Search results for: mobile performance monitoring

Authors: Md Omar Faruq Howlader, Tariq Pervez Sattar, Sandra Dudley

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This paper describes the design process of a 200 MHz Ground Penetrating Radar (GPR) and a battery powered concrete vertical concrete surface climbing mobile robot. The key design feature is a miniaturized 200 MHz dipole antenna using additional radiating arms and procedure records a reduction of 40% in length compared to a conventional antenna. The antenna set is mounted in front of the robot using a servo mechanism for folding and unfolding purposes. The robot’s adhesion mechanism to climb the reinforced concrete wall is based on neodymium permanent magnets arranged in a unique combination to concentrate and maximize the magnetic flux to provide sufficient adhesion force for GPR installation. The experiments demonstrated the robot’s capability of climbing reinforced concrete wall carrying the attached prototype GPR system and perform floor-to-wall transition and vice versa. The developed GPR’s performance is validated by its capability of detecting and localizing an aluminium sheet and a reinforcement bar (rebar) of 12 mm diameter buried under a test rig built of wood to mimic the concrete structure environment. The present robotic GPR system proves the concept of feasibility of undertaking inspection procedure on large concrete structures in hazardous environments that may not be accessible to human inspectors.

Keywords: climbing robot, dipole antenna, ground penetrating radar (GPR), mobile robots, robotic GPR

Procedia PDF Downloads 272

Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

Procedia PDF Downloads 172

Authors: Zhi Liu, Hui Jiang, Jin Li, Kunhao Chen, Langfang Zhang

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Fast acquisition of the seismic information and accurate assessment of the earthquake disaster is the key problem for emergency rescue after a destructive earthquake. In order to meet the requirements of the earthquake emergency response and rescue for the cities and counties, a quasi real-time comprehensive evaluation system for earthquake disaster is developed. Based on monitoring data of Micro-Electro-Mechanical Systems (MEMS) strong motion network, structure database of a county area and the real-time disaster information by the mobile terminal after an earthquake, fragility analysis method and dynamic correction algorithm are synthetically obtained in the developed system. Real-time evaluation of the seismic disaster in the county region is finally realized to provide scientific basis for seismic emergency command, rescue and assistant decision.

Keywords: quasi real-time, earthquake disaster data collection, MEMS accelerometer, dynamic correction, comprehensive evaluation

Procedia PDF Downloads 211

Authors: Chayma Bahar, Chokri Baccouch, Hedi Sakli, Nizar Sakli

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Harvesting and transport of optical and radiofrequency signals are a topical subject with multiple challenges. In this paper, we present a Optical RECTENNA system. We propose here a hybrid system solar cell antenna for 5G mobile communications networks. Thus, we propose rectifying circuit. A parametric study is done to follow the influence of load resistance and input power on Optical RECTENNA system performance. Thus, we propose a solar cell antenna structure in the frequency band of future 5G standard in 2.45 GHz bands.

Keywords: antenna, IoT, optical rectenna, solar cell

Procedia PDF Downloads 177

Authors: Mark Ivan Roblas

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The Science Explorer is a mobile learning science facility in the Philippines. It is a bus that travels to different provinces in the country bringing interactive science modules facilitated by scientists from the industry and academe. The project aims to entice students to get into careers in science through interactive science modules and interaction with real-life scientists. This article looks into the effectiveness of its modules as a communication source and message to encourage high school students to get into careers in the future. The study revealed that as the Science Explorer modules are able to retain students to stay in science careers of their choice and even convert some to choose from non-science to a science degree, it still lacks in penetrating the belief system of the students and influencing them to take a scientific career path.

