Search results for: electronic data interchange

Authors: M. Wendeker, K. Siadkowska, P. Magryta, Z. Czyz, K. Skiba

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In the paper environmental impact analysis the optimal Diesel engine for a light helicopter was performed. The paper consist an answer to the question of what the optimal Diesel engine for a light helicopter is, taking into consideration its expected performance and design capacity. The use of turbocharged engine with self-ignition and an electronic control system can substantially reduce the negative impact on the environment by decreasing toxic substance emission, fuel consumption and therefore carbon dioxide emission. In order to establish the environmental benefits of the diesel engine technologies, mathematical models were created, providing additional insight on the environmental impact and performance of a classic turboshaft and an advanced diesel engine light helicopter, incorporating technology developments.

Keywords: diesel engine, helicopter, simulation, environmental impact

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Authors: Kaddi Mohammed, A. Benatiallah, D. Benatiallah

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Data grid is a technology that has full emergence of new challenges, such as the heterogeneity and availability of various resources and geographically distributed, fast data access, minimizing latency and fault tolerance. Researchers interested in this technology address the problems of the various systems related to the industry such as task scheduling, load balancing and replication. The latter is an effective solution to achieve good performance in terms of data access and grid resources and better availability of data cost. In a system with duplication, a coherence protocol is used to impose some degree of synchronization between the various copies and impose some order on updates. In this project, we present an approach for placing replicas to minimize the cost of response of requests to read or write, and we implement our model in a simulation environment. The placement techniques are based on a cost model which depends on several factors, such as bandwidth, data size and storage nodes.

Keywords: response time, query, consistency, bandwidth, storage capacity, CERN

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Authors: Ahmad B. Musamih, Ahmad A. Albloushi, Ahmed H. Alshemeili, Abdulaziz Y. Alfili, Ala A. Hussien

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This paper proposes a universal wireless battery charger design for portable electronic devices. As the number of portable electronics devices increases, the demand for more flexible and reliable charging techniques is becoming more urgent. A wireless battery charger differs from a traditional charger in the way the power transferred to the battery. In the latter, the power is transferred through electrical wires that connect the charger terminals to the battery terminals, while in the former; the power is transferred by induction without electrical connections. With a detection algorithm that detects the battery size and chemistry, the proposed charger will be able to accommodate a wide range of applications, and will allow a more flexible and reliable option to most of today’s portable electronics.

Keywords: efficiency, magnetically-coupled resonators, resonance frequency, wireless power transfer

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Authors: Yael Wolff Sagy, Yiska Loewenberg Weisband, Vered Kaufman Shriqui, Michal Krieger, Arie Ben Yehuda, Ronit Calderon Margalit

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Background: Obesity is both a risk factor and common comorbidity of diabetes. Obesity impedes the achievement of glycemic control, and enhances damage caused by hyperglycemia to blood vessels; thus it increases diabetes-related complications. This study assessed the prevalence of obesity and morbid obesity among Israeli adults with diabetes, and estimated disparities associated with sex and socioeconomic position (SEP). Methods: A cross-sectional study was conducted in the setting of the Israeli National Program for Quality Indicators in Community Healthcare. Data on all the Israeli population is retrieved from electronic medical records of the four health maintenance organizations (HMOs). The study population included all Israeli patients with diabetes aged 20-64 with documented body mass index (BMI) in 2016 (N=180,451). Diabetes was defined as the existence of one or more of the following criteria: (a) Plasma glucose level >200 mg% in at least two tests conducted at least one month apart in the previous year; (b) HbA1c>6.5% at least once in the previous year (c) at least three prescriptions of diabetes medications were dispensed during the previous year. Two measures were included: the prevalence of obesity (defined as last BMI≥ 30 kg/m2 and <35 kg/m2) and the prevalence of morbid obesity (defined as last BMI≥ 35 kg/m2) in individuals aged 20-64 with diabetes. The cut-off value for morbid obesity was set in accordance with the eligibility criteria for bariatric surgery in diabetics. Data were collected by the HMOs and aggregated by age, sex and SEP. SEP was based on statistical areas ranking by the Israeli Central Bureau of Statistics and divided into 4 categories, ranking from 1 (lowest) to 4 (highest). Results: BMI documentation among adults with diabetes was 84.9% in 2016. The prevalence of obesity in the study population was 30.5%. Although the overall rate was similar in both sexes (30.8% in females, 30.3% in males), SEP disparities were stronger in females (32.7% in SEP level 1 vs. 27.7% in SEP level 4; 18.1% relative difference) compared to males (30.6% in SEP level 1 vs. 29.3% in SEP level 4; 4.4% relative difference). The overall prevalence of morbid obesity in this population was 20.8% in 2016. The rate among females was almost double compared to the rate in males (28.1% and 14.6%, respectively). In both sexes, the prevalence of morbid obesity was strongly associated with lower SEP. However, in females, disparities between SEP levels were much stronger (34.3% in SEP level 1 vs. 18.7% in SEP level 4; 83.4% relative difference) compared to SEP-disparities in males (15.7% in SEP level 1 vs. 12.3% in SEP level 4; 27.6% relative difference). Conclusions: The overall prevalence of BMI≥ 30 kg/m2 among adults with diabetes in Israel exceeds 50%; and the prevalence of morbid obesity suggests that 20% meet the BMI-criteria for bariatric surgery. Prevalence rates show major SEP- and sex-disparities; especially strong SEP disparities in morbid obesity among females. These findings highlight the need for greater consideration of different population groups when implementing interventions.

