Search results for: travel time estimation

Authors: Ali Yasin, Ali Kamran, Muhammad Safdar

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In order to reduce the hefty cost involved in terms of time and project cost, the development and application of advanced numerical tools to address the burn-back analysis problem in solid rocket motor design and development is the need of time. Several advanced numerical schemes have been developed in recent times, but their usage in the design of propellant grain of solid rocket motors is very rare. In this paper, an advanced numerical technique named the Level-Set method has been utilized for the burn-back analysis of star grain to study the effect of geometrical parameters on ballistic performance indicators such as solid loading, neutrality, and sliver percentage. In the level set technique, simple finite difference methods may fail quickly and require more sophisticated non-oscillatory schemes for feasible long-time simulation. For internal ballistic calculations, a simplified equilibrium pressure method is utilized. Preliminary results of the operative conditions, for all the combustion time, of star grain burn-back using level set techniques are compared with published results using CAD technique to test the developed numerical model.

Keywords: solid rocket motor, internal ballistic, level-set technique, star grain

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Authors: Longfei Wang, Selçuk Köse

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Hardware Trojan becomes great concern as integrated circuit (IC) technology advances and not all manufacturing steps of an IC are accomplished within one company. Real-time hardware Trojan detection is proven to be a feasible way to detect randomly activated Trojans that cannot be detected at testing stage. On-chip sensors serve as a great candidate to implement real-time hardware Trojan detection, however, the optimization of on-chip sensors has not been thoroughly investigated and the location of Trojan has not been carefully explored. On-chip sensor ellipse distribution method and equivalent mapping technique are proposed based on the characteristics of on-chip power delivery network in this paper to address the optimization and distribution of on-chip sensors for real-time hardware Trojan detection as well as to estimate the location and current consumption of hardware Trojan. Simulation results verify that hardware Trojan activation can be effectively detected and the location of a hardware Trojan can be efficiently estimated with less than 5% error for a realistic power grid using our proposed methods. The proposed techniques therefore lay a solid foundation for isolation and even deactivation of hardware Trojans through accurate location of Trojans.

Keywords: hardware trojan, on-chip sensor, power distribution network, power/ground noise

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Authors: Sunny Arora, Meghal A. Desai

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An impetus towards green consumerism and implementation of sustainable techniques, consumption of natural products and utilization of environment friendly techniques have gained accelerated acceptance. Butein, a natural colorant, has many medicinal properties apart from its use in dyeing industries. Extraction of butein from the flowers of flame of forest was carried out using ultrasonication bath. Solid loading (2-6 g), extraction time (30-50 min), volume of solvent (30-50 mL) and types of solvent (methanol, ethanol and water) have been studied to maximize the yield of butein using the Taguchi method. The highest yield of butein 4.67% (w/w) was obtained using 4 g of plant material, 40 min of extraction time and 30 mL volume of methanol as a solvent. The present method provided a greater reduction in extraction time compared to the conventional method of extraction. Hence, the outcome of the present investigation could further be utilized to develop the method at a higher scale.

Keywords: butein, flowers of Flame of the Forest, Taguchi method, ultrasonic bath

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Authors: Mario Belseran

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The issue of climate change become world attention where one of them increase in air temperature due to greenhouse gas emissions. This climate change is caused by gases in the atmosphere, one of which is CO2. DKI Jakarta as the capital has a dense population with a variety of existing land use. Land use that is dominated by settlements resulting in fewer green space, which functions to absorb atmospheric CO2. Image interpretation SPOT-7 is used to determine the greenness level of vegetation on a green space using the vegetation index NDVI, EVI, GNDVI and OSAVI. Measuring the diameter and height of