Keywords: informal science, mobile science, science careers, science education

Procedia PDF Downloads 219

Authors: Yuni Rochmawati, Luluk Il Mukarromah

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Android is a mobile operating system (OS) based on the linux kerrnel and currently developed by google. With a user interface based on direct manipulation, Android is designed primarily for touchscreen mobile deviced such as smartphone and tablet computer, with specialized user interface for television (Android TV), cars (Android Auto), and wrist watches (Android Wear). Now, almost all peoples using smartphone. Smartphone seems to be a must-have object, because smartphone has many benefits. In addition, of course smartphone have many benefits for education, like resume of lesson that form of e-book. However, this article is not about resume of lesson. This article is about practical based on android, exactly for physics. Therefore, we will explain our idea about physics’s practical based on android and for output, we wish many students will be like to studying physics and always remember about physics’s phenomenon by physics’s practical based on android.

Keywords: android, smartphone, physics, practical

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Authors: Muhammad Akhtaruzzaman

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The impact of corporate environmental social and governance (ESG) on financial performance is often difficult to quantify despite the ESG related theories predict that ESG performance improves financial performance of a company. This research examines the link between corporate ESG performance and the financial performance of the NZX (New Zealand Stock Exchange) listed companies. For this purpose, this research utilizes mixed methods approaches to examine and understand this link. While quantitative results found no robust evidence of such a link, however, the qualitative analysis of content data suggests a strong cooccurrence exists between ESG performance and financial performance. The findings of this research have important implications for policymakers to support higher ESG-performing companies and for management practitioners to develop ESG-related strategies.

Keywords: ESG, financial performance, New Zealand firms, thematic analysis, mixed methods

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Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

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It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

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Authors: Frank Hespeler, Giuseppe Loiacono

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We propose measures for systemic risk generated through intra-sectorial interdependencies in the hedge fund sector. These measures are based on variations in the average cross-effects of funds showing significant interdependency between their individual returns and the moments of the sector’s return distribution. The proposed measures display a high ability to identify periods of financial distress, are robust to modifications in the underlying econometric model and are consistent with intuitive interpretation of the results.

Keywords: hedge funds, systemic risk, vector autoregressive model, risk monitoring

Procedia PDF Downloads 324

Authors: B. G. Abiona, E. O. Fakoya, S. O. Adeogun, J. O. Blessed

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This study assessed the influence of communication pattern on agricultural employees’ job performance. Data were collected from 61 randomly selected respondents using a structured questionnaire. Perceived communication pattern that influence job performance include: the attitude of the administrators (x̅ = 3.41, physical barriers to communication flow among employees (x̅ = 3.21). Major challenges to respondents’ job performance were different language among employees (x̅ = 3.12), employees perception on organizational issues (x̅ = 3.09), networking (x̅ = 2.88), and unclear definition of work (x̅ = 2.74). A significant relationship was found between employees’ perceived communication pattern (r = 0.423, p < 0.00) and job performance. Information must be well designed in such a way that would positively influence employees’ job performance as this is essential in any agricultural organizations.

Keywords: communication pattern, job performance, agricultural employees, constraint, administrators, attitude

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Authors: Angela Meyer

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The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

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Authors: Doaa Alhaboby

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Behavior change is a complex process that often requires ongoing support and guidance. Telecoaching programs have emerged as effective tools in facilitating behavior change by providing personalized support remotely. This abstract explores the lessons learned from a randomized controlled trial (RCT) evaluation of a telecoaching program focused on behavior change for Diabetics and discusses strategies for implementing these lessons to overcome the challenge of making physical activity a habit. The telecoaching program involved participants engaging in regular coaching sessions delivered via phone calls. These sessions aimed to address various aspects of behavior change, including goal setting, self-monitoring, problem-solving, and social support. Over the course of the program, participants received personalized guidance tailored to their unique needs and preferences. One of the key lessons learned from the RCT was the importance of engagement, readiness to change and the use of technology. Participants who set specific, measurable, attainable, relevant, and time-bound (SMART) goals were more likely to make sustained progress toward behavior change. Additionally, regular self-monitoring of behavior and progress was found to be instrumental in promoting accountability and motivation. Moving forward, implementing the lessons learned from the RCT can help individuals overcome the hardest part of behavior change: making physical activity a habit. One strategy is to prioritize consistency and establish a regular routine for physical activity. This may involve scheduling workouts at the same time each day or week and treating them as non-negotiable appointments. Additionally, integrating physical activity into daily life routines and taking into consideration the main challenges that can stop the process of integrating physical activity routines into the daily schedule can help make it more habitual. Furthermore, leveraging technology and digital tools can enhance adherence to physical activity goals. Mobile apps, wearable activity trackers, and online fitness communities can provide ongoing support, motivation, and accountability. These tools can also facilitate self-monitoring of behavior and progress, allowing individuals to track their activity levels and adjust their goals as needed. In conclusion, telecoaching programs offer valuable insights into behavior change and provide strategies for overcoming challenges, such as making physical activity a habit. By applying the lessons learned from these programs and incorporating them into daily life, individuals can cultivate sustainable habits that support their long-term health and well-being.

