Programming Research Articles

Predicting Human Behavior by Voice and Face Modulation

The secret to clearly expressing one's views and ideas is communication. Speech is the most prevalent and efficient means for humans to communicate out of all the many types of communication. The Internet of Things (IoT) age is evolving quickly, making increasingly sophisticated technology accessible for daily use. Basic wearable gadgets to sophisticated selfdriving cars automated systems used in a variety of industries are examples of these applications. Intelligent apps mostly employ voice- based input, are interactive, and require little user effort to operate. Because of this, these computer programs must be able to fully understand human speech. The speaker's age, race, gender, language, and mood may all be inferred from a speech percept. An emotion detection system is integrated with a number of current voice recognition systems utilised in Internet of Things applications to assess the speaker's emotional state. One of these techniques for identifying human emotions (such as fear, neutral, anger, pleasure, disgust, sorrow, and surprise) is based on the technique for analysing facial expressions employing the popular deep learning

Factor associated with diarrhea incidence in coastal area Bungkutoko, Kendari, Indonesia

Diarrhea is a health problem that has not been resolved until now, even this disease is the main cause of death in toddlers both globally and nationally. Diarrhea cases in the Nambo Health Center work area, Kendari City have continued to increase over the past 3 years. Bungkutoko is one of the sub-districts located in the coastal area of ​​Nambo District, Kendari City. Coastal areas include areas with inadequate sanitation access, with problems including the availability of clean water, toilets and other basic sanitation facilities that can be factors causing diarrhea. This study aims to determine the factors related to the incidence of diarrhea in the coastal area of ​​Bungkutoko. An observational analytic with cross sectional design was conducted in this study. This study was carried out in June 2024 in Bungkutoko Village, Kendari City, Southeast Sulawesi Province. The sample consisted of 70 respondents obtained using non-probability sampling, accidental sampling techniques. Data were collected using questionnaires and observation sheets, then processed and analyzed using a computer program. Data were analyzed bivariately using chi square test and fisher exact (if not eligible for chi square test) with 95% confidence level (α = 0.05). The results showed there was a relationship between water treatment before drinking and the incidence of diarrhea (p-value = 0.03), and there was no relationship between hand washing behavior (p-value = 0.09) and the condition of waste disposal sites (p-value = 0.25) with the incidence of diarrhea in the coastal area of ​​Bungkutoko, Kendari City. Therefore, it is expected that the community can process drinking water before consuming it to avoid diarrhea.

Utilizing Raspberry Pi and Internet of Things (IoT) Frameworks for Comprehensive Monitoring of Urban Pollutants and Climate Variables

Global warming is the effect of a rise in Earth's climate temperature due to air pollution. Urban areas have higher levels of air pollution than rural areas due to increased traffic and rapid development. In addition to brief health problems like headaches, eye infections, and throat in-factions, pollution also has lengthy health repercussions like lung cancer and heart disease. As a result, it's important to keep an eye on the many climatic and pollution indicators, including light intensity, temperature, humidity, air pressure, oxygen and carbon dioxide level and camera. Using suitable equipment and Internet of Things (IoT) technologies, a pollution and climate monitoring system is constructed in the proposed paper that can measure the parameters above at regular intervals. The system then uploads the data to a webpage in the Thing Speak. The IoT analytics platform service Thing Speak enables the collection, visualization, and analysis of real-time data streams. The sensors are used to feed data to Thing Speak, which instantly visualizes the data in a graph. The main tool for gathering data from the sensors and sending parameters to the website is the Raspberry Pi3 computer. The software code is developed using Python. By logging on to the website from any location in the world, one can view the submitted pollution and climate parameters of a specific location.

Soil fertility management on sesame (Sesamum indicum L.) production in Northern Ethiopia: A review.

