Search results for: financial bubble detection

Authors: Ahmet Sekreter

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Although there are conceptual similarities in terms of financial products between conventional and Islamic finance, they are entirely different financial systems. Despite Islamic finance’s small size in the conventional finance world, its promising growth makes Islamic finance a hot topic both in academia and business world. Today customers can access sophisticated Islamic financial products not only in Muslim countries but also in Europe. This study analyzes Islamic finance and its products and includes a brief overview of Islamic finance in Europe. Literature review is the basis of this paper. The author analyzed the academic papers, numerical data, and estimations to set a perspective for the future of Islamic finance in Europe. Findings show that UK is the main hub for the Islamic finance, and it will remain so in the near future.

Keywords: islamic finance, islamic banking, islamic finance in Europe, finance

Procedia PDF Downloads 238

Authors: Yushen Dai, Tao Deng, Miaoying Chen, Baoqin Huang, Yan Ji, Yongshen Feng, Shaofei Liu, Dongmei Zhong, Tao Zhang, Lifeng Zhang

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Background: Detection and diagnosis are prerequisites for early interventions in the care of children with Autism Spectrum Disorder (ASD). However, few studies have focused on this topic. Aim: This study aims to characterize the timing from symptom detection to intervention in children with ASD and to identify the potential predictors of early detection, diagnosis, and intervention. Methods and procedures: A cross-sectional survey was conducted with 314 parents of children with ASD in Guangzhou, China. Outcomes and Results: This study found that most children (76.24%) were diagnosed within one year after detection, and 25.8% of them did not receive the intervention after diagnosis. Predictors to ASD diagnosis included ASD-related symptoms identified at a younger age, more serious symptoms, and initial symptoms with abnormal development and sensory anomalies. ASD-related symptoms observed at an older age, initial symptoms with the social deficit, sensory anomalies, and without language impairment, parents as the primary caregivers, family with lower income and less social support utilization increased the odds of the time lag between detection and diagnosis. Children whose fathers had a lower level of education were less likely to receive the intervention. Conclusions and Implications: The study described the time for detection, diagnosis, and interventions of children with ASD. Findings suggest that the ASD-related symptoms, the timing at which symptoms first become a concern, primary caregivers’ roles, father’s educational level, and the family economic status should be considered when offering support to improve early detection, diagnosis, and intervention. Helping children and their families take full advantage of support is also important.

Keywords: autism spectrum disorder, child, detection, diagnosis, intervention, social support

Procedia PDF Downloads 90

Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

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The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

Procedia PDF Downloads 357

Authors: Feddaoui Amina

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Through this study we will try to shed light on the theoretical framework proposed for understanding creative accounting as a financial numbers game and one of the most important techniques of accounts manipulation, its main actors and its practices. We will discover the role of the modified Jones model (1995) in detecting creative accounting practices using discretionary accruals. Finally we will try to confirm the importance and the need to address this type of practices using corporate governance as a main control system and an important defense line to reduce these dangerous accounts manipulation.

Keywords: financial numbers game, creative accounting, modified Jones model, accounts manipulation

Procedia PDF Downloads 477

Authors: Muftah H. El-Naas, Ameera F. Mohammad, Mabruk I. Suleiman, Mohamed Al Musharfy, Ali H. Al-Marzouqi

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CO₂ capture and storage technologies play a significant role in contributing to the control of climate change through the reduction of carbon dioxide emissions into the atmosphere. The present study evaluates and optimizes CO₂ capture through a process, where carbon dioxide is passed into pH adjusted high salinity water and reacted with sodium chloride to form a precipitate of sodium bicarbonate. This process is based on a modified Solvay process with higher CO₂ capture efficiency, higher sodium removal, and higher pH level without the use of ammonia. The process was tested in a bubble column semi-batch reactor and was optimized using response surface methodology (RSM). CO₂ capture efficiency and sodium removal were optimized in terms of major operating parameters based on four levels and variables in Central Composite Design (CCD). The operating parameters were gas flow rate (0.5–1.5 L/min), reactor temperature (10 to 50 ^oC), buffer concentration (0.2-2.6%) and water salinity (25-197 g NaCl/L). The experimental data were fitted to a second-order polynomial using multiple regression and analyzed using analysis of variance (ANOVA). The optimum values of the selected variables were obtained using response optimizer. The optimum conditions were tested experimentally using desalination reject brine with salinity ranging from 65,000 to 75,000 mg/L. The CO₂ capture efficiency in 180 min was 99% and the maximum sodium removal was 35%. The experimental and predicted values were within 95% confidence interval, which demonstrates that the developed model can successfully predict the capture efficiency and sodium removal using the modified Solvay method.

