Periodicals of Engineering and Natural Sciences (PEN - International University of Sarajevo)
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Automated detection of gait events using inertial sensor signals and a discrete wavelet transform approach
Get PDFDetection of gait cycle events is a crucial step toward an effective evaluation and rehabilitation of pathologies or injuries in human locomotion. Recently, methods based on the Discrete Wavelet Transform (DWT) have been useful for this detection due to their robustness and the wide variety of options for analyzing and decomposing signals in time/frequency domains, as well as their ability to extract relevant features embedded in the signals. In this study, a detection method of main gait cycle events, using the Wavelet Symlets and Daubechies families, was developed. These events are the heel-strike (HS) and the toe–off (TO). Inertial signals were acquired by three different devices: a G–WALK (reference equipment), an Apple Watch (AW), and a noncommercial device based on Inertial Measurement Units (IMUs). The dataset was obtained from six–minute walking tests performed by 22 healthy subjects. First, the dataset was processed, and then the signals were synchronized regarding the reference system. Subsequently, the signals were decomposed into 6 levels using sym4 and db5 Wavelets to obtain multiple perspectives of the signals. Then, using automatic threshold techniques and symmetric windows, it was possible to detect HS and TO events. Finally, the IMUs–based system obtained a 94.398 % of recall, 100 % of precision, and 97.117 % of F_1–score, with absolute values delays in the detection between 10–20 ms. In contrast, the AW system performance was 90.168 %, 100 %, and 94.828 % for recall, precision, and F_1–score, respectively, with absolute values delays in the detection of 10–28 ms
Applying engineering principles to financial inclusion in Ecuador: A VEC model analysis of economic growth trends
Get PDFFinancial inclusion is currently considered an important strategy to strengthen the economic growth of countries, especially developing ones. This study seeks to examine the impact that financial inclusion variables have had on the economic growth of Ecuador using quarterly time series information that corresponds to the period between 2020 and 2023. An error correction model was used, taking the Product Gross Domestic as a dependent variable and having as financial inclusion variables the credit granted by financial institutions with respect to GDP and the relationship credit granted by financial institutions with deposits; Other control variables were also used, such as liquidity in the broad sense (M2) in relation to GDP and the liquidity of banks and cooperatives. The study concluded that financial inclusion has a positive and significant impact on economic growth in Ecuador through the Credit variable; Additionally, in the short term all variables are related to each other, although in the long term only the variables M2/GDP and Credits/deposits influence the behavior of GDP
The impact of Cognitive Behavioral Therapy (CBT) program on anxiety disorder and memory recall
Get PDFThe efficient treatment of anxiety-related disorders and memory recall is significant, regarding the occurrence of these disorders and their relationship with poor psychology operational. Thus, this study aims to measure the modern evidence on the efficacy of CBT on anxiety- disorders and memory recall in elderly in Amman, Jordan. Quasi-experimental intervention was conducted combined with qualitative approach. Purposive sampling method was used to sample 46 elderly resident in Amman. Feedback and observation were used to collect qualitative data. The tests of “The State-Trait Anxiety Inventory” (STAI), “Rey Auditory Verbal Learning Test” (RAVLT), and Narrative Recall Assessment (NRA) were used to collect the data. SPSS 25.0 and NVivo software analyzed the data. The findings show that the Cognitive Behavioral Therapy program has a positive effect on anxiety decreasing, memory function and recalling in elderly people. Three major themes emerged “improved coping, increased confidence, positive engagement”. The positive findings highlight the importance of personalized CBT interventions in improving mental health among elderly people residing within an institutionalized care setting. The study contributions, recommendations, and future directions were explained at the end of the study
Advanced detection and discrimination of power transformer internal faults from other abnormal condition using DWT-based feature extraction and ANN classification
