Search results for: financial performance.

Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: Narges Ebadi, Davod Ahmadi, Hiliary Monteith, Hugo Melgar-Quinonez

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Migration cannot necessarily relieve pressure on water resources in origin communities, and male out-migration can increase the water management burden of women. However, inflows of financial remittances seem to offer possibilities of investing in improving drinking-water access. Therefore, remittances may be an important pathway for migrants to support water security. This paper explores the association between water access and the receipt of remittances in households in sub-Saharan Africa. Data from round 6 of the 'Afrobarometer' surveys in 2016 were used (n= 49,137). Descriptive, bivariate and multivariate statistical analyses were carried out in this study. Regardless of country, findings from descriptive analyses showed that approximately 80% of the respondents never received remittance, and 52% had enough clean water. Only one-fifth of the respondents had piped water supply inside the house (19.9%), and approximately 25% had access to a toilet inside the house. Bivariate analyses revealed that even though receiving remittances was significantly associated with water supply, the strength of association was very weak. However, other factors such as the area of residence (rural vs. urban), cash income frequencies, electricity access, and asset ownership were strongly associated with water access. Results from unadjusted multinomial logistic regression revealed that the probability of having no access to piped water increased among remittance recipients who received financial support at least once a month (OR=1.324) (p < 0.001). In contrast, those not receiving remittances were more likely to regularly have a water access concern (OR=1.294) (p < 0.001), and not have access to a latrine (OR=1.665) (p < 0.001). In conclusion, receiving remittances is significantly related to water access as the strength of odds ratios for socio-demographic factors was stronger.

Keywords: remittances, water access, SSA, migration

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Authors: F. Ben Abdelghani, W. Maherezi

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Dredging operations generate, each year, a great quantity of marine sediments. These raw materials can not be used in road construction without a specific treatment process. Sediments suitability tests has shown that most of studied sediments are not suitable to be used in road construction. In order to improve their compacity and their mechanical performance, addition of a granular material is recommended. The use of a dredged sand, to improve the granular mixture containing sediments, allows a better management of the two types of dredge materials (sand and sediment). In this study, a new road material containing dredged marine sediments and dredged sand is formulated and treated by adding various binders. Mechanical performance investigation of different mixtures by measuring Proctor-IPI values and simple compressive strengths is realized.

Keywords: dredged sediments, suitability tests, road construction, hydraulic binder, mechanical performance

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Authors: Sareh Rajabi, Taha Anjamrooz, Ahmed Hassan Almarzooqi

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Employee satisfaction, engagement, and performance are crucial for successful organizations. The performance of the employees now depends on their satisfaction level and whether they are satisfied with the management. Due to this fact, the organizations are now measuring the satisfaction level of their employees to increase profitability, productivity, and turnover. The aim of this research is to inspect the antecedents which direct in the direction of significant employee engagement and good job fit by finding the relationship between employee satisfaction and engagement. Based on an inclusive literature review on the employees’ satisfaction, engagement and performance, this research will conduct a study and survey in the UAE organizations in order to develop a framework for evaluating the impact of factors like employee satisfaction and engagement on the operation as an outcome by using statistical analysis. This study will allow in understanding the advantages of containing satisfied employees and how they perform in their peak motivation to make the company more profitable and competitive.

Keywords: employees’ satisfaction, employees’ engagement, antecedents, outcomes

Procedia PDF Downloads 151

Authors: Seemab Zehra, A. H. W. Mohammed, E. Pantanella, J. L. Q. Laranja, P. H. De Mello, R. Saleh, A. A. Siddik, A. Al Shaikhi, A. M. Al-Suwailem