Keywords: CO2 capture, water desalination, Response Surface Methodology, bubble column reactor

Procedia PDF Downloads 287

Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

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This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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Authors: Sloka Bhushan

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Dark matter constitutes a majority of matter in the universe, yet very little is known about it due to its extreme lack of interaction with regular matter and the fundamental forces. Weakly Interacting Massive Particles, or WIMPs, have been contested to be one of the strongest candidates for dark matter due to their promising theoretical properties. However, various endeavors to detect these elusive particles have failed. This paper explores the various particles which may be WIMPs and the detection techniques being employed to detect WIMPs (such as underground detectors, LHC experiments, and so on). There is a special focus on the reasons for the lack of detection of WIMPs so far, and the possibility of limits in detection being a reason for the lack of physical evidence of the existence of WIMPs. This paper also explores possible inconsistencies within the WIMP particle theory as a reason for the lack of physical detection. There is a brief review on the possible solutions and alternatives to these inconsistencies. Additionally, this paper also reviews the supersymmetry theory and the possibility of the supersymmetric neutralino (A possible WIMP particle) being detectable. Lastly, a review on alternate candidates for dark matter such as axions and MACHOs has been conducted. The explorative study in this paper is conducted through a series of literature reviews.

Keywords: dark matter, particle detection, supersymmetry, weakly interacting massive particles

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Authors: Pradthana Sianglam, Wittaya Ngeontae

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A new approach for the fabrication of cadmium ion (Cd2+) sensor is demonstrated. The detection principle is based on the in-situ generation of cadmium sulfide quantum dots (CdS QDs) in the presence of chiral thiol containing compound and detection by the circular dichroism spectroscopy (CD). Basically, the generation of CdS QDs can be done in the presence of Cd2+, sulfide ion and suitable capping compounds. In addition, the strong CD signal can be recorded if the generated QDs possess chiral property (from chiral capping molecule). Thus, the degree of CD signal change depends on the number of the generated CdS QDs which can be related to the concentration of Cd2+ (excess of other components). In this work, we use the mixture of cysteamine (Cys) and L-Penicillamine (LPA) as the capping molecules. The strong CD signal can be observed when the solution contains sodium sulfide, Cys, LPA, and Cd2+. Moreover, the CD signal is linearly related to the concentration of Cd2+. This approach shows excellence selectivity towards the detection of Cd2+ when comparing to other cation. The proposed CD sensor provides low limit detection limits around 70 µM and can be used with real water samples with satisfactory results.

Keywords: circular dichroism sensor, quantum dots, enaniomer, in-situ generation, chemical sensor, heavy metal ion

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Authors: Rana Muhammad Armaghan Ayaz, Yigit Uysallı, Nima Bavili, Berna Morova, Alper Kiraz

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Traditional optical methods for example resonance wavelength shift and cavity ring-down spectroscopy used for material detection and sensing have disadvantages, for example, less resistance to laser noise, temperature fluctuations and extraction of the required information can be a difficult task like ring downtime in case of cavity ring-down spectroscopy. Phase shift cavity ring down spectroscopy is not only easy to use but is also capable of overcoming the said problems. This technique compares the phase difference between the signal coming out of the cavity with the reference signal. Detection of any material is made by the phase difference between them. By using this technique, air, water, and isopropyl alcohol can be recognized easily. This Methodology has far-reaching applications and can be used in air pollution detection, human breath analysis and many more.

Keywords: materials, noise, phase shift, resonance wavelength, sensitivity, time domain approach

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Authors: Angrita Denziana, Haninun, Hepiana Patmarina, Ferdinan Fatah

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The aims of the study are to determine the effect of the company's financial performance with Return on Asset (ROA) and Return on Equity (ROE) indicators. The macroeconomic factors with the indicators of Indonesia interest rate (SBI) and exchange rate on stock returns of non-financial companies listed in IDX. The results of this study indicate that the variable of ROA has negative effect on stock returns, ROE has a positive effect on stock returns, and the variable interest rate and exchange rate of SBI has positive effect on stock returns. From the analysis data by using regression model, independent variables ROA, ROE, SBI interest rate and the exchange rate very significant (p value < 0.01). Thus, all the above variable can be used as the basis for investment decision making for investment in Indonesia Stock Exchange (IDX) mainly for shares in the non- financial companies.