Sesame (Sesamum indicum L.) is an important cash crop and plays a vital role in many people's livelihoods in Ethiopia. However, its production is low due to many constraints, and low soil fertility is among the major. The previous fertilizer recommendation was a blanket recommendation regardless of the soil fertility status. Hence, the objective of this review is to synthesize the different recommendations and forward to the sesame growing areas. R statistical software and Python programming language used to analyze the chemical and physical soil properties, association among the chemical and physical soil properties and association with soil depth. The organic carbon, total N (Nitrogen), available P (Phosphorus), S (Sulfur) and Zn (Zinc) are below optimum value while K is sufficient in the soil and moderately alkaline soil. The soil particle size is dominantly clay (58.5%). The clay particle size and pH increased while the sand and silt particle sizes, organic carbon, total N, available P and S decreased as the soil depth increased. 204,558.8 ton of sesame stack residue are burned every year, and from this, 7360.03 ton of NPK is lost every year in Western Tigray. The recommended N, P and S for sesame are: (i) 64 and 41kgha -1N for low N content areas and for medium N content areas respectively; 46 and 23kgha -1 P2O5 for low and medium P content areas; (iii) 60 and 30kgha -1S for low medium S content areas may be recommended to boost sesame production.

The reality of pressure ulcers: an exploratory sequential mixed design study in coaches and Paralympic athletes

ABSTRACT Objectives This study aims to explore and understand the knowledge and attitudes of Paralympic athletes and their coaches toward pressure ulcers. By focusing on this underserved population, the study seeks to improve awareness, recognition, and management practices to minimize the health and performance impacts of pressure ulcers in Paralympic sports. Methods Paralympic athletes and their coaches were contacted. Volunteers were included in the exploratory sequential mixed design study. In the quantitative phase, a digital survey was used to evaluate Paralympic athletes’ and coaches’ awareness of pressure ulcers. To gain a deeper understanding of the factors deemed significant in the quantitative analyses, the researcher conducted one-on-one semi-structured interviews with athletes and coaches. The data was analyzed using the SPSS package program and MAXQDA program. Results Ten coaches and 82 Paralympic athletes participated in the study. The sports disciplines were wheelchair basketball (40%), Paralympic table tennis (40%), Paralympic court tennis (10%), and athletics (10%). Coaches’ knowledge about pressure ulcers was low, and athletes’ knowledge was even lower. It was concluded that coaches should improve their attitudes toward pressure ulcers, particularly in the areas of competence and responsibility sharing. During the interviews with the participants, several themes emerged. Conclusion To address pressure ulcers’ significance, it is essential to increase the knowledge level of both athletes and the entire team and adopt a positive attitude. It has been concluded that different areas of expertise in the fields of health and sports should work with a more organized structure and team awareness.

Risk analysis and protection in case of intrusion of nuclear facilities

Abstract Physical protection systems (PPSs) are designed to counter and neutralize any theft or sabotage attempts carried out against a given site. PPS designs are crucial, requiring rigorous analysis and evaluation to ensure their reliability, sustainability and optimal security. This paper assumes a Hypothetical Nuclear Research Center (HNRC) for PPS analysis and evaluation. This work will determine the PPS’s most vulnerable path elements, by demonstrating expected intrusion attack scenarios by taking advantage of the HNRC’s design weaknesses. Also, this work determines the threats resulting from adversary intrusion through the weakness path elements located at the nuclear site. Additionally, this paper develops an analytical methodology for this evaluation and risk assessment, by using the Systematic Analysis of Vulnerability to Intrusion (SAVI) computer program. Through constructing adversary sequence diagrams (ASDs), SAVI can easily identify the HNRC’s most vulnerable paths, pinpointing the areas which require the most attention. Alongside SAVI is the quantitative risk analysis method - the Dai et al. Model – which can calculate the effectiveness and risk of the PPS itself by measuring its degree of uncertainty using effectiveness entropy. To comply with effectiveness and risk standards, this work also introduces security system upgrade processes and determines the optimal security solution for the HNRC.

Unveiling pterion variability: a meta-analytic approach to enhance neurosurgical precision