Get PDFPower transformers are one of the most critical elements of the electrical Power System because of the aforementioned function in the voltage regulation and power supply. It is very important in the field of power engineering to be able to differentiate the inrush currents caused due to the energization of the transformer from the internal fault currents created in the transformer. This paper represents an efficient approach to solving this issue by employing DWT feature extraction and ANN classification. This approach is based on the determination of waveforms by distinguishing the D4 and D5 coefficients of instantaneous differential currents using DWT. These coefficients present much useful information related to the waveform type, making it possible to differentiate between the inrush and the internal fault currents. This is a key factor when making classification in that these criteria are related to the energy content involved within these coefficients. This energetic approach forms the basis for the ANN controller to determine particular decisions about the quality of the current. This proposed approach is supported with simulation to represent empirical data in supporting the use of this approach. The results always confirm the efficiency of such an approach to the differentiation between inrush and internal fault currents with a high percentage of accuracy. The effectiveness of this method goes beyond accuracy as it is reliable, responds quickly to abnormal conditions, and can be applied to a variety of power transformer types. Applying this concept in real grid power systems can lead to increased reliability and less downtime thereby strengthening the electrical system as a whole. The reliability and safety of power transformers remain a critical concern in power engineering. The present paper proposes a new method to improve power transformer protection for differentiating internal faults from other abnormal situations. The method described herein utilizes advanced signal processing and machine learning with the help of DWT and ANN to reach higher standards of accuracy and reliability
Study of the impact of special educational programmes on the psycho-emotional well-being of students
Get PDFThe purpose of the study is to investigate the impact of special educational programmes on the psychological and emotional development of higher education students. To achieve this goal, survey methods were used (200 participants). The method of content analysis was used to study the scientific literature on this issue. The results show that the use of modern programmes has led to a number of organisational challenges related to ensuring a stable Internet connection and limited opportunities to acquire practical skills that are important for many specialities. This situation caused particular anxiety among students. The study showed that students generally have a positive perception of the use of modern technologies and methods. However, there are also negative aspects of constant interaction with the digital environment, such as atomisation, problems with soft skills development, the risk of emotional burnout, etc. Overcoming these challenges is possible through the evolution of the organisation of the educational process. The creation of smaller academic groups of students provides opportunities for deeper interaction and the development of relevant communication skills. The conclusions emphasise that the development and implementation of new methods that can quickly adapt to modern educational environments is a promising area for further research. 
The impact of strategic leadership on strategic performance in higher education institutions: The mediating role of change management
Get PDFThis study aims to identify the impact of strategic leadership (SL) in enhancing strategic performance (SP) using the balanced scorecard (BSC) approach in Jordanian higher education institutions. In addition to identifying what change management (CM) can provide in explaining the role of SL in enhancing SP. The study population consisted of all official universities in Jordan, which numbered (11) official universities. The study followed a comprehensive survey method, where questionnaires were distributed to all official universities. The sampling unit consisted of deans of colleges in official Jordanian universities. The sample size was 350 respondents. The recovered questionnaires were (238) questionnaires. The results of analyzing the study data indicated that there was an effect for all dimensions of SL on SP. The study also found that all dimensions of SL affect SP in Jordanian official universities. Finally, the results of the data analysis indicated that the CM variable plays a mediating role in the impact of SL on SP. Based on the results, the study recommends the need for Jordanian official universities to pay attention to strengthening aspects of SL among current and future leaders and raising them to higher levels
Social network data as a tool for engineering consumer behavior analysis
Get PDFSocial networks can be used to carefully study how people act, focusing on how they can be used to understand and change people\u27s decisions. A mixed-method approach is used for the study, which blends qualitative results from theories of customer behavior with quantitative analysis of Phoenix-area Yelp data. Many people visit the same place more often when they have friends who use sites like Yelp. It\u27s 64% more likely for friends to go to the same place than for people who aren\u27t friends. Studies of demographics show that females and younger people have lower levels of social power than older people and men. To deal with endogeneity and split the different groups of customers in the study, dyadic fixed effects models are used. These changes to the way studies are done help us get a better sense of how social impact works and make the results more reliable. What happened to marketing plans shows how important it is to focus on certain groups and share social ideas through high scores. There is also discussion about moral problems that come up with keeping data safe and being open. In general, this study helps us learn more about how to use social networks to study how people behave and shape modern marketing tactics