Keywords: lifestyle, behavior change, physical activity, chronic conditions

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Authors: Violina Angelova, Krasimir Ivanov, Stefan Krustev, Dimitar Dimitrov

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Availability of a metal is characterised by its quantity transgressing from soil into different extractants or by its content in plants. In literature, the terms 'available forms of compounds' and 'mobile' are often considered as equivalents of the term 'accessible' to plants. Rapid and a sufficiently reliable method for defining the accessible for plants forms turns out to be their extraction through different extractants, imitating the functioning of the root system. As a criterion for the pertinence of the extractant to this purpose usually serves the significant statistic correlation between the extracted quantities of the element from soil and its content in plants. The aim of this work was to evaluate the effectiveness of various extractions (DTPA-TEA, AB-DTPA, Mehlich 3, 0.01 M CaCl₂, 1M NH₄NO₃) for the determination of bioavailability of heavy metals in industrially polluted soils from the metallurgical activity near Plovdiv and Kardjali, Bulgaria. Quantity measurements for contents of heavy metals were performed with ICP-OES. The results showed that extraction capacity was as follows: Mehlich 3>ABDTPA>DTPA-TEA>CaCl₂>NaNO₃. The content of the mobile form of heavy metals depends on the nature of metal ion, the nature of extractant and pH. The obtained results show that CaCl₂ extracts a greater quantity of mobile forms of heavy metals than NH₄NO₃. DTPA-TEA and AB-DTPA are capable of extracting from the soil not only the heavy metals participating in the exchange processes but also the heavy metals bound in carbonates and organic complexes, as well as bound and occluded in oxide and secondary clay minerals. AB-DTPA extracts a bit more heavy metals than DTPA-TEA. The darker color of the solutions obtained with AB-DTPA indicates that considerable quantities organic matter are being destructed. A comparison of the mobile forms of heavy metals extracted from clean and highly polluted soils has revealed that in the polluted soils the greater portion of heavy metals exists in a mobile form. High correlation coefficients are obtained between the metals extracted with different extractants and their total content in soil (r=0.9). A positive correlation between the pH, soil organic matter and the extracted quantities of heavy metals has been found. The results of correlation analysis revealed that the heavy metals extracted by DTPA-TEA, AB-DTPA, Mehlich 3, CaCl₂ and NaNO₃ correlated significantly with plant uptake. Significant correlation was found between DTPA-TEA, AB-DTPA, and CaCl₂ with heavy metals concentration in plants. Application of extracting methods contains chelating agents would be recommended in the future research onthe availabilityof heavy metals in polluted soils.

Keywords: availability, chemical extractants, heavy metals, mobile forms

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Authors: Annu Sheokand, Vinay Kumar

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Hydrogen sulfide (H₂S) detection is essential for environmental monitoring and industrial safety due to its high toxicity, even at low concentrations. This study explores the H₂S gas sensing properties of Cu-doped Fe₂O₃ materials derived from metal-organic frameworks (MOFs), which offer high surface area and controlled porosity for optimized gas sensing. The structural and morphological characteristics of the synthesized material were thoroughly analyzed using techniques such as X-ray Diffraction (XRD), Field Emission Scanning Electron Microscopy (FE-SEM), and UV-Vis Spectroscopy. The resulting sensor exhibited remarkable sensitivity and selectivity, achieving a detection limit at the ppb level for H₂S. The study indicates that Cu doping significantly enhances the gas sensing performance of Fe₂O₃ by introducing abundant active sites within the material. These enhanced sensing properties emphasize the potential of MOF-derived Cu-doped Fe₂O₃ as a highly effective material for H₂S gas sensors in various applications.