Keywords: diabetes, health disparities, health policy, obesity, socio-economic position

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Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: N. Samarinas, C. Evangelides, C. Vrekos

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The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: classification, fuzzy logic, tolerance relations, rainfall data

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Authors: Maged Assem Soliman Mossallam

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One of the main prospectives on the demand of space exploration is to reduce the costs and efforts for satellite design. Concerning this issue satellite down scaling attracts space scientists and engineers. Picosatellite is the smallest category of satellites. The overall mass is less than 1 kg and dimensions are 10x10x3 cm3. Thermal control target is to keep the Pico-satellite board temperature within the permissible limits of temperature. Thermal design is completely passive which relies mainly on the enhancement of the thermo-optical properties of aluminum using anodization. Transient analysis is given for two different orbits, ISS orbit and 600 km altitude orbit. Results show that board temperature lies within 3 oC to 22 oC using black anodization which is a permissible limit for the satellite internal electronic board.

Keywords: satellite thermal control, small satellites, thermooptical properties , transient orbit analysis

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Authors: S. Anastasiou, C. Nathanailides

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The purpose of this study is to examine the possible link between employee and customer satisfaction. The service provided by employees, help to build a good relationship with customers and can help at increasing their loyalty. Published data for job satisfaction and indicators of customer services were gathered from relevant published works which included data from five different countries. The reviewed data indicate a significant correlation between indicators of customer and employee satisfaction in the Banking sector. There was a significant correlation between the two parameters (Pearson correlation R2=0.52 P<0.05) The reviewed data provide evidence that there is some practical evidence which links these two parameters.

Keywords: job satisfaction, job performance, customer’ service, banks, human resources management

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Authors: Abdusalam Gsiea, Ramadan Al-habashi, Mohamed Atumi, Khaled Atmimi

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We present a theoretical investigation on the structural, electronic properties and vibrational mode of nitrogen impurities in ZnO. The atomic structures, formation and transition energies and vibrational modes of (NO3)i interstitial or NO4 substituting on an oxygen site ZnO were computed using ab initio total energy methods. Based on Local density functional theory, our calculations are in agreement with one interpretation of bound-excition photoluminescence for N-doped ZnO. First-principles calculations show that (NO3)i defects interstitial or NO4 substituting on an Oxygen site in ZnO are important suitable impurity for p-type doping in ZnO. However, many experimental efforts have not resulted in reproducible p-type material with N2 and N2O doping. by means of first-principle pseudo-potential calculation we find that the use of NO or NO2 with O gas might help the experimental research to resolve the challenge of achieving p-type ZnO.