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Two separate feeding trials were conducted to determine the effects of using different commercial diets and water temperatures on the growth performance, feed intake, feed conversion ratio (FCR) and condition factor of sobaity seabream Sparidentex hasta. In experiment I, growth performance, feed intake, protein efficiency ratio (PER), feed conversion ratio (FCR) and survival (%) of sobaity seabream Sparidentex hasta (330.5±2.6 g; 26.9±1.0 cm) were evaluated by four different commercial diets (1, 2, 3 and 4) for 80 days. The daily weight gain was around 3.2 g day-1 with an SGR of 0.7% day-1. Both the FCR and PER in the fish were significantly better in diet 2 that contained 46.36% crude protein and 12.54% crude fat. In experiment II, (99±2.6 g; 17.1±1.0 cm). The fish were cultured in 1m3 tanks supplied with seawater from the Red Sea wherein three different rearing temperatures were set as treatments (24, 28 and 32°C). Fish were fed with a commercial diet based on the results of experiment I (46.4% protein; 20.1 MJ kg-1 energy) to satiation for 96 days. Total weight gain was significantly higher for the fish reared in the 32°C group (158.57 g) followed by the 28°C group (138.25 g), while the lowest weight gain was observed in the 24°C group (116.98 g). The FCR was significantly lower in the 32°C group (1.62) as compared to 28 (1.8) and 24°C (1.85) groups. Based on the results obtained from these preliminary studies (experiment I and II), sobaity seabream can attain better growth performance, FCR and PER at 32°C in the Red Sea by feeding commercial diet 2.

Keywords: Sparidentex hasta, nutrition, FCR, Red Sea, growth performance

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Authors: Tamar Lazariashvili

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Introduction: The growth and development of the economy in the country depend on many factors, the most important of which is the use of innovation. The article analyzes the innovations and the potential of agricultural development in Georgia, presents the problems in the field, justifies the need to introduce innovations, shows the policy of innovation development, evaluates the positive and negative factors of the use of innovations in agriculture. Methodology: The article uses general and specific research methods, namely, analysis, synthesis, induction, deduction, comparison and statistical ones: selection, grouping, observation, trend. All these methods used together in the article reveal the main problems and challenges and their development trends. Main Findings: The introduction of innovations for the country has an impact if there is established state support system for business development and the State creates an effective environment for innovation development. As a result, the appropriate establishment gives incentives to increase budget revenues, create new jobs, increase export turnover and improve the overall economic situation in the country. Georgia has sufficient resource potential to create and develop new businesses in agriculture by introducing innovations and contribute to the further socio-economic development of the country. Political and economic stability, the existing legislation in the country, infrastructure, the proper functioning of financial institutions and the qualification of the workforce are crucial for the development of innovations. These criteria determine the political and economic ratings of all countries of the world, which are of great importance to foreign investors in the implementation of innovations. Conclusion: Enactment of agro-insurance will increase the interest and confidence of financial institutions in the farming sector, financial resources will be accessible to the farmers that will facilitate the stable development of the sector in the country. The size of the agro-insurance market in the country should be increased and the new territories should be covered. The State must have an obligation to ensure the risk of farmers and subsidize insurance companies. Based on an analysis of the insurance market the conclusions on agro-insurance issues and the relevant recommendations are proposed. The introduction of innovations in agriculture will have a great impact on the Georgian economy: it will improve the technological base, establish enterprises equipped with modern equipment and methodologies, retrain existing enterprises, promote to improve skills of workers and improve management systems. Based on the analysis, conclusions are made about the prospects for the development of innovation in agriculture and relevant recommendations are proposed.

Keywords: agriculture, development potential, innovation, optimal environment

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Authors: Luís Farinha, João J. Ferreira

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Nowadays innovation represents a challenge crucial to remaining globally competitive. This study seeks to develop a conceptual model aimed at measuring the dynamic interactions of the triple/quadruple helix, balancing innovation and entrepreneurship initiatives as pillars of regional competitiveness – the Regional Helix Scoreboard (RHS). To this aim, different strands of literature are identified according to their focus on specific regional competitiveness governance mechanisms. We put forward an overview of the state-of-the-art of research and is duly assessed in order to develop and propose a framework of analysis that enables an integrated approach in the context of collaborative dynamics. We conclude by presenting the RHS for the study of regional competitiveness dynamics, which integrates and associates different backgrounds and identifies a number of key performance indicators for research challenges.