Enhancing road construction management in Peru through virtual design and construction integration
Get PDFThis study examines the integration of Building Information Modeling (BIM) with Project Production Management (PPM) and Integrated Concurrent Engineering (ICE) under the Virtual Design and Construction (VDC) framework to address chronic inefficiencies in road infrastructure projects in Peru. Focusing on a 93 km road project in Puno, the research demonstrates that the combined VDC approach leads to significant improvements in project management. Key findings include a 25% reduction in project delays and a 15% decrease in overall project costs compared to traditional management methods. The implementation of VDC also resulted in a 90% reduction in design conflicts and a 95% improvement in the resolution of construction observations. Production metrics were established, showing that BIM scope fulfillment reached 100%, and key stakeholders\u27 attendance at ICE sessions exceeded 85%, ensuring effective interdisciplinary coordination. The study highlights the critical role of coordinated BIM, PPM, and ICE processes in mitigating risks and enhancing project delivery in Peru. These results show that adopting the VDC framework can lead to substantial efficiency gains in future road infrastructure projects. Recommendations include the establishment of continuous training programs and the creation of robust digital infrastructures to support the widespread adoption of VDC in the Peruvian construction sector
Comparative approach between traditional banking marketing and participative banking marketing
Get PDFThe efficient treatment of anxiety-related disorders and memory recall is significant, regarding the occurrence of these disorders and their relationship with poor psychology operational. Thus, this study aims to measure the modern evidence on the efficacy of CBT on anxiety- disorders and memory recall in elderly in Amman, Jordan. Quasi-experimental intervention was conducted combined with qualitative approach. Purposive sampling method was used to sample 46 elderly resident in Amman. Feedback and observation were used to collect qualitative data. The tests of “The State-Trait Anxiety Inventory” (STAI), “Rey Auditory Verbal Learning Test” (RAVLT), and Narrative Recall Assessment (NRA) were used to collect the data. SPSS 25.0 and NVivo software analyzed the data. The findings show that the Cognitive Behavioral Therapy program has a positive effect on anxiety decreasing, memory function and recalling in elderly people. Three major themes emerged “improved coping, increased confidence, positive engagement”. The positive findings highlight the importance of personalized CBT interventions in improving mental health among elderly people residing within an institutionalized care setting. The study contributions, recommendations, and future directions were explained at the end of the study
A big data approach to risk management and control: Cybersecurity in accounting
Get PDFThis research reviews into the critical interplay between big data applications and cybersecurity risks within the accounting sector. Aimed at understanding how big data can mitigate these risks, the study develops a novel theoretical model using differential equations. This model, rooted in a thorough empirical approach, undergoes validation through logistic regression analysis of responses from 200 participants. The analysis particularly focuses on how demographic and socio-economic factors influence cybersecurity perceptions. Data Breach Consistency emerges as a key factor, evidenced by a coefficient of 1.204 and an odds ratio of 3.331, indicating a substantial link between the recognition of data breaches and increased cybersecurity concerns. Malware and Ransomware concerns demonstrate a notable impact, with a coefficient of 0.907 and an odds ratio of 2.477, underscoring the gravity of these threats. Results further highlight the mitigating influence of Big Data Mitigation on cybersecurity risks, marked by a coefficient of 0.491. The robustness of the model is affirmed by an Area Under the Curve (AUC) score of 0.843, attesting to its efficacy in predicting cybersecurity concerns. The findings highlight the vital role of big data in formulating effective cybersecurity strategies. This study not only contributes to the academic discourse on the intersection of big data and cybersecurity in accounting but also offers practical insights for enhanced decision-making and policy formulation in the evolving digital business environment