochemical parameters (pH, Total Dissolved Solids, Dissolved Oxygen and Electrical Conductivity) were measured in-situ. Four heavy metals (Cd, Cr, Pb, and Zn) in water and bio-accumulation in the edible parts of the fish were analyzed with flame atomic absorption spectrometry. The mean values of TDS, EC, DO and pH of the lake water were 458.1 mg/L, 905.7 µ s/cm, 7.36 mg/L, and 7.9, respectively. The mean concentrations of Zn, Cr, and Cd in the edible part of fish were also 0.18 mg/kg, ND-0.24 mg/kg, and ND-0.03 mg/kg, respectively. Pb was, however, not identified. The amount of Cr in the examined fish muscle was above the level set by FAO, and the accumulation of the metals showed marked differences between sampling sites (p<0.05). The concentrations of Cd, Pb and were below the maximum permissible limit. The results also indicated that Cr has a high transfer factor value and Zn has the lowest. The carcinogenic hazard ratio values were below the threshold value (<1) for the edible parts of fish. The estimated weekly intake of heavy metals from fish muscles ranked as Cr>Zn>Cd, but the values were lower than the Reference Dose limit for metals. The carcinogenic risk values indicated a low health risk due to the intake of individual metals from fish. Furthermore, the hazard index of the edible part of fish was less than unity. Generally, the water quality is not a risk for the survival and reproduction of fish, and the heavy metal contents in the edible parts of fish exhibited low carcinogenic risk through the food chain.

Keywords: bio-accumulation, cyprinus carpio, hazard index, heavy metals, Lake Koka

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Authors: Ezgi Kaya, A. Dilek Maden

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A topological index is a number related to graph which is invariant under graph isomorphism. In theoretical chemistry, molecular structure descriptors (also called topological indices) are used for modeling physicochemical, pharmacologic, toxicologic, biological and other properties of chemical compounds. Let G be a graph with n vertices and m edges. For a given edge uv, the quantity nu(e) denotes the number of vertices closer to u than v, the quantity nv(e) is defined analogously. The vertex PI index defined as the sum of the nu(e) and nv(e). Here the sum is taken over all edges of G. The energy of a graph is defined as the sum of the eigenvalues of adjacency matrix of G and the Laplacian energy of a graph is defined as the sum of the absolute value of difference of laplacian eigenvalues and average degree of G. In theoretical chemistry, the π-electron energy of a conjugated carbon molecule, computed using the Hückel theory, coincides with the energy. Hence results on graph energy assume special significance. The Laplacian matrix of a graph G weighted by the vertex PI weighting is the Laplacian vertex PI matrix and the Laplacian vertex PI eigenvalues of a connected graph G are the eigenvalues of its Laplacian vertex PI matrix. In this study, Laplacian vertex PI energy of a graph is defined of G. We also give some bounds for the Laplacian vertex PI energy of graphs in terms of vertex PI index, the sum of the squares of entries in the Laplacian vertex PI matrix and the absolute value of the determinant of the Laplacian vertex PI matrix.

Keywords: energy, Laplacian energy, laplacian vertex PI eigenvalues, Laplacian vertex PI energy, vertex PI index

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Authors: Palwinder Bhatia

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As all know new media is a broad term in media studies that emerged in the latter part of the 20th century which refers to on-demand access to content any time, anywhere, on any digital device, as well as interactive user feedback, creative participation and community formation around the media content. The role of new media in advertisement is impeccable these days. It becomes the cheap and best way of advertising. Another important promise of new media is the democratization of the creation, publishing, distribution and consumption of media content. New media brings a revolution in about every field. It makes bridge between customer and companies. World make a global village with the only help of new media. Advertising helps in shaping the consumer behavior and effect on consumer psychology, sociology, social anthropology and economics. People do comments and like the particular brands on the networking sites which create mesmerism impact on the behavior of customer. Recent study did by Times of India shows that 64% of Facebook users have liked a brand on Facebook.