PurposeThis meta-analytical systematic review aims at investigating the variability of the pterion, focusing on its morphological types and precise distances from various bony landmarks. Additionally, the neurosurgical significance of this critical cranial landmark is examined in depth.MethodsThe systematic review was conducted following PRISMA 2020 and Evidence-based Anatomy Workgroup guidelines for anatomical studies. The risk of bias was assessed using the Anatomical Quality Assurance Tool (AQUA). The meta-analysis was performed using R programming software and RStudio, employing the “meta” and “metafor” packages.ResultsA total of 79 studies were included, encompassing 18,694 skull sides. The sphenoparietal type was identified as the most prevalent pterion variant, with a pooled prevalence of 78.54%. The epipteric type followed at 8.41%, while the frontotemporal (5.74%) and stellate (4.26%) types were the rarest. Significant differences in the prevalence of the epipteric, frontotemporal, and stellate types were observed across different nationalities. However, sex, side, and study type did not significantly influence pterion morphological variation. The study also extracted and calculated the distances between the pterion and key anatomical landmarks, including the midpoint of the zygomatic arch, the frontozygomatic suture, the mastoid process, and the external acoustic meatus.ConclusionThis study offers critical anatomical insights by accurately mapping the pterion’s location relative to essential cranial landmarks. These findings are vital for neurosurgical planning, particularly for procedures involving the anterior and middle cranial fossae. The detailed anatomical data provided can enhance the precision and safety of neurosurgical interventions, ultimately improving patient outcomes.

Willingness to donate eyes and associated factors among adults in Addis Ababa City, Ethiopia: a mixed-methods approach

ObjectiveThis study intended to assess willingness to donate eyes and associated factors among adults in Addis Ababa City, Ethiopia.Methods and analysisThis study used a triangulated phenomenological mixed-methods design, involving 1293...

SPACIER: on-demand polymer design with fully automated all-atom classical molecular dynamics integrated into machine learning pipelines

Machine learning has rapidly advanced the design and discovery of new materials with targeted applications in various systems. First-principles calculations and other computer experiments have been integrated into material design pipelines to address the lack of experimental data and the limitations of interpolative machine learning predictors. However, the enormous computational costs and technical challenges of automating computer experiments for polymeric materials have limited the availability of open-source automated polymer design systems that integrate molecular simulations and machine learning. We developed SPACIER, an open-source software program that incorporates RadonPy, a Python library for fully automated polymer physical property calculations based on all-atom classical molecular dynamics, into a Bayesian optimization-based polymer design system to overcome these challenges. As a proof-of-concept study, we synthesized optical polymers that surpass the Pareto boundary formed by the tradeoff between the refractive index and the Abbe number.

Review Paper — Hydroeconomic Analysis: History, Status, and Possibilities

This paper reviews recent advances in the motivation, conceptualization, development, application, and assessment of hydroeconomic models (HEMs), for which these models are implemented by conducting a hydroeconomic analysis (HEA). It addresses various dimensions of HEA, including problems motivating the need for an HEM, roles of HEA, policy debates informed by HEMs, important uses of HEA, recent achievements in the scientific literature performed by use of HEMs, future improvements desired in HEA, as well as one simple prototype HEM. Supplementary material is included describing some contributions made to HEA, with special attention given to four individual contributors to water resource economics generally, criteria for credibility, and a description of some of the more popular mathematical programming packages used to build an HEM.

RESEARCH NOTES—GMRepair: Graph Mining Template-Based Automated Software Repair

With the increasing scale and complexity of software recently, automated software bug repair has grown in importance. However, the current automated software bug repair process suffers from issues such as coarse-grained repair granularity and poor patch quality. To address these problems, we propose a graph mining template-based automatic software repair (GMRepair) to improve the performance of automated software bug repair. First, this approach adopts the Ochiai fault localization technique to locate and generate a list of suspicious defect statements. We utilize the GumTree tool to parse the bug and repair program files, generating edit scripts. These edit scripts are then transformed into a graphical representation. Second, we utilize a frequent graph miner to obtain graph mining templates by matching the context of the suspicious statements with the context of the graph mining templates, generating an initial population for them. The buggy program is evolved using genetic programming through mutation and crossover operations, generating new individuals. Finally, we sequentially pass the candidate patches (CPs) through corresponding test cases and prioritize the test cases using priority sorting techniques. Patches that fail to pass the test cases are filtered out, and the patches that pass the test cases are output. We conducted the experiments using two datasets, QuixBugs and Defects4J. In Defects4J, the GMRepair successfully repaired 41 defects, while in QuixBugs, it successfully repaired 15 defects. Compared to the existing methods, GMRepair offers a higher success rate and efficiency in defect repair.