Keywords: entrepreneurship, KPIs, innovation, performance measurement, regional competitiveness, regional helix scoreboard

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Authors: Simone Medio

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If we observe many modern cities from above, we are typically confronted with a sea of asphalt-clad flat rooftops. In contrast to the modernist expectation of a populated flat roof, flat rooftops in modern multi-story buildings are rarely used. On the contrary, they typify a desolate and abandoned landscape encouraging mechanical system allocation. Flat roof technology continues to be seen as a state-of-fact in most multi-storey building designs and its greening its prevalent environmental justification. This paper aims to seek a change in the approach to flat roofing. It makes a case for the opportunity at hand for architectonically resolute, sheltered, livable spaces that make a better use of the environment at rooftop level. The researcher is looking for the triggers that allow for that change to happen in the design process of case study buildings. The paper begins by exploring Han Slawick covered roof terrace in Amsterdam as a simple and essential example of transforming the flat roof in a usable, inhabitable space. It investigates the design challenges and the logistic, financial and legislative hurdles faced by the architect, and the outcomes in terms of building performance and occupant use and satisfaction. The researcher uses a grounded research methodology with direct interview process to the architect in charge of the building and the building user. Energy simulation tools and calculation of running costs are also used as further means of validating change.

Keywords: environmental design, flat rooftop persistence, roof re-habitation, tectonics

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Authors: Behnoush Dousti, Ye Choi, Gil S. Lee

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Supercapacitors which are also known as ultra supercapacitors play a significant role in development of energy storage devices owing to their high power density and rate capability. Nobel research has been conducted on micro scale energy storage systems currently to address the demand for smaller wearable technology and portable devices. Improving the performance of these microsupercapacitors have been always a challenge. Here, we demonstrate a facile fabrication of a microsupercapacitor (MSC) with interdigitated electrodes using novel structure of carbon nanotube sheets which are spun directly from as-grown carbon nanotube forests. Stability and performance of the device was tested using an aqueous PVA-H3PO4 gel electrolyte that also offers desirable electrochemical capacitive properties. High Coulombic efficiency around 100%, great rate capability and excellent capacitance retention over 15,000 cycles were obtained. Capacitive performance greatly improved with surface modification with acid and nitrogen doping of the CNT sheets. The high power density and stable cycling performance make this microsupercapacitor a suitable candidate for verity of energy storage application.

Keywords: carbon nanotube sheet, energy storage, solid state electrolyte, supercapacitor

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: H. B. Mahmud, Syamsul Bahri, Y. W. Yee, Y. T. Yeap

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This paper reports the strength and durability properties of high strength high performance concrete incorporating rice husk ash (RHA) having high silica, low carbon content and appropriate fineness. In this study concrete containing 10%, 15% and 20% RHA as cement replacement and water to binder ratio of 0.25 were investigated. The results show that increasing amount of RHA increases the dosage of superplasticizer to maintain similar workability. Partial replacement of cement with RHA did not increase the early age compressive strength of concrete. However, concrete containing RHA showed higher compressive strength at later ages. The results showed that compressive strength of concrete in the 90-115 MPa range can be obtained at 28 curing days and the durability properties of RHA concrete performed better than that of control concrete. The water absorption of concrete incorporating 15% RHA exhibited the lowest value. The porosity of concrete is consistent with water absorption whereby higher replacement of RHA decreased the porosity of concrete. There is a positive correlation between reducing porosity and increasing compressive strength of high strength high performance concrete. The results also indicate that up to 20% of RHA incorporation could be advantageously blended with cement without adversely affecting the strength and durability properties of concrete.