Keywords: film, visual, culture, media, advertisement

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Authors: Badr A. Al-Jehani

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Nowadays, contractor selection is a critical activity of the project owner. Selecting the right contractor is essential to the project manager for the success of the project, and this cab happens by using the proper selecting method. Traditionally, the contractor is being selected based on his offered bid price. This approach focuses only on the price factor and forgetting other essential factors for the success of the project. In this research paper, the Analytic Network Process (ANP) method is used as a decision tool model to select the most appropriate contractor. This decision-making method can help the clients who work in the construction industry to identify contractors who are capable of delivering satisfactory outcomes. Moreover, this research paper provides a case study of selecting the proper contractor among three contractors by using ANP method. The case study identifies and computes the relative weight of the eight criteria and eleven sub-criteria using a questionnaire.

Keywords: contractor selection, project management, decision-making, bidding

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Authors: Ilma Robo, Saimir Heta, Nedja Hysi, Vera Ostreni

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Introduction: Marginal gingivitis is a disease with considerable frequency among patients who present routinely for periodontal control and treatment. In fact, this disease may not have alarming symptoms in patients and may go unnoticed by themselves when personal hygiene conditions are optimal. The aim of this study was to collect retrograde data on the prevalence of marginal gingiva in the respective group of patients, evaluated according to specific periodontal diagnostic tools. Materials and methods: The study was conducted in two patient groups. The first group was with 34 patients, during December 2019-January 2020, and the second group was with 64 patients during 2010-2018 (each year in the mentioned monthly period). Bacterial plaque index, hemorrhage index, amount of gingival fluid, presence of xerostomia and candidiasis were recorded in patients. Results: Analysis of the collected data showed that susceptibility to marginal gingivitis shows higher values according to retrograde data, compared to cross-sectional ones. Susceptibility to candidiasis and the occurrence of xerostomia, even in the combination of both pathologies, as risk factors for the occurrence of marginal gingivitis, show higher values ​​according to retrograde data. The female are presented with a reduced bacterial plaque index than the males, but more importantly, this index in the females is also associated with a reduced index of gingival hemorrhage, in contrast to the males. Conclusions: Cross-sectional data show that the prevalence of marginal gingivitis is more reduced, compared to retrograde data, based on the hemorrhage index and the bacterial plaque index together. Changes in production in the amount of gingival fluid show a higher prevalence of marginal gingivitis in cross-sectional data than in retrograde data; this is based on the sophistication of the way data are recorded, which evolves over time and also based on professional sensitivity to this phenomenon.

Keywords: marginal gingivitis, cross-sectional, retrograde, prevalence

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Authors: P. Nayak, Shakeel Shaikh

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In this paper, we analyse the apparel export performance of Southeast Asian Nations (ASEAN) in the world market. The study covers the 2003-2012 period at the sector as well as product levels (6 digit HS) and analysis is based HS 2002 nomenclature. We measure export similarity among Southeast Asian nations for the apparel sector (two digit HS-61 & 62), besides analysing the products performance in the world through Revealed Comparative Advantage (RCA) technique. Coupled with RCA, the price as a factor of competitiveness was examined from the available Unit Value Realizations (UVR). Further to this, the resource availability or outsourced from the region was considered as an extension to the analysis of competitiveness between the nations. With the help of these methodologies, we examine the degree of competition between the exports of southeast nations in the world market. Our results show that Cambodia, Indonesia, Thailand, and Vietnam are well performing states within ASEAN. The paper further delves into sustainability of the export performing countries within ASEAN.