Stigmatizing Views of Ill Women in Kuwaiti Memoir of Arthritis

This study explored the portrayal of illness and disability in Kuwaiti author Kulthoum Dashti’s memoir Almost Faded: Rheumatoid Arthritis Journey specifically focusing on how health-based thematic categorizations intersect with perceptions of the external world. Using the Linguistic Inquiry and Word Count (LIWC-2015) software program, a corpus specific to the novel was analyzed, retrieving thematic categories and contrasting them with the psychologically validated lexica. The analysis revealed the author’s strong authenticity in narrating her journey with arthritis, characterized by heavy use of function words contributing to reflective tone. Additionally, the marginal confidence and low emotional tone in the narrative reflected the author’s intention to share experiences without asserting authority, while social, temporal, and spatial references centralized the lack of familial support and accurate depictions of locations, shaping the narrative’s structure. This case study contributes to understanding how illness and disability are portrayed in Kuwaiti literature, shedding light on the psychological dimensions embedded within the disability narrative.

Simulation-Based Studies on FAGeI3-Based Lead (Pb2+)-Free Perovskite Solar Cells

In the recent reports, it is clear that lead-free perovskite materials with low band gaps are desirable candidates for photovoltaic cells. In this regard, it was observed that germanium (Ge) is a less toxic lead-free metal that is significant for the preparation of Ge-based perovskite materials. Ge-based perovskite materials, for example, methyl ammonium germanium iodide (MAGeI3), cesium germanium iodide (CsGeI3), and/or formamidinium germanium iodide (FAGeI3) may be the suitable absorber materials and alternatives towards the fabrication of lead-free photovoltaic cells. In the past few years, few attempts were made to develop FAGeI3-based perovskite solar cells, but their photovoltaic performance is still under limitations. This is indicating that some significant and effective strategies should be designed and developed for the construction of Ge-based perovskite solar cells. It is believed that optimization of layer thickness, device structure, and selection of a suitable electron transport layer (ETL) may improve the photovoltaic performance of FAGeI3-based perovskite solar cells. Solar cell capacitance simulation, i.e., SCAPS is one of the promising software programs that can provide significant theoretical findings for the development of FAGeI3-based perovskite solar cells. The simulation studies via SCAPS may benefit researchers to save their energy and high cost for the optimization process in the laboratories. In this research article, SCAPS was adopted as a simulation tool for the theoretical investigations of FAGeI3-based perovskite solar cells. The simulation studies exhibited the excellent efficiency of 15.62% via SCAPS. This study proposed the optimized device structure of FTO/TiO2/FAGeI3/PTAA/Au with enhanced photovoltaic performance.

Material Characterisation Experiments and Data Preparation for a Finite Element Analysis of the Deep Drawing Process Using AA 1050-O

The use of computer simulation to imitate physical processes has proven to be a time-efficient and cost-effective way of performing scenario testing for process optimisation in different applications. The finite element analysis (FEA) is the dominant numerical simulation method for analysing sheet metal forming processes. It uses mathematical tools and computer-aided engineering software programmes to predict forming processes. To improve the quality of output from the simulation, accurate material characterisation data that correctly model the behaviour of the material when it undergoes deformation must be provided. This paper outlines the stages of conducting material characterisation experiments, such as tensile, hardness, and formability tests, using the aluminium alloy AA1050-O. Sample preparation, the machine setup, and testing procedures for the material characterisation tests are given. Subsequent data preparation methods for input into an FEA software programme are also outlined. Implications of the testing results to a deep drawing process are examined while considering the formation of a rectangular monolithic component measuring 2300 mm by 1400 mm with a drawing depth of approximately 150 mm. The results from the characterisation tests indicate that the forming process for the product can be achieved using cold forming at room temperatures as a 25% strain was recorded before necking against an anticipated uniaxial strain of 5.93%. The aluminium alloy AA1050-O demonstrated a negligible strain rate sensitivity in the forming region, thus eliminating tool velocity from the key process parameters that should be considered during FEA simulations. A 50% increase in hardness was recorded after strain hardening.