Keywords: DFF, nitrogen, p-type, ZnO

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Authors: Suman Podder

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As Australian ‘Open Banking’ allows customers to share their financial data with accredited Third-Party Providers (‘TPPs’), it is necessary to evaluate whether the regulators have achieved the balance between protecting customer data privacy and promoting data-related innovation. Recognising the need to increase customers’ influence on their own data, and the benefits of data-related innovation, the Australian Government introduced ‘Consumer Data Right’ (‘CDR’) to the banking sector through Open Banking regulation. Under Open Banking, TPPs can access customers’ banking data that allows the TPPs to tailor their products and services to meet customer needs at a more competitive price. This facilitated access and use of customer data will promote innovation by providing opportunities for new products and business models to emerge and grow. However, the success of Open Banking depends on the willingness of the customers to share their data, so the regulators have augmented the protection of data by introducing new privacy safeguards to instill confidence and trust in the system. The dilemma in policymaking is that, on the one hand, lenient data privacy laws will help the flow of information, but at the risk of individuals’ loss of privacy, on the other hand, stringent laws that adequately protect privacy may dissuade innovation. Using theoretical and doctrinal methods, this paper examines whether the privacy safeguards under Open Banking will add to the compliance burden of the participating financial institutions, resulting in the undesirable effect of stifling other policy objectives such as innovation. The contribution of this research is three-fold. In the emerging field of customer data sharing, this research is one of the few academic studies on the objectives and impact of Open Banking in the Australian context. Additionally, Open Banking is still in the early stages of implementation, so this research traces the evolution of Open Banking through policy debates regarding the desirability of customer data-sharing. Finally, the research focuses not only on the customers’ data privacy and juxtaposes it with another important objective of promoting innovation, but it also highlights the critical issues facing the data-sharing regime. This paper argues that while it is challenging to develop a regulatory framework for protecting data privacy without impeding innovation and jeopardising yet unknown opportunities, data privacy and innovation promote different aspects of customer welfare. This paper concludes that if a regulation is appropriately designed and implemented, the benefits of data-sharing will outweigh the cost of compliance with the CDR.

Keywords: consumer data right, innovation, open banking, privacy safeguards

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Authors: Hyun-Woo Cho

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Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

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Authors: M. Fakhim Lamrani, M. Ouchri, M. Belaiche, El Kenz, M. Loulidi, A. Benyoussef

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Electronic and magnetic calculations based on density functional theory within the generalized gradient approximation for II-VI compound semiconductor TiO2 doped with single impurity Os and Mo; these compounds are a half metallic ferromagnet in their ground state with a total magnetic moment of 2 μB for both systems. Then, TiO2 doped with double impurities Os and Mo have been performed. As result, Ti1-2xOsxMoxO2 with x=0.065 is half-metallic antiferromagnets with 100% spin polarization of the conduction electrons crossing the Fermi level, without showing a net magnetization. Moreover, Ti14OsMoO32 compound is stable energetically than Ti1-xMoxO2 and Ti1-xOsxO2. The antiferromagnetic interaction in Ti1-2xOsxMoxO2 system is attributed to the double exchange mechanism, and the latter could also be the origin of their half metallic.

Keywords: diluted magnetic semiconductor, half-metallic antiferromagnetic, augmented spherical wave method

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Authors: Imme Petersen, Wiebke Sick, Regine Kollek

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In systems medicine, high-throughput technologies produce large amounts of data on different biological and pathological processes, including (disturbed) gene expressions, metabolic pathways and signaling. The large volume of data of different types, stored in separate databases and often located at different geographical sites have posed new challenges regarding data handling and processing. Tools based on bioinformatics have been developed to resolve the upcoming problems of systematizing, standardizing and integrating the various data. However, the heterogeneity of data gathered at different levels of biological complexity is still a major challenge in data analysis. To build multilayer disease modules, large and heterogeneous data of disease-related information (e.g., genotype, phenotype, environmental factors) are correlated. Therefore, a great deal of attention in systems medicine has been put on data standardization, primarily to retrieve and combine large, heterogeneous datasets into standardized and incorporated forms and structures. However, this data-centred concept of standardization in systems medicine is contrary to the debate in science and technology studies (STS) on standardization that rather emphasizes the dynamics, contexts and negotiations of standard operating procedures. Based on empirical work on research consortia that explore the molecular profile of diseases to establish systems medical approaches in the clinic in Germany, we trace how standardized data are processed and shaped by bioinformatics tools, how scientists using such data in research perceive such standard operating procedures and which consequences for knowledge production (e.g. modeling) arise from it. Hence, different concepts and meanings of standardization are explored to get a deeper insight into standard operating procedures not only in systems medicine, but also beyond.