Keywords: export competitiveness, export similarity index, revealed comparative advantage, unit value realisation

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Authors: Kwok W. Mui, Ling T. Wong, Tsz W. Tsang

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Many Hong Kong people nowadays spend most of their lifetime working indoor. Since poor Indoor Air Quality (IAQ) potentially leads to discomfort, ill health, low productivity and even absenteeism in workplaces, a call for establishing statutory IAQ control to safeguard the well-being of residents is urgently required. Although policies, strategies, and guidelines for workplace IAQ diagnosis have been developed elsewhere and followed with remedial works, some of those workplaces or buildings have relatively late stage of the IAQ problems when the investigation or remedial work started. Screening for IAQ problems should be initiated as it will provide information as a minimum provision of IAQ baseline requisite to the resolution of the problems. It is not practical to sample all air pollutants that exit. Nevertheless, as a statutory control, reliable, rapid screening is essential in accordance with a compromise strategy, which balances costs against detection of key pollutants. This study investigates the feasibility of using an IAQ index as a parameter of IAQ control in Hong Kong. The index is a screening parameter to identify the unsatisfactory workplace IAQ and will highlight where a fully effective IAQ monitoring and assessment is needed for an intensive diagnosis. There already exist a number of representative common indoor pollutants based on some extensive IAQ assessments. The selection of pollutants is surrogate to IAQ control consists of dilution, mitigation, and emission control. The IAQ Index and assessment will look at high fractional quantities of these common measurement parameters. With the support of the existing comprehensive regional IAQ database and the IAQ Index by the research team as the pre-assessment probability, and the unsatisfactory IAQ prevalence as the post-assessment probability from this study, thresholds of maintaining the current measures and performing a further IAQ test or IAQ remedial measures will be proposed. With justified resources, the proposed IAQ Index and assessment protocol might be a useful tool for setting up a practical public IAQ surveillance programme and policy in Hong Kong.

Keywords: assessment, index, indoor air quality, surveillance programme

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Authors: Ismatilla Mardanov

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There are three types of countries, the first of which is willing to attract foreign direct investment (FDI) in enormous amounts and do whatever it takes to make this happen. Therefore, FDI pours into such countries. In the second cluster of countries, even if the country is suffering tremendously from the shortage of investments, the governments are hesitant to attract investments because they are at the hands of local oligarchs/cartels. Therefore, FDI inflows are moderate to low in such countries. The third type is countries whose companies prefer investing in the most efficient locations globally and are hesitant to invest in the homeland. Sorting countries into such clusters, the present study examines the essential institutions and economic factors that make these countries different. Past literature has discussed various determinants of FDI in all kinds of countries. However, it did not classify countries based on government motivation, institutional setup, and economic factors. A specific approach to each target country is vital for corporate foreign direct investment risk analysis and decisions. The research questions are 1. What specific institutional and economic factors paint the pictures of the three clusters; 2. What specific institutional and economic factors are determinants of FDI; 3. Which of the determinants are endogenous and exogenous variables? 4. How can institutions and economic and political variables impact corporate investment decisions Hypothesis 1: In the first type, country institutions and economic factors will be favorable for FDI. Hypothesis 2: In the second type, even if country economic factors favor FDI, institutions will not. Hypothesis 3: In the third type, even if country institutions favorFDI, economic factors will not favor domestic investments. Therefore, FDI outflows occur in large amounts. Methods: Data come from open sources of the World Bank, the Fraser Institute, the Heritage Foundation, and other reliable sources. The dependent variable is FDI inflows. The independent variables are institutions (economic and political freedom indices) and economic factors (natural, material, and labor resources, government consumption, infrastructure, minimum wage, education, unemployment, tax rates, consumer price index, inflation, and others), the endogeneity or exogeneity of which are tested in the instrumental variable estimation. Political rights and civil liberties are used as instrumental variables. Results indicate that in the first type, both country institutions and economic factors, specifically labor and logistics/infrastructure/energy intensity, are favorable for potential investors. In the second category of countries, the risk of loss of assets is very high due to governmentshijacked by local oligarchs/cartels/special interest groups. In the third category of countries, the local economic factors are unfavorable for domestic investment even if the institutions are well acceptable. Cluster analysis and instrumental variable estimation were used to reveal cause-effect patterns in each of the clusters.