Keywords: compressive strength, durability, high performance concrete, rice husk ash

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Hyun-Jun Shin, Jae-Jeong Kim, Hyoung-Kyu Song

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In broadcasting and cellular system, a cooperative scheme is proposed for the improvement of performance of bit error rate. Up to date, the coverage of broadcasting system coexists with the coverage of cellular system. Therefore each user in a cellular coverage is frequently involved in a broadcasting coverage. The proposed cooperative scheme is derived from the shared areas. The users receive signals from both broadcasting base station and cellular base station. The proposed scheme selects a cellular base station of a worse channel to achieve better performance of bit error rate in cooperation. The performance of the proposed scheme is evaluated in fading channel.

Keywords: cooperative communication, diversity, STBC, CDD, channel condition, broadcasting system, cellular system

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Authors: M. Ranjeeth, S. Anuradha

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Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as P_f Vs P_d for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Keywords: spectrum sensing, energy detection, fading channels, probability of detection, probability of false alarm

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Authors: Rifat Tabassoom

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Recently multistoried housing projects are accelerating in the capital of Bangladesh- Dhaka, to house its massive population. Insufficient background research leads to a building design trend where a single unit is designed and then multiplied all through the buildings. Therefore, although having identical designs, all the units cannot perform evenly considering daylight, which also alters their household activities. This paper aims to understand if a single unit can be an optimum solution regarding daylight for a selected housing project.

Keywords: daylight, orientation, performance, simulations

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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: Norhayati Mat Wajid, Abdul Murad Zainal Abidin, Faiz Fadzil, Mohd Yusof Aizad Mukhtar

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One of the areas that present an opportunity to reduce the national carbon emission is the energy management of public buildings. To our present knowledge, there is no easy-to-use and centralized mechanism that enables the government to monitor the overall energy performance, as well as the carbon footprint, of Malaysia’s public buildings. Therefore, the Public Works Department Malaysia, or PWD, has developed a web-based energy performance reporting tool called JENOSYS (JKR Energy Online System), which incorporates a database of utility account numbers acquired from the utility service provider for analysis and reporting. For test case purposes, 23 buildings under PWD were selected and monitored for their monthly energy performance (in kWh), carbon emission reduction (in tCO₂eq) and utility cost (in MYR), against the baseline. This paper demonstrates the simplicity with which buildings without energy metering can be monitored centrally and the benefits that can be accrued by the government in terms of building energy disclosure and concludes with the recommendation of expanding the system to all the public buildings in Malaysia.

Keywords: energy-efficient buildings, energy management systems, government buildings, JENOSYS

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Authors: Ernest Nweke

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Mongolia has made giant strides in the development of its auditing and accounting system from Soviet-style to a market-oriented system. High levels of domestic and foreign investment desired by the Mongolian government require that better and improved quality of corporate information and disclosure consistent with international standards be made available to investors. However, the Mongolian Certified Public Accountants (CPA) profession is still developing, and the quality of services provided by accounting firms in most cases do not comply with International Financial Reporting Standards (IFRS) framework approved by the government for use in financial reporting. Against this backdrop, Accounting and audit reforms, liberalization and deregulation, establishment of an efficient and effective professional monitoring and supervision regime are policy necessities. These will further enhance the Mongolian business environment, eliminate incompetence in the system, make the economy more attractive to investors and ultimately lift reporting standards and bring about improved accounting, auditing and disclosure practices among Mongolian firms. This paper examines the fundamental issues in the accounting and auditing environment in Mongolia and investigates the relationship between selected characteristics of Mongolian Stock Exchange (MSE) listed firms (profitability, leverage, firm size, firm auditor size, firm listing age, board size and proportion of independent directors) and voluntary accounting disclosures in their annual reports and accounts. The selected sample of firms for the research purpose consists of the top 20 indexes of the MSE, representing over 95% of the market capitalization. An empirical analysis of the hypothesized relationship was carried out using multiple regression in EViews analytical software. Research results lend credence to the fact that only a few of the company attributes positively impact voluntary accounting disclosures in Mongolian Stock Exchange-listed firms. The research is motivated by the absence of empirical evidence on the correlation between the quality of voluntary accounting disclosures made by listed companies in Mongolia and company characteristics and the findings thereof significantly useful to both firms and regulatory authorities. The concluding part of the paper precisely consists of useful research-based recommendations for listed firms and regulatory agencies on measures to put in place in order to enhance the quality of corporate financial reporting and disclosures in Mongolia.