Keywords: detection limit, doping, MOF, sensitivity, sensor

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Authors: Witthaya Mekhum, Wutthikorn Malikong

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The objective of this study is to investigate the increasing desktop computer performance after overclocking central processing unit or CPU by running a computer component at a higher clock rate (more clock cycles per second) than it was designed at the rate of 0.1 GHz for each level or 100 MHz starting at 4000 GHz-4500 GHz. The computer performance is tested for each level with 4 programs, i.e. Hyper PI ver. 0.99b, Cinebench R15, LinX ver.0.6.4 and WinRAR . After the CPU overclock, the computer performance increased. When overclocking CPU at 29% the computer performance tested by Hyper PI ver. 0.99b increased by 10.03% and when tested by Cinebench R15 the performance increased by 20.05% and when tested by LinX Program the performance increased by 16.61%. However, the performance increased only 8.14% when tested with Winrar program. The computer performance did not increase according to the overclock rate because the computer consists of many components such as Random Access Memory or RAM, Hard disk Drive, Motherboard and Display Card, etc.

Keywords: overclock, performance, central processing unit, computer

Procedia PDF Downloads 281

Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

Procedia PDF Downloads 175

Authors: Bryce Benson, Sooin Lee, Ashwin Belle

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Unrecognized or delayed identification of patient deterioration is a key cause of in-hospitals adverse events. Clinicians rely on vital signs monitoring to recognize patient deterioration. However, due to ever increasing nursing workloads and the manual effort required, vital signs tend to be measured and recorded intermittently, and inconsistently causing large gaps during patient monitoring. Additionally, during deterioration, the body’s autonomic nervous system activates compensatory mechanisms causing the vital signs to be lagging indicators of underlying hemodynamic decline. This study analyzes the predictive efficacy of the Analytic for Hemodynamic Instability (AHI) system, an automated tool that was designed to help clinicians in early identification of deteriorating patients. The lead time analysis in this retrospective observational study assesses how far in advance AHI predicted deterioration prior to the start of an episode of hemodynamic instability (HI) becoming evident through vital signs? Results indicate that of the 362 episodes of HI in this study, 308 episodes (85%) were correctly predicted by the AHI system with a median lead time of 57 minutes and an average of 4 hours (240.5 minutes). Of the 54 episodes not predicted, AHI detected 45 of them while the episode of HI was ongoing. Of the 9 undetected, 5 were not detected by AHI due to either missing or noisy input ECG data during the episode of HI. In total, AHI was able to either predict or detect 98.9% of all episodes of HI in this study. These results suggest that AHI could provide an additional ‘pair of eyes’ on patients, continuously filling the monitoring gaps and consequently giving the patient care team the ability to be far more proactive in patient monitoring and adverse event management.

Keywords: clinical deterioration prediction, decision support system, early warning system, hemodynamic status, physiologic monitoring

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Authors: Loghman Ansarian, Teoh Mei Lin

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In an attempt to increase oral proficiency of Iranian EFL learners, the researchers compared the effect of problem-based mobile-assisted language learning with the conventional language learning approach (Communicative Language Teaching) in Iran. The experimental group (n=37) went through PBL instruction and the control group (n=33) went through conventional instruction. The results of quantitative data analysis after 26 sessions of treatment revealed that PBL could positively affect participants' knowledge of grammar, vocabulary, spoken fluency, and pronunciation; however, in terms of task achievement, no significant effect was found. This study can have pedagogical implications for language teachers, and material developers.