Keywords: ROA, ROE, interest rate, exchange rate, stock return

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Authors: Muhammad Shehu Garba

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The financial statements of the firms between the periods of 2013 and 2022 were collected using the secondary method of data collection, and the study aims to investigate the effect of ownership structure on the financial performance of listed industrial goods companies in Nigeria. 10 firms were used as the study's sample size. The study used panel data variables of the study. The ownership structure is measured with managerial ownership, institutional ownership and foreign ownership, while financial performance is measured with return on asset and return on equity; the study made use of control variables leverage and firm size. The result shows a multivariate relationship that exists between variables of the study, which shows ROA has a positive correlation with ROE (0.4053), MO (0.2001), and FS (0.3048). It has a negative correlation with FO (-0.1933), IO (-0.0919), and LEV (-0.3367). ROE has a positive correlation with ROA (0.4053), MO (0.2001), and FS (0.2640). It has a negative correlation with FO (-0.1864), IO (-0.1847), and LEV (-0.0319). It is recommended that firms should focus on increasing their ROA. Firms should also consider increasing their MO, as this can help to align the interests of managers and shareholders. Firms should also be aware of the potential impact of FO and IO on their ROA.

Keywords: firm size, ownership structure, financial performance, leaverage

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Authors: Adewusi Adeoluwawale, Oronti Iyabosola Busola, Akinola Iretiayo, Komolafe Olusola Aderibigbe

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The complex and radial structure of the low voltage distribution network (415V) makes it vulnerable to faults which are due to system and the environmental related factors. Besides these, the protective scheme employed on the low voltage network which is the fuse cannot be monitored remotely such that in the event of sustained fault, the utility will have to rely solely on the complaint brought by customers for loss of supply and this tends to increase the length of outages. A microcontroller based fault detection scheme is hereby developed to detect low voltage and high voltage fault conditions which are common faults on this network. Voltages below 198V and above 242V on the distribution feeders are classified and detected as low voltage and high voltages respectively. Results shows that the developed scheme produced a good response time in the detection of these faults.

Keywords: fault detection, low voltage distribution feeders, outage times, sustained faults

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Authors: Nicole Virgili, Romolo Remetti

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The aim of this work is to characterize, from radiation protection point of view, the emission into the environment of air contaminated by argon-41. In this research work, 41Ar is produced by a TR19PET cyclotron, operated at 19 MeV, installed at 'A. Gemelli' University Hospital, Rome, Italy, for fluorine-18 production. The production rate of 41Ar has been calculated on the basis of the scheduled operation cycles of the cyclotron and by utilising proper production algorithms. Then extensive Monte Carlo calculations, carried out by MCNP code, have allowed to determine the absolute detection efficiency to 41Ar gamma rays of a Geiger Muller detector placed in the terminal part of the chimney. Results showed unsatisfactory detection efficiency values and the need for integrating the detection system with more efficient detectors.

Keywords: Cyclotron, Geiger Muller detector, MCNPX, argon-41, emission of radioactive gas, detection efficiency determination

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Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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Authors: Joel Vilca Tarazona, Igor Aguilar-Alonso

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The problem of this research related to business intelligence is the lack of a tool that supports automated and efficient financial analysis for decision-making and allows an evaluation of the financial statements, which is why the availability of the information is difficult. Relevant information to managers and users as an instrument in decision making financial, and administrative. For them, a business intelligence solution is proposed that will reduce information access time, personnel costs, and process automation, proposing a 4-layer architecture based on what was reviewed by the research methodology.

Keywords: decision making, business intelligence, Google Cloud, Microsoft Power BI

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Authors: Aria Vitkova, Hanna Sykulska-Lawrence

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In recent years, Europa has been one of the major focus points in astrobiology due to its high potential of harbouring life in the vast ocean underneath its icy crust. However, the detection of life on Europa faces many challenges due to the harsh environmental conditions and mission constraints. Raman spectroscopy is a highly capable and versatile in-situ characterisation technique that does not require any sample preparation. It has only been used on Earth to date; however, recent advances in optical and laser technology have also allowed it to be considered for extraterrestrial exploration. So far, most efforts have been focused on the exploration of Mars, the most imminent planetary target. However, as an emerging technology with high miniaturization potential, Raman spectroscopy also represents a promising tool for the exploration of Europa. In this study, the capabilities of Raman technology in terms of life detection on Europa are explored and assessed. Spectra of biosignatures identified as high priority molecular targets for life detection on Europa were acquired at various excitation wavelengths and conditions analogous to Europa. The effects of extremely low temperatures and low concentrations in water ice were explored and evaluated in terms of the effectiveness of various configurations of Raman instruments. Based on the findings, a design of a miniaturized Raman instrument optimized for in-situ detection of life on Europa is proposed.