Keywords: data, science and technology studies (STS), standardization, systems medicine

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Authors: W. Ait Ahmed, M. Aggour, M. Naciri

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Extracting energy from biomass is an important alternative to produce different types of energy (heat, electricity, or both) assuring low pollution and better efficiency. It is a new yet reliable approach to reduce green gas emission by extracting methane from industry effluents and use it to power machinery. We focused in our project on using paper and mill effluents, treated in a UASB reactor. The methane produced is used in the factory’s power supply. The aim of this work is to develop an electronic system using Arduino platform connected to a gas sensor, to measure and display the curve of daily methane production on processing. The sensor will send the gas values in ppm to the Arduino board so that the later sends the RS232 hardware protocol. The code developed with processing will transform the values into a curve and display it on the computer screen.

Keywords: biogas, Arduino, processing, code, methane, gas sensor, program

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Authors: Kavian Khosravinia, Mohd Khair Hassan, Ribhan Zafira Abdul Rahman, Syed Abdul Rahman Al-Haddad

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The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request-response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

Keywords: CAN bus, OBD-II, vehicle data acquisition, connected cars, telemetry, Raspberry Pi3

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Authors: Sergio Zabala-Vargas, Miguel Jiménez-Barrera, Luz VArgas-Sánchez

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In recent years, information related to project management in organizations has been increasing exponentially. Performance data, management statistics, indicator results have forced the collection, analysis, traceability, and dissemination of project managers to be essential. In this sense, there are current trends to facilitate efficient decision-making in emerging technology projects, such as: Machine Learning, Data Analytics, Data Mining, and Big Data. The latter is the most interesting in this project. This research is part of the thematic line Construction methods and project management. Many authors present the relevance that the use of emerging technologies, such as Big Data, has taken in recent years in project management in the construction sector. The main focus is the optimization of time, scope, budget, and in general mitigating risks. This research was developed in the northeastern region of Colombia-South America. The first phase was aimed at diagnosing the use of emerging technologies (Big-Data) in the construction sector. In Colombia, the construction sector represents more than 50% of the productive system, and more than 2 million people participate in this economic segment. The quantitative approach was used. A survey was applied to a sample of 91 companies in the construction sector. Preliminary results indicate that the use of Big Data and other emerging technologies is very low and also that there is interest in modernizing project management. There is evidence of a correlation between the interest in using new data management technologies and the incorporation of Building Information Modeling BIM. The next phase of the research will allow the generation of guidelines and strategies for the incorporation of technological tools in the construction sector in Colombia.

Keywords: big data, building information modeling, tecnology, project manamegent

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Authors: Prashant Neupane, Asmi Pandey, Mumna Ehsan, Katie Davies, Richard Lowsby

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Introduction/Background & aims: Safe and effective prescribing in hospitals, directly and indirectly, impacts the health of the patients. Even though digital prescribing in the National Health Service (NHS), UK has been used in lots of tertiary centers along with district general hospitals, a significant number of NHS trusts are still using paper prescribing. We came across lots of irregularities in our daily clinical practice when we are doing paper prescribing. The main aim of the study was to assess how safely and effectively are we prescribing at our hospital where there is no access to digital prescribing. Method/Summary of work: We conducted a prospective audit in the critical care department at Mid Cheshire Hopsitals NHS Foundation Trust in which 20 prescription charts from different patients were randomly selected over a period of 1 month. We assessed 16 multiple categories from each prescription chart and compared them to the standard trust guidelines on prescription. Results/Discussion: We collected data from 20 different prescription charts. 16 categories were evaluated within each prescription chart. The results showed there was an urgent need for improvement in 8 different sections. In 85% of the prescription chart, all the prescribers who prescribed the medications were not identified. Name, GMC number and signature were absent in the required prescriber identification section of the prescription chart. In 70% of prescription charts, either indication or review date of the antimicrobials was absent. Units of medication were not documented correctly in 65% and the allergic status of the patient was absent in 30% of the charts. The start date of medications was missing and alternations of the medications were not done properly in 35%of charts. The patient's name was not recorded in all desired sections of the chart in 50% of cases and cancellations of the medication were not done properly in 45% of the prescription charts. Conclusion(s): From the audit and data analysis, we assessed the areas in which we needed improvement in prescription writing in the Critical care department. However, during the meetings and conversations with the experts from the pharmacy department, we realized this audit is just a representation of the specialized department of the hospital where access to prescribing is limited to a certain number of prescribers. But if we consider bigger departments of the hospital where patient turnover is much more, the results could be much worse. The findings were discussed in the Critical care MDT meeting where suggestions regarding digital/electronic prescribing were discussed. A poster and presentation regarding safe and effective prescribing were done, awareness poster was prepared and attached alongside every bedside in critical care where it is visible to prescribers. We consider this as a temporary measure to improve the quality of prescribing, however, we strongly believe digital prescribing will help to a greater extent to control weak areas which are seen in paper prescribing.