Microbiota Composition in Raw Drinking Milk from Vending Machines: A Case Study in Croatia

According to the Regulation on the Quality of Fresh Raw Milk, up to 100,000 microorganisms/mL are allowed in milk obtained by the hygienic milking of healthy cows, which represents the natural microbiota of milk and has no negative impact on the overall quality of milk. However, with unprofessional handling during and after milking, milk is easily contaminated and becomes a potential medium for the growth and reproduction of microorganisms, some of which can be harmful to human health. Since the number of aerobic mesophilic bacteria in milk is one of the indicators of the hygienic quality of milk, their number and identification are fundamental in the control of raw milk from milk vending machines. From five different milk vending machines, 35 samples were collected, from which the total number of aerobic mesophilic bacteria was determined using the flow cytometry method and the classic method of counting colonies on a nutrient medium. Randomly selected colonies based on morphological differences (n = 700) were identified by comparing MALDI-TOF mass spectra with reference spectra stored in the microorganism library and processing using the MALDI Biotyper computer program. Thirty-eight genera and eighty-one bacterial species and five genera and seven fungal species were successfully identified. The species that predominate are Lactococcus lactis, Hafnia alvei, Escherichia coli, Leuconostoc mesenteroides, and Kluyveromyces lactis. By integrating advanced methods like flow cytometry and MALDI-TOF MS for precise microbial identification, this study highlights the need for enhanced monitoring and adherence to hygienic standards in raw milk vending machines. This approach not only safeguards public health but also supports consumer confidence in milk quality from vending machines.

Review Analysis on Virtual Doctor Bot

This review presents an overview of our research on “Virtual Doctor Bot.” The paper aims to explore Virtual Doctor Bots, which are computer programs designed to interact with patients, providing medical advice and support. These bots are increasingly being used in healthcare, offering various benefits to both patients and healthcare providers. The paper presents a comprehensive literature survey, analyzing the integration of AI, IoT, and telemedicine in healthcare solutions. It highlights the potential of these technologies to improve accessibility, reduce patient waiting times, and alleviate the burden on healthcare facilities. Key benefits include 24/7 access to medical information, personalized health advice, and the reduction of hospital crowding. The proposed system demonstrates the potential to revolutionize healthcare delivery, particularly in resource-constrained settings, by offering a scalable, cost-effective, and efficient solution for patient management and engagement. Key Words: IoT, Telemedicine, Pulse sensor ,Thermal temperature sensor , Screen.

Estimation of microbiota and interleukin-1 beta in tears and conjunctival secretions of patients with ocular defects after using unilateral ocular prosthesis.

Clinical studies evaluating the levels of interleukin-1 beta (IL-1β) in tears and conjunctival secretions of patients with ocular defects after using ocular prostheses are lacking. Therefore, a comparative evaluation of IL-1β levels in the defective eye before and after placement of an ocular prosthesis is needed. The purpose of this clinical study was to compare the microbiota and IL-1β in tears and conjunctival secretions of patients with an ocular defect after using an ocular prosthesis. Patients visiting the prosthodontic department for the rehabilitation of an eye defect that could be restored with an ocular prosthesis were screened with predetermined inclusion and exclusion criteria. Twenty participants were enrolled in the study, and written informed consent was obtained. An ocular prosthesis was provided for each participant to manage anophthalmia. Tear samples for the evaluation of microbiota and IL-1β levels were collected from each participant from the healthy and the defective eye before and after using the ocular prosthesis. The culture method was used to identify microbiotas, and the IL-1β was quantified using an enzyme-linked immunosorbent assay sandwich kit. The obtained data of all parameters were tabulated and compared by using a statistical software program (α=.05). A statistically significant difference was observed on comparing microbiota and the levels of IL-1β, with a significant increase in the levels after the ocular prosthesis was provided (P<.05). Levels of IL-1 β in the test group increased as compared with the control group. The increase might be attributed to the inflammatory changes as a result of change in microbiota.

Network Analysis of Psychological Empowerment, Need for Cognition, and Academic Self-Efficacy among Graduate Students.