Keywords: problem-based learning, spoken intelligibility, Iranian EFL context, cognitive learning

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Authors: Candra Irawan, David Yudianto, Ahsanu Nadiyya, Dewi Anna Br Sitepu, Hanafi, Erna Styani

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Jelly drink was produced from a combination of both natural and synthetic materials, such as acesulfame potassium (acesulfame-K) as synthetic sweetener material. Acesulfame-K content in jelly drink could be determined by High-Performance Liquid Chromatography (HPLC), but this method needed validation due to having a change on the reagent addition step which skips the carrez addition and comparison of mix mobile phase (potassium dihydrogen phosphate and acetonitrile) with ratio from 75:25 to 90:10 to be more efficient and cheap. This study was conducted to evaluate the performance of determination method for acesulfame-K content in the jelly drink by HPLC. The method referred to Deutsches Institut fur Normung European Standard International Organization for Standardization (DIN EN ISO):12856 (1999) about Foodstuffs, Determination of acesulfame-K, aspartame and saccharin. The result of the correlation coefficient value (r) on the linearity test was 0.9987 at concentration range 5-100 mg/L. Detection limit value was 0.9153 ppm, while the quantitation limit value was 1.1932 ppm. The recovery (%) value on accuracy test for sample concentration by spiking 100 mg/L was 102-105%. Relative Standard Deviation (RSD) value for precision and homogenization tests were 2.815% and 4.978%, respectively. Meanwhile, the comparative and stability tests were tstat (0.136) < ttable (2.101) and |µ1-µ2| (1.502) ≤ 0.3×CV Horwitz. Obstinacy test value was tstat < ttable. It can be concluded that the HPLC  method for the determination of acesulfame-K in jelly drink product by HPLC has been valid and can be used for analysis with good performance.

Keywords: acesulfame-K, jelly drink, HPLC, validation

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Authors: Lucas Bublitz, Michael Herdrich

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By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

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Authors: M. Manohari, S. Priyadharshini, K. Bajeer Sulthan, R. Santhanam, S. Chandrasekaran, B. Venkatraman

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In-vivo monitoring facility at Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam, caters to the monitoring of internal exposure of occupational radiation workers from various radioactive facilities of IGCAR. Internal exposure measurement is done using Na(Tl) based Scintillation detectors. Two types of whole-body counters, namely Shielded Chair Counter (SC) and Standing Whole-Body Monitor (SWBM), are being used. The shielded Chair is based on a NaI detector of 20.3 cm diameter and 10.15 cm thick. The chair of the system is shielded using lead shots of 10 cm lead equivalent and the detector with 8 cm lead bricks. Counting geometry is sitting geometry. Calibration is done using 95 percentile BOMAB phantom. The minimum Detectable Activity (MDA) for 137Cs for the 60s is 1150 Bq. Standing Wholebody monitor (SWBM) has two NaI(Tl) detectors of size 10.16 x 10.16 x 40.64 cm3 positioned serially, one over the other. It has a shielding thickness of 5cm lead equivalent. Counting is done in standup geometry. Calibration is done with the help of Ortec Phantom, having a uniform distribution of mixed radionuclides for the thyroid, thorax and pelvis. The efficiency of SWBM is 2.4 to 3.5 times higher than that of the shielded chair in the energy range of 279 to 1332 keV. MDA of 250 Bq for 137Cs can be achieved with a counting time of 60s. MDA for 131I in the thyroid was estimated as 100 Bq from the MDA of whole-body for one-day post intake. Standing whole body monitor is better in terms of efficiency, MDA and ease of positioning. In case of emergency situations, the optimal MDAs for in-vivo monitoring service are 1000 Bq for 137Cs and 100 Bq for 131I. Hence, SWBM is more suitable for the rapid screening of workers as well as the public in the case of an emergency. While a person reports for counting, there is a potential for external contamination. In SWBM, there is a feasibility to discriminate them as the subject can be counted in anterior or posterior geometry which is not possible in SC.