Keywords: safe prescribing, NHS, digital prescribing, prescription chart

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Authors: Priscilla Marcus

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The mass media was a force to reckon with in the struggle and attainment of Nigeria’s independence in 1960 and since then, the Nigerian media has carved a niche for itself in performing its traditional role of education, information, entertainment, shaping of opinions and swinging of views of the society on knotty national issues. Boko Haram insurgency in Nigeria which emerged from an unnoticed, negligible and quiet beginning, has turned out daring, monstrous and unstoppable. This paper examines The Media and Reportage of Boko Haram Insurgency in Nigeria and to suggest strategies the mass media could adopt in combating this form of terrorism. Data for the study were collected from a variety of sources including the print and electronic media. The major observation of this study is that the mass media have an enormous role to play if Boko Haram’s activities are to be combated. It argued that even though the media houses are just doing their job – reporting the incident(s) as they occur, thus keeping the citizens abreast of facts; the rate at which news keeps coming regarding the activities of the sect has portrayed the media as information dissemination and terror campaign spread. It also argued that the ceaseless reporting has not translated to a decrease in the activities of the sect or increase in the level of government actions to check the insurgency. However, the information being disseminated is enlightening the populace and also creating an atmosphere of panic and insecurity. It further argued that the media should move beyond mere recitation of events to providing the public with knowledge needed to make things better. This is because the sect has been accorded too much undeserved and unnecessary publicity while the government on the other hand has been portrayed, albeit indirectly as a weak organization incapable of handling the ‘more organized’ Boko Haram. The study, concluded that, to effectively address the problem of this form of terrorism in Nigeria, the media have to brace up to the task of uncovering activities of the sect in appreciation of their watch-dog role.

Keywords: Boko Haram, insurgency, mass media, Nigeria

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Authors: A. Fahim, Mutahira N. Naseem

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SPAM is any unwanted electronic message or material in any form posted to many people. As the world is growing as global world, social networking sites play an important role in making world global providing people from different parts of the world a platform to meet and express their views. Among different social networking sites facebook become the leading one. With increase in usage different users start abusive use of facebook by posting or creating ways to post spam. This paper highlights the potential spam types nowadays facebook users faces. This paper also provide the reason how user become victim to spam attack. A methodology is proposed in the end discusses how to handle different types of spam.

Keywords: artificial neural networks, facebook spam, social networking sites, spam filter

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

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Authors: Nazaket Gazieva

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Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations.

Keywords: phonogram, speech signal, temporal characteristics, fundamental frequency, biometric fingerprints

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Authors: Hussein Shaman

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This study introduces an innovative design for an RF phase shifter that can maintain a consistent phase shift across a broad spectrum of frequencies. The proposed design integrates an adaptive control system into a reflective-type phase shifter, typically showing frequency-related variations. Adjusting the DC voltage according to the frequency ensures a more reliable phase shift across the frequency span of operation. In contrast, conventional frequency-dependent reflective-type phase shifters may exhibit significant fluctuations in phase shifts exceeding 60 degrees in the same bandwidth. The proposed phase shifter is configured to deliver a 90-degree operation with an expected deviation of around 15 degrees. The fabrication of the phase shifter and adaptive control circuit has been verified through experimentation, with the measured outcomes aligning with the simulation results.

Keywords: phase shifter, adaptive control, varactors, electronic circuits.

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Authors: Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

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This study investigates the task of identifying musical instruments in polyphonic compositions using Convolutional Neural Networks (CNNs) from spectrogram inputs, focusing on binary classification. The model showed promising results, with an accuracy of 97% on solo instrument recognition. When applied to polyphonic combinations of 1 to 10 instruments, the overall accuracy was 64%, reflecting the increasing challenge with larger ensembles. These findings contribute to the field of Music Information Retrieval (MIR) by highlighting the potential and limitations of current approaches in handling complex musical arrangements. Future work aims to include a broader range of musical sounds, including electronic and synthetic sounds, to improve the model's robustness and applicability in real-time MIR systems.