Keywords: foreign direct investment, economy, institutions, instrumental variable estimation

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Authors: S. Murr, S. Phillips

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One of the biggest challenges entering a market with a carsharing or any other shared mobility (SM) service is sound investment decision-making. To support this process, the authors think that a city index evaluating different criteria is necessary. The goal of such an index is to benchmark cities along a set of external measures to answer the main two challenges: financially viability and the understanding of its specific requirements. The authors have consulted several shared mobility projects and industry experts to create such a Shared Mobility City Index (SMCI). The current proposal of the SMCI consists of 11 individual index measures: general data (demographics, geography, climate and city culture), shared mobility landscape (current SM providers, public transit options, commuting patterns and driving culture) and political vision and goals (vision of the Mayor, sustainability plan, bylaws/tenders supporting SM). To evaluate the suitability of the index, 16 cities on the East Coast of North America were selected and secondary research was conducted. The main sources of this study were census data, organisational records, independent press releases and informational websites. Only non-academic sources where used because the relevant data for the chosen cities is not published in academia. Applying the index measures to the selected cities resulted in three major findings. Firstly, density (city area divided by number of inhabitants) is not an indicator for the number of SM services offered: the city with the lowest density has five bike and carsharing options. Secondly, there is a direct correlation between commuting patterns and how many shared mobility services are offered. New York, Toronto and Washington DC have the highest public transit ridership and the most shared mobility providers. Lastly, except one, all surveyed cities support shared mobility with their sustainability plan. The current version of the shared mobility index is proving a practical tool to evaluate cities, and to understand functional, political, social and environmental considerations. More cities will have to be evaluated to refine the criteria further. However, the current version of the index can be used to assess cities on their suitability for shared mobility services and will assist investors deciding which city is a financially viable market.

Keywords: carsharing, transportation, urban planning, shared mobility city index

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Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: D. Berg, N. Hartley, L. Nasr

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This paper presents a conceptual model of human-robot interaction within service encounters and the effect on the well-being of both consumers and service providers. In this paper, service providers are those employees who work alongside frontline service robots. The significance of this paper lies in the knowledge created which outlines how frontline service robots can be effectively utilized in service encounters for the benefit of organizations and society as a whole. As this paper is conceptual in nature, the main methodologies employed are theoretical, namely problematization and theory building. The significance of this paper is underpinned by the shift of service robots from manufacturing plants and factory floors to consumer-facing service environments. This service environment places robots in direct contact with frontline employees and consumers creating a hybrid workplace where humans work alongside service robots. This change from back-end to front-end roles may have implications not only on the physical environment, servicescape, design, and strategy of service offerings and encounters but also on the human parties of the service encounter itself. Questions such as ‘how are frontline service robots impacting and changing the service encounter?’ and ‘what effect are such changes having on the well-being of the human actors in a service encounter?’ spring to mind. These questions form the research question of this paper. To truly understand social service robots, an interdisciplinary perspective is required. Besides understanding the function, system, design or mechanics of a service robot, it is also necessary to understand human-robot interaction. However not simply human-robot interaction, but particularly what happens when such robots are placed in commercial settings and when human-robot interaction becomes consumer-robot interaction and employee-robot interaction? A service robot in this paper is characterized by two main factors; its social characteristics and the consumer-facing environment within which it operates. The conceptual framework presented in this paper contributes to interdisciplinary discussions surrounding social robotics, service, and technology’s impact on consumer and service provider well-being, and hopes that such knowledge will help improve services, as well as the prosperity and well-being of society.