Keywords: astrobiology, biosignatures, Europa, life detection, Raman Spectroscopy

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Authors: Mohammad Besharatloo

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Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

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Authors: Mahmoud E. Mohamed, Ahmed F. Shalash, Hanan A. Kamal

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In communication systems, frequency jump is a serious problem caused by the oscillators used. Kalman filters are used to detect that jump, Despite the tradeoff between the noise level and the speed of the detection. In this paper, An improvement is introduced in the Kalman filter, Through a nonlinear change in the bandwidth of the filter. Simulation results show a considerable improvement in the filter speed with a very low noise level. Additionally, The effect on the response to false alarms is also presented and false alarm rate show improvement.

Keywords: Kalman filter, innovation, false detection, improvement

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Authors: Andrea Paltrinieri, Alberto Dreassi, Stefano Miani, Alex Sclip

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The financial crises caused a collapse in prices of most asset classes, raising the attention on alternative investments such as Sukuk, a smaller, fast growing but often misunderstood market. We study diversification benefits of Sukuk, their correlation with other asset classes and the effects of their inclusion in investment portfolios of institutional and retail investors, through a comprehensive comparison of their risk/return profiles during and after the financial crisis. We find a beneficial performance adjusted for the specific volatility together with a lower correlation especially during the financial crisis. The distribution of Sukuk returns is positively skewed and leptokurtic, with a risk/return profile similarly to high yield bonds. Overall, our results suggest that Sukuk present diversification opportunities, a significant volatility-adjusted performance and lower correlations especially during the financial crisis. Our findings are relevant for a number of institutional investors. Long term investors, such as life insurers would benefit from Sukuk’s protective features during financial crisis yet keeping return and growth opportunities, whereas banks would gain due to their role of placers, advisors, market makers or underwriters.

Keywords: sukuk, zero beta asset, asset allocation, sukuk market

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Authors: Sukhleen Kaur

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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

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Authors: Disha Batra

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With the advent of economic reforms in India in 1992, economic journalism in India has undergone a sea change along with the rise in the Indian economy. Squeezing out of economic news stories (economy-in-general) over business (individual corporate stories) and financial (financial and equity markets) news stories have been done and are still underway. The objective of the study is to explore how economic journalism – news stories about macroeconomic issues or economy-in-general has changed over the past three decades with the emergence of LPG (Liberalisation, Privatisation, and Globalisation) policies in India. The purpose of the study is to examine to what extent business and financial news are constricting economic news which is done by analysing news stories and content of business papers. The study is based on the content analyses of the top three Indian business dailies as per IRS (Indian Readership Survey) 2017. The parametric analysis of the different parameters (source of information, sub-topic, a dominant source in economic news, layout and framing, etc.) has been done in order to come across with the distinct adaptations and modifications by these dailies. The paper significantly dwells upon the thematic analysis of these newspapers in order to explore and find out the coverage given to various sub-themes of EBF (economic, business, and financial) journalism. The study revealed that stories concerning broader issues about the economy which are likely to be of public concern had been dropped. The paper further indicates an upward trend for the stories concerning individual corporate, equity, and financial markets. Findings of the study raise concern over the indicated disparity between economic and business news stories which may further limit the information that people need in order to make well-versed decisions.

Keywords: business-papers, business news, economic news, financial news

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Ofuan James Ilaboya, Okhae J. Ibhadode

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The objective of this paper is to theoretically examine the truism of the “true and fair view” in the context of financial reporting. The paper examines the concepts such as true, fair, true and fair view, problems of true and fair view, the origin/history of true and fair view, review of attributes and key issues relating to true and fair view. The methodological approach adopted in this paper is library-based research, focusing on the review of relevant and related extant literature. The findings based on the review of relevant and related literature is suggestive of the fact that the true and fair concept in financial reporting environment is contentious. The study concludes that given the circumstances as chronicled on this paper, it is evident that the truism of the true and fair view of the auditor’s opinion is under serious threat. The way forward may be for the auditor to certify the accuracy and the correctness of the financial statement. While this position being canvassed here may help to substantially bridge the age-long expectation gap, it may as well require an upward review of the current audit fee structure in order to be able to operationalize the onerous task of certifying the accuracy and correctness of the financial statement. This position is contentious and will require a robust consideration which is not within the purview of the present review.

Keywords: fiduciary duty, financial statement, true and correct, true and fair

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Authors: Abdelghani Chahmi

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This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.

Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation

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Authors: Sunday Odunaiya

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The statistics of banks in operation in this current dispensation compared to some decades ago has brought about a lot of changes on the face of the financial system. The demand of customers, technological advancement, and government policies among others has therefore generated a lot of heat for financial sector’s growth, sustenance and survival. This paper discusses mergers and acquisitions (M&A) in banking sector using West Africa as a yardstick of evaluation. It explains rigorously the conditions that warrant mergers and acquisitions in the banking sector, its effect, and how to ensure mergers and acquisitions effectiveness in the banking sector. The conceptual and empirical review of the relevant literature were done systematically while value-increasing and value-decreasing theories were used to substantiate the discourse. Findings of this paper show that mergers and acquisitions is a practical and conscious activity in Nigeria, Ghana and Ivory Coast from earliest time till date with tremendous turnaround in the financial sector. It was found out that M&A is consensually arrived at by the targets and the acquirer on a value-based account. In other words, merger and acquisition is a deliberate decision reached by the management of such bank for a ‘just cause’.

Keywords: acquisitions, merger, management, financial sector

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Authors: Nada Hamed, Mariam Aldhaheri, Sonia Abdennadher

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Islamic Finance is not a new term that emerging in the global market, but it is still under scope by many countries. Its characteristics and regulation are not widely clear and implemented. In 2015, The United Nation announced a plan about potential benefits of using Islamic Finance as a sustainable development approach. Enhancing its application in financial markets could protect from unexpected crisis that might be created from the traditional tools of finance. This paper focuses on this area to test if Islamic finance could be used for maintaining sustainable development and if the term of 'Green Islamic Finance' could be implemented to minimize the deficiencies and 'pollution’ generated from traditional techniques and tools of finance. This paper intends to measure the impact on financial performance and sustainability when financial institutions use Islamic finance or better practice it. The objective of this explanatory research is to measure the performance of Islamic Finance with using a case study of an Islamic bank. The paper would analyze and compare the behavior of financial institutions that used traditional financing tools and converted to Islamic banking system. The methodology used is based on a case study of an Islamic bank in Dubai with comparing its performance before implementing Islamic Finance and after. The selected case study represents the first national bank in Emirates Arab Unis who adopt the Islamic finance approach. Based on a time series analysis, a quantitative analysis would be also used through looking at various set of ratios that are routinely used to measure bank performance.

Keywords: Islamic finance, financial stability, green finance, Islamic finance practices, financial ratios

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Authors: Yasmin Umar Assegaf, Falikhatun, Salamah Wahyuni

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This study aims to provide empirical evidence about the influence of Islamic Corporate Social Responsibility Disclosures of the financial performance of Islamic banking with the characteristics of the company, as a control variable in Islamic banking in Indonesia. ICSR disclosures are an independent variable, while the Financial Performance is the dependent variable (proxied by Return on Assets (ROA), Return on Equity (ROE), Income Expense Ratio (IER), and Non-net Interest Margin (NIM). The control variables used are firm size, firm age and the type of audit. The population of the study was all Islamic Banks (BUS) operate in Indonesia. The research sample is Islamic Commercial Bank which has existed in Indonesia since 2002 and publishes financial statements between the years of 2007-2011. The sample of the study were include 31 Annual Report published. The results of this study concluded that there are significant influences between the ICSR Disclosures and financial performance. The disclosure is partially effect on ROA, IER and NIM, whereas there is no influence on ROE. Further result shows that all control variables (Firm Size, Age, and Type of Audit Companies) does not have any influence on ICSR Disclosures in Indonesia. This research gives a suggestion for further research to compare these ICSR disclosures in Indonesia with ICSR disclosures in other countries that have Islamic banking, by using other measure variables of financial performance, to get more comprehensive model and real picture.

Keywords: ROA, ROE, IER, NIM, company size, age of the company, audit type, Islamic banking

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Authors: Antoine F. Dedewanou, Eric N. Ekpinda

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We investigate whether and how deposit insurance program affects savings decisions in the Economic Community of Central African States (ECCAS). Specifically, using the World Bank’s 2014 and 2011 Global Financial Inclusion (Global Findex) databases, we apply special regressor approach. We find that the deposit insurance program increases significantly, everything else equal, the probability that people save their money at a financial institution by 11 percentage points in Gabon, by 22.2 percentage points in DR Congo and by 15.1 percentage points in Chad. These effects are matched with positive effects of age and education level. But in Cameroon, the effect of deposit insurance is not significant. The policies aimed at fostering financial inclusion will be more effective if there is a deposit insurance scheme in place, along with awareness among young people, and education programs. JEL Classification: G21, O12, O16

Keywords: deposit insurance, savings, special regressor, ECCAS countries

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Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

Abstract:

Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

Procedia PDF Downloads 379