Keywords: binary classifier, CNN, spectrogram, instrument

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Authors: Francky Fouedjio

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Multivariate geostatistical data have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations within the same cluster are more similar while clusters are different from each other, in some sense. Spatially contiguous clusters can significantly improve the interpretation that turns the resulting clusters into meaningful geographical subregions. In this paper, we develop an agglomerative hierarchical clustering approach that takes into account the spatial dependency between observations. It relies on a dissimilarity matrix built from a non-parametric kernel estimator of the spatial dependence structure of data. It integrates existing methods to find the optimal cluster number and to evaluate the contribution of variables to the clustering. The capability of the proposed approach to provide spatially compact, connected and meaningful clusters is assessed using bivariate synthetic dataset and multivariate geochemical dataset. The proposed clustering method gives satisfactory results compared to other similar geostatistical clustering methods.

Keywords: clustering, geostatistics, multivariate data, non-parametric

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Authors: Sara ElElimy, Samir Moustafa

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Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

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Authors: Nidhin Dani Abraham, T. K. Sri Shilpa

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Asset liability management is an important aspect in banking business. Moreover, the today’s banking is based on BASEL III which strictly regulates on the counterparty default. This paper focuses on prediction and analysis of counter party default risk, which is a type of risk occurs when the customers fail to repay the amount back to the lender (bank or any financial institutions). This paper proposes an approach to reduce the counterparty risk occurring in the financial institutions using an appropriate data mining technique and thus predicts the occurrence of NPA. It also helps in asset building and restructuring quality. Liability management is very important to carry out banking business. To know and analyze the depth of liability of bank, a suitable technique is required. For that a data mining technique is being used to predict the dormant behaviour of various deposit bank customers. Various models are implemented and the results are analyzed of saving bank deposit customers. All these data are cleaned using data cleansing approach from the bank data warehouse.

Keywords: data mining, asset liability management, BASEL III, banking

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Authors: Mohsen Khaledian, Razali Ismail, Mehdi Saeidmanesh, Mahdiar Hosseinghadiry

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A semi-analytical model for impact ionization coefficient of graphene nanoribbon (GNR) is presented. The model is derived by calculating probability of electrons reaching ionization threshold energy Et and the distance traveled by electron gaining Et. In addition, ionization threshold energy is semi-analytically modeled for GNR. We justify our assumptions using analytic modeling and comparison with simulation results. Gaussian simulator together with analytical modeling is used in order to calculate ionization threshold energy and Kinetic Monte Carlo is employed to calculate ionization coefficient and verify the analytical results. Finally, the profile of ionization is presented using the proposed models and simulation and the results are compared with that of silicon.

Keywords: nanostructures, electronic transport, semiconductor modeling, systems engineering

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Authors: Chris Suma, Yingcai Xiao

Abstract:

This paper presents Parallel Coordinates on a Spiral Surface (PCoSS), a parallel coordinate based interactive visualization method for high-dimensional data, and a test implementation of the method. Plots generated by the test system are compared with those generated by XDAT, a software implementing traditional parallel coordinates. Traditional parallel coordinate plots can be cluttered when the number of data points is large or when the dimensionality of the data is high. PCoSS plots display multivariate data on a 3D spiral surface and allow users to see the whole picture of high-dimensional data with less cluttering. Taking advantage of the 3D display environment in PCoSS, users can further reduce cluttering by zooming into an axis of interest for a closer view or by moving vantage points and by reorienting the viewing angle to obtain a desired view of the plots.

Keywords: human computer interaction, parallel coordinates, spiral surface, visualization

Procedia PDF Downloads 12

Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

Abstract:

Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

Procedia PDF Downloads 201

Authors: D. Majumdar, M. Baskey, S. K. Saha

Abstract:

Graphene has already been identified as a promising material for future carbon based electronics. To develop graphene technology, the fabrication of a high quality P-N junction is a great challenge. In the present work, we have described a simple and general technique to grow single crystalline polyaniline (PANI) films on graphene sheets using in situ polymerization via the oxidation-reduction of aniline monomer and graphene oxide, respectively, to fabricate a high quality P-N junction, which shows diode-like behavior with a remarkably low turn-on voltage (60 mV) and high rectification ratio (1880:1) up to a voltage of 0.2 Volt. The origin of these superior electronic properties is the preferential growth of a highly crystalline PANI film as well as lattice matching between the d-values [~2.48 Å] of graphene and {120} planes of PANI.

Keywords: epitaxial growth, PANI, reduced graphene oxide, rectification ratio

Procedia PDF Downloads 289