Keywords: frontline service robots, human-robot interaction, service encounters, well-being

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Authors: E. Happ, Zs. Ivancsone Horvath

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With the development of the information technology, IT, sector, all industry of the world has a new path, dealing with digitalisation. Tourism is the most rapidly increasing industry in the world. Without digitalisation, tourism operators would not be competitive enough with foreign destinations or other experience-based service providers. Digitalisation is also necessary to enable organizations, which are interested in tourism to meet the growing expectations of consumers. With the help of digitalisation, tourism providers can also obtain information about tourists, changes in consumer behaviour, and the use of online services. The degree of digitalisation in tourism is different for different services. The research is based on a questionnaire survey conducted in 2018 in Hungary. The sample with more than 500 respondents was processed by the SPSS program, using a variety of analysis methods. The following two variables were observed from more aspects: frequency of travel and the importance of services related to online travel. With the help of these variables, a cluster analysis was performed among the participants. The sample can be divided into two groups using K-mean cluster analysis. Cluster ‘1’ is a positive group; they can be called the “most digital tourists.” They agree in most things, with low standard deviation, and for them, digitalisation is a starting point. To the members of Cluster ‘2’, digitalisation is important, too. The results show what is important (accommodation, information gathering) to them, but also what they are not interested in at all within the digital world (e.g., car rental or online sharing). Interestingly, there is no third negative cluster. This result (that there is no result) proves that tourism uses digitalisation, and the question is only the extent of the use of online tools and methods. With the help of the designed consumer groups, the characteristics of digital tourism segments can be identified. The help of different variables characterised these groups. One of them is the frequency of travel, where there is a significant correlation between travel frequency and cluster membership. The shift is clear towards Cluster ‘1’, which means, those who find services related to online travel more important, are more likely to travel as well. By learning more about digital tourists’ consumer behaviour, the results of this research can help the providers in what kind of marketing tools could be used to influence the consumer choices of the different consumer groups created using digital devices, furthermore how to conduct more detailed and effective marketing activities. The main finding of the research was that most of the people have digital tools which are important to be able to participate in e-tourism. Of these, mobile devices are increasingly preferred. That means the challenge for service providers is no longer the digital presence but having optimised application for different devices.

Keywords: cluster analysis, digital tourism, marketing tool, tourist behaviour

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Authors: L. S. Godlevsky, N. V. Kresyun, V. P. Martsenyuk, K. S. Shakun, T. V. Tatarchuk, K. O. Prybolovets, L. F. Kalinichenko, M. Karpinski, T. Gancarczyk

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Structures of eye bottom were extracted using multiscale texture gradient method and color characteristics of macular zone and vessels were verified in CIELAB scale. The difference of average values of L*, a* and b* coordinates of CIE (International Commision of Illumination) scale in patients with diabetes and healthy volunteers was compared. The average value of L* in diabetic patients exceeded such one in the group of practically healthy persons by 2.71 times (P < 0.05), while the value of a* index was reduced by 3.8 times when compared with control one (P < 0.05). b* index exceeded such one in the control group by 12.4 times (P < 0.05). The integrated index on color difference (ΔE) exceeded control value by 2.87 times (P < 0.05). More pronounced differences with ΔE were followed by a shorter period of MA appearance with a correlation level at -0.56 (P < 0.05). The specificity of diagnostics raised by 2.17 times (P < 0.05) and negative prognostic index exceeded such one determined with the expert method by 2.26 times (P < 0.05).

Keywords: diabetic retinopathy, multiscale texture gradient, color spectrum analysis, medical diagnostics

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Authors: Ashwini Kumar, Vinod Nayak, Shankar M. Bakkannavar

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The identification of humans is important in forensic investigations not only in living but also in dead, especially in cases of mass disorders. The procedure followed in dead known as post-mortem identification is a challenging task for the forensic pathologist. However, it is mandatory in terms of the law to fulfill the social norms. Many times, due to mutilation of body parts, the normal methods of identification using skeletal remains cannot be used in the process of identification. In such cases, the intact components of the skeletal remains or bony parts play an important role in identification. In these situations, digital forensics can come to our rescue. The authors hereby made a study for determination of sex based on nasal index by using (Big Bore 16 Slice) Multidetector Computed Tomography 2D Scans. The results are represented as a poster.

Keywords: sex determination, multidetector computed tomography, nasal index, digital forensic

Procedia PDF Downloads 400