Keywords: accounting, auditing, corporate disclosure, listed firms

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Authors: Seung-Lock Seo

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This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

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Authors: John Hawkins, Graham Burton

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Contextual targeting is a common strategy for advertising that places marketing messages in media locations that are expected to be aligned with the target audience. There are multiple major challenges to contextual targeting: the ideal categorisation scheme needs to be known, as well as the most appropriate subsections of that scheme for a given campaign or creative. In addition, the campaign reach is typically limited when targeting becomes narrow, so a balance must be struck between requirements. Finally, refinement of the process is limited by the use of evaluation methods that are either rapid but non-specific (click through rates), or reliable but slow and costly (conversions or brand recall studies). In this study we evaluate the use of attention measurement as a technique for understanding the performance of targeting on the basis of specific contextual topics. We perform the analysis using a large scale dataset of impressions categorised using the iAB V2.0 taxonomy. We evaluate multiple levels of the categorisation hierarchy, using categories at different positions within an initial creative specific ranking. The results illustrate that measuring attention time is an affective signal for the performance of a specific creative within a specific context. Performance is sustained across a ranking of categories from one period to another.

Keywords: contextual targeting, digital advertising, attention measurement, marketing performance

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Authors: Paolo Pietro Biancone

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The spread of Islamic financial instruments is an opportunity to offer integration for the immigrant population and to attract, through the specific products, the richness of sovereign funds from the "Arab" countries. However, it is important to consider the possibility of comparing a traditional finance model, which in recent times has given rise to many doubts, with an "alternative" finance model, where the ethical aspect arising from religious principles is very important.

Keywords: banks, Europe, Islamic finance, Italy

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Authors: Ashraf Muharam, Nasser Al-Hemiddi, El Sayed Amer

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Green roof is one of sustainable practice for reducing the environmental impact of a building. Green roofs are vegetation roofs that are partially or completely covered building's roof. It can provide multiple environmental benefits such as mitigation of urban heat island effect and protecting buildings against solar radiation. In Riyadh city buildings consume about 70 % of the total energy used in the building for cooling and heating because of the Riyadh's harsh and tropical climate. So, the study aim was identifying the thermal performance of extensive green roof and comparing its performance with concrete roof performance during summer season. The experimental validations results indicated that the extensive green roofs system was better than concrete roof system for lowering the indoor air temperature. It could reduce the indoor air temperature from 2°C to 5.5°C compared to the concrete roof system. Also, the finding of this study demonstrated that extensive green roof system could reduce 12% to 33% of energy consumption of air conditioning in Riyadh city during summer seasons by using environmentally friendly insulation.

Keywords: thermal performance, green roof system, concrete roof system, tropical climatic, internal temperatures

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Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau

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Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.

Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement

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Authors: Muhammad Umar Kiani, Muhammad Shahbaz

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Performance of any vehicle can be predicted by its design/modeling and optimization. Design optimization leads to efficient performance. Followed by horizontal launch, the air launch re-entry vehicle undergoes a launch maneuver by introducing a carefully selected angle of attack profile. This angle of attack profile is the basic element to complete a specified mission. Flight program of said vehicle is optimized under the constraints of the maximum allowed angle of attack, lateral and axial loads and with the objective of reaching maximum altitude. The main focus of this study is the endo-atmospheric phase of the ascent trajectory. A three degrees of freedom trajectory model is simulated in MATLAB. The optimization process uses evolutionary algorithm, because of its robustness and efficient capacity to explore the design space in search of the global optimum. Evolutionary Algorithm based trajectory optimization also offers the added benefit of being a generalized method that may work with continuous, discontinuous, linear, and non-linear performance matrix. It also eliminates the requirement of a starting solution. Optimization is particularly beneficial to achieve maximum advantage without increasing the computational cost and affecting the output of the system. For the case of launch vehicles we are immensely anxious to achieve maximum performance and efficiency under different constraints. In a launch vehicle, flight program means the prescribed variation of vehicle pitching angle during the flight which has substantial influence reachable altitude and accuracy of orbit insertion and aerodynamic loading. Results reveal that the angle of attack profile significantly affects the performance of the vehicle.