The present study employed network analysis to explore the interrelationships between academic self-efficacy, psychological empowerment, and the need for knowledge at the symptom level among graduate students. Three hundred fifty-three graduate students from King Faisal University, Hofuf, Saudi Arabia (63.5% male, 72.2% in the 25-35 age range) completed the Psychological Empowerment Scale, Need for Cognition Scale (NCS), and Academic Self-Efficacy Scale as self-report measures. Different R-Studio programming software packages, such as "graph," "network tools," and "botnet," were used to analyze the current study's data. The most central node on the network analysis was Self.2 (history of success/failure), with the greatest betweenness (2.18), closeness (1.84), and strength (1.86). This node showed that it was essential for connecting other variables, despite having an expected negative effect (-0.37). Then there was also Psy.4 (impact), which showed a high centrality of betweenness 1.13 and closeness 1.29. Indeed, positive edges for Self.2 (previous successes/failures) and MB (Need for Cognition) (edge weight 0.37) clearly showed that good past experiences increased cognitive activity. A Bridge Betweenness of 10 was the most significant bridge node (Self.4 (university behavior) in the bridge analysis), linking network elements. Bootstrapped confidence intervals proved that these connections remained stable, ensuring the network was robust over resamples. Enhancing graduate students' self-efficacy and psychological empowerment, particularly through positive past experiences, could improve their academic performance and cognitive engagement. Future research should explore the implications of these findings for designing interventions to foster academic success.

Evaluating basic chest pass skills in the 21st century using chest pass automatic board 2.0

Introduction: This research develops an automated tool to measure the chest pass ability in basketball. We developed this measurement to reduce human error in assessing the chest pass ability in basketball. Objective: The product refines the previous version of the automatic chest pass board by adding a feature for automatic result calculation and utilizing wireless technology. Methodology: This study utilized the research and development approach. A total of 42 participative students were involved in this research. Results: The results of the first test showed a significance value of Sig. (2-tailed) = 0.047 (p &lt; 0.05). In the second test, the significance value obtained was Sig. (2-tailed) = 0.008 (p &lt; 0.05). Both tests showed significant differences. The results of three prototype reliability tests showed very good reliability (ICC = 0.990; 0.987 and 0.920) with a 95% confidence interval. The Bland-Altman plot analysis shows that there is a good level of agreement for this prototype. There is no measurement bias in chest passes using either the automatic board or the usual methods. This is because both instruments are very reliable. Discussion: The inventions that make it easier and faster to evaluate chest pass test results include the use of vibration sensors, wireless data transmission, a computer program, and a database that directly obtains measurement results. Conclusions: The prototype of the automatic chest pass board 2.0 is a reliable and stable potential substitute for measuring the chest pass ability of each individual in basketball games.

Rotating Hinge Revision Total Knee Arthroplasty With and Without Porous Cone Adjunct Fixation.

As the number of revision total knee arthroplasties (rTKA) continues to rise, there is increasing interest in the use of contemporary rotating hinge prostheses. These devices often incorporate porous cones to fill bone defects and enhance long-term fixation. This study evaluated the clinical and functional outcomes and survivorship in rTKA patients utilizing a rotating hinge prosthesis with flexible titanium (FT) cones, porous tantalum (PT) cones, or no cones. From December 2014 to July 2023, 251 patients who underwent rTKA with a rotating hinge prosthesis were identified. Among them, 184 (73.3%) received cones: 93 tibial, 22 femoral, and 69 with combined cone fixation. Data were collected on demographics, surgical details, functional outcomes, complications, and implant survivorship. Statistical analyses were performed using a software program. The average age of the cohort was 68 years (range, 34 to 98), the mean body mass index was 34.2 (range, 18.6 to 64), mean American Society of Anesthesiologists score was 2.97 (range, 2 to 4), and the mean Charleson Comorbidity Index 4.03 ± 1.88. The mean follow-up period was 1.85 years (range, 0 to 7.9), with 97 (40%) men. Aseptic loosening of the hinge implant was observed in seven patients (2.8%) across the entire cohort. In patients who had cones, none were found to be loose despite loosening of the rTKA components. Postoperatively, wound complications were more common in the PT group (15.4%) compared to the FT (2.6%) and no cone groups (14.9%, P = 0.017). There were no significant differences in reoperation rates across the groups. The use of FT and PT cones with a novel rotating hinge prosthesis appears to be effective in achieving stable fixation and favorable early outcomes in rTKA. While aseptic loosening rates were low across all groups, the no-cone cohort had the highest proportion of cases. Long-term follow-up is necessary to validate these early findings and assess the durability and cost-effectiveness of these implants over time.