Keywords: minimum detectable activity, shielded chair, shielding thickness, standing whole body monitor

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Authors: Ebrahim Farahmand, Ali Mahani

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Wireless sensor networks (WSNs) can facilitate continuous monitoring of patients and increase early detection of emergency conditions and diseases. High density WSNs helps us to accurately monitor a remote environment by intelligently combining the data from the individual nodes. Due to energy capacity limitation of sensors, enhancing the lifetime and the reliability of WSNs are important factors in designing of these networks. The clustering strategies are verified as effective and practical algorithms for reducing energy consumption in WSNs and can tackle WSNs limitations. In this paper, an Energy-efficient weight-based Clustering Protocol (EWCP) is presented. Artificial retina is selected as a case study of WSNs applied in body sensors. Cluster heads’ (CHs) selection is equipped with energy efficient parameters. Moreover, cluster members are selected based on their distance to the selected CHs. Comparing with the other benchmark protocols, the lifetime of EWCP is improved significantly.

Keywords: WSN, healthcare monitoring, weighted based clustering, lifetime

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Authors: Adhila Sandra Devy, Evangeline Syalomita Silitonga

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The landscape of corporate governance and accountability has led to the emergence of Integrated Reporting (IR) in response to the shortcomings of traditional reporting frameworks. Developed by The International Integrated Reporting Council (IIRC), IR aims to offer stakeholders a comprehensive view of a company’s performance by integrating financial and non-financial disclosures. This study analyzes literature on Integrated Reporting and Corporate Financial Performance from 2013 to 2024, employing a descriptive analysis methodology. 31 relevant articles were gathered from various sources, indicating a positive correlation between integrated reporting and financial performance, albeit without conclusive evidence of long-term impact.

Keywords: integrated reporting, corporate financial performance, corporate performance, firm performance, bibliometric analysis

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Authors: Christina Tay

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This paper investigates the impact of Information and Communication Technology (ICT) on bilateral trade in goods. Empirical analysis is performed on the United States and 34 partnering countries from 2000 to 2013. Our econometric model fits the data well, explaining 52% of the variation in trade flows for goods trade, 53.2% of the variation in trade flows for goods export and 48% of the variation in trade flows for goods import. For every 10% increase in fixed broadband Internet subscribers per 100 people increases, goods trade by 7.9% and for every 5% increase in fixed broadband Internet subscribers per 100 people, goods export increases by 11%. For every 1% increase in fixed telephone line penetration per 100 people, goods trade increases by 26.3%, goods export increases by 24.4% and goods import increases by 24.8%. For every 1% increase in mobile-cellular telephone subscriptions, goods trade decreases by 29.6% and goods export decreases by 27.1%, whilst for every 0.01% increase in mobile-cellular telephone subscriptions, goods import decreases by 34.3%. For every 1% increase in the percentage of population who used the Internet from any location in the last 12 months Internet, goods trade increases by 32.5%, goods export increases by 38.9%, goods import increases by 33%. All our trade determinants as well as our ICT variables have significances on goods exports for the US. We can also draw from our study that the US relies more rather heavily on ICT for its goods export compared to goods import.

Keywords: bilateral trade, fixed broadband, fixed telephone, goods trade, information and communicative technologies, Internet, mobile-cellular phone

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Authors: Nalini C. Iyer, Shraddha H., Anagha B. Varahamurthy, Dikshith C. S., Ishwar G. Kubasad, Vinayak I. Karalatti, Pavan B. Mulimani

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The current scenario of the pandemic due to COVID-19 has led to the awareness among the people to avoid unneces-sary contact in public places. There is a need to avoid contact with physical objects to stop the spreading of infection. The contactless feature has to be included in the systems in public places wherever possible. For example, attendance monitoring systems with fingerprint biometric can be replaced with a contactless feature. One more important protocol followed in the current situation is temperature monitoring and screening. The paper describes an attendance system with a contactless feature and temperature screening for the university. The system displays a QR code to scan, which redirects to the student login web page only if the location is valid (the location where the student scans the QR code should be the location of the display of the QR code). Once the student logs in, the temperature of the student is scanned by the contactless temperature sensor (mlx90614) with an error of 0.5°C. If the temperature falls in the range of the desired value (range of normal body temperature), then the attendance of the student is marked as present, stored in the database, and the door opens automatically. The attendance is marked as absent in the other case, alerted with the display of temperature, and the door remains closed. The door is automated with the help of a servomotor. To avoid the proxy, IR sensors are used to count the number of students in the classroom. The hardware system consisting of a contactless temperature sensor and IR sensor is implemented on the microcontroller, NodeMCU.