Keywords: endo-atmospheric, evolutionary algorithm, efficient performance, optimization process

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Authors: Jamaluddin Abd Rashid, Aris Abdul Rahman

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Mobile phones have become the most popular way to communicate with other individuals and it has created an unspoken social dependency. Making phone calls, instant messaging, playing online games and accessing the Internet are among the features added to a mobile phone, attracting teenagers to spend more hours fixated on their gadgets. As such, this study attempted to examine the frequency of time spent on mobile phones and how this influenced academic performance. A quantitative methodology was applied in this study, where face to face survey through the distribution of questionnaires was facilitated onto a group of 200 secondary school students from the Shah Alam community in Selangor,Malaysia. Both genders, male and females were assessed equally to find out if there exists a correlation between genders when measuring higher or lower frequency of attachment to mobile phones. It can also be seen that 100% correspondents have a mobile phone in their possession. The adolescents uses mobile phones daily, which shows students being somewhat addicted, as they tend to feel that it is necessary to use a mobile phone. The main findings of this research found out that, students that are mobile phone addictive received a lower grade in schools. Mobile phone addiction does affect academic performance negatively. As this study discusses the modern-day phenomenon, it is hoped that the findings and discussion could add to present literary works and help future researchers understand the relationship between mobile phone addiction and academic performance.

Keywords: academic performance, mobile phone addiction, social media, student

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Authors: Anne Gesare Timu, Megan Sheahan, Andrew Gache Mude, Rupsha Banerjee

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Women headed households are among the most vulnerable to negative climatic shocks and are often left poorer as a result. Credit provision has been recognized as one way of alleviating rural poverty and developing poor rural households’ resilience to shocks. Much has been documented about credit demand in small-holder agriculture settings in Kenya. However, little is known about demand for credit among pastoral women. This paper analyzes the determinants of demand for credit in the pastoral regions of Marsabit District of Northern Kenya. Using a five wave balanced panel data set of 820 households, a double hurdle model is employed to analyze if shocks, financial literacy and risk aversion affect credit demand among female and male headed households differently. The results show that borrowing goods on credit and monetary credit from informal market segments are the most common sources of credit in the study area. The impact of livestock loss and financial literacy on the decision to borrow and how much to borrow vary with gender. While the paper suggests that provision of credit is particularly valuable in the aftermath of a negative shock and more so for female-headed households, it also explores alternatives to the provision of credit where credit access is a constraint. It recommends further understanding of systems and institutions which could enhance access to credit, and particularly during times of stress, to enable households in the study area in particular and Northern Kenya in general to invest, engage in meaningful development and growth, and be resilient to persistent shocks.

Keywords: female headed households, pastoralism, rural financing, double hurdle model

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Authors: Amna Bibi, Hina Rana

Abstract:

In the social, behavioral, and medical sciences, and particularly in Pakistani popular culture and political discourse, transgender issues are a relatively recent subject of research. The present study aimed to explore the lived experiences related to psycho-social issues faced by transgenders in Pakistani society. In this qualitative study, phenomenology research design was used. The purposive and snowball sampling techniques were used for data collection, and in-depth interviews were conducted with N= 8 transgenders belonging to Lahore city, Pakistan. All interviews were audio recorded and transcribed properly. Interpretative phenomenological analysis was used to generate results in terms of themes. The results of the current study revealed different major themes, such as psychological, social, and financial problems. Several emergent and sub-themes were also generated, such as insomnia, suicidal ideation, stress, physical abuse, social rejection, discrimination at work workplace, fewer job opportunities, and harassment. Current studies indicate that transgender suffer from different problems and struggle hard for their daily living. It was concluded that there should be a step taken at the government level for the betterment of this community. The findings of the present study can help out transgender communities and activists uncover their problems and empower transgender individuals through education, skill development, and opportunities for growth. Their abilities can be utilized by providing education, polishing their skills, and employment opportunities. The data provides the knowledge that there should be strategies at the family, society and government level for the betterment of transgenders.

Keywords: psychological issues, social issues, financial issues, transgender, Pakistani society

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Authors: Yassir M. Abbas, Mohammad Iqbal Khan, Galal Fare

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In the present work, the structural responses of 12 ultrahigh-performance concrete (UHPC) beams to four-point loading conditions were experimentally and analytically studied. The inclusion of a fibrous system in the UHPC material increased its compressive and flexural strengths by 31.5% and 237.8%, respectively. Based on the analysis of the load-deflection curves of UHPC beams, it was found that UHPC beams with a low reinforcement ratio are prone to sudden brittle failure. This failure behavior was changed, however, to a ductile one in beams with medium to high ratios. The implication is that improving UHPC beam tensile reinforcement could result in a higher level of safety. More reinforcement bars also enabled the load-deflection behavior to be improved, particularly after yielding.

Keywords: ultrahigh-performance concrete, moment capacity, RC beams, hybrid fiber, ductility

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Authors: Yu-Chen Wei

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The relationship between organizational human capital and organizational effectiveness have been a common topic of interest to organization researchers. Much of this research has concluded that higher human capital can predict greater organizational outcomes. Whereas human capital research has traditionally focused on organizations, the current study turns to the team level human capital. In addition, there are no known empirical studies assessing the effect of human capital divergence on team performance. Team human capital refers to the sum of knowledge, ability, and experience embedded in team members. Team human capital divergence is defined as the variation of human capital within a team. This study is among the first to assess the role of human capital divergence as a moderator of the effect of team human capital on team performance. From the traditional perspective, team human capital represents the collective ability to solve problems and reducing operational risk of all team members. Hence, the higher team human capital, the higher the team performance. This study further employs social learning theory to explain the relationship between team human capital and team performance. According to this theory, the individuals will look for progress by way of learning from teammates in their teams. They expect to have upper human capital, in turn, to achieve high productivity, obtain great rewards and career success eventually. Therefore, the individual can have more chances to improve his or her capability by learning from peers of the team if the team members have higher average human capital. As a consequence, all team members can develop a quick and effective learning path in their work environment, and in turn enhance their knowledge, skill, and experience, leads to higher team performance. This is the first argument of this study. Furthermore, the current study argues that human capital divergence is negative to a team development. For the individuals with lower human capital in the team, they always feel the pressure from their outstanding colleagues. Under the pressure, they cannot give full play to their own jobs and lose more and more confidence. For the smart guys in the team, they are reluctant to be colleagues with the teammates who are not as intelligent as them. Besides, they may have lower motivation to move forward because they are prominent enough compared with their teammates. Therefore, human capital divergence will moderate the relationship between team human capital and team performance. These two arguments were tested in 510 team-seasons drawn from major league baseball (1998–2014). Results demonstrate that there is a positive relationship between team human capital and team performance which is consistent with previous research. In addition, the variation of human capital within a team weakens the above relationships. That is to say, an individual working with teammates who are comparable to them can produce better performance than working with people who are either too smart or too stupid to them.

Keywords: human capital divergence, team human capital, team performance, team level research

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Authors: Chia-Yu Yao

Abstract:

This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance.

Keywords: pulse-shaping filters, FIR filters, jittering, QAM

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