Keywords: NodeMCU, IR sensor, attendance monitoring, contactless, temperature

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Authors: G. Usha, S. Kannimuthu, K. Mahalakshmi

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Mobile Adhoc Network (MANET) is one of the most promising technologies that have applications ranging from various portable devices to military networks. MANET has no fixed infrastructure and the security of such network is a big concern. Therefore, in order to operate MANET’s securely, the misbehavior and intrusions should be detected before the attackers affect the network communication. In this article, we make a comprehensive survey against black hole attack that is a serious threat against MANET that exploits the routing behavior of the MANET. We have given broad survey solutions that detect black hole attacks in MANET. This is achieved by analyzing the techniques involved in detecting the attacks in each scheme. Furthermore, we examine about the challenges to the researchers for constructing an in-depth solution against black hole attack.

Keywords: AODV, cross layer security, mobile Adhoc network (MANET), packet delivery ratio, single layer security

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Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

Abstract:

In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

Abstract:

The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, gazebo, Rviz, Turtlebot2, slam algorithms, 2d indoor environment, cartographer

Procedia PDF Downloads 144

Authors: Murtadha Kareem, Oliver Faust

Abstract:

Wearable biosensor systems can be designed and developed for health monitoring. There is much interest in both scientific and industrial communities established since 2007. Fundamentally, the cost of healthcare has increased dramatically and the world population is aging. That creates the need to harvest technological improvements with small bio-sensing devices, wireless-communication, microelectronics and smart textiles, that leads to non-stop developments of wearable sensor based systems. There has been a significant demand to monitor patient's health status while the patient leaves the hospital in his/her personal environment. To address this need, there are numerous system prototypes which has been launched in the medical market recently, the aim of that is to provide real time information feedback about patient's health status, either to the patient himself/herself or direct to the supervising medical centre station, while being capable to give a notification for the patient in case of possible imminent health threatening conditions. Furthermore, wearable health monitoring systems comprise new techniques to address the problem of managing and monitoring chronic heart diseases for elderly people. Wearable sensor systems for health monitoring include various types of miniature sensors, either wearable or implantable. To be specific, our proposed system able to measure essential physiological parameter, such as heart rate signal which could be transmitted through Bluetooth to the cloud server in order to store, process, analysis and visualise the data acquisition. The acquired measurements are connected through internet of things to a central node, for instance an android smart phone or tablet used for visualising the collected information on application or transmit it to a medical centre.

Keywords: Wearable sensor, Heart rate, Internet of things, Chronic heart disease

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Authors: Babatunde Femi Bakare

Abstract:

Groundwater quality was evaluated at a site for three years after the site was used for entrenchment of Ventilated Improved Pit (VIP) latrine sludge. Analysis performed on the soil characteristics at the entrenchment site indicated that, the soils at the entrenchment site are predominantly sandy. Depth of the water table at the entrenchment site was found to be approximately five meters. Five monitoring boreholes were dug along the perimeter of the sludge trenches and water samples taken from these monitoring boreholes were analyzed for pH, conductivity, sodium ions, chloride ions, phosphate, nitrate, ammonia, and bacteriological analysis. The results obtained from the analysis conducted were compared with the South African Bureau of Standards for drinking water and it was found that the parameters analyzed falls below the specified range. The data obtained from this study indicate that, given the relatively high sludge loading rates, poor soil quality, and the duration of the groundwater quality monitoring, it is unlikely that contamination of groundwater at the entrenchment site will be a major concern. However, caution is advised in extrapolating these results to other locations.

Keywords: boreholes, contamination, entrenchment, groundwater quality, VIP latrines

Procedia PDF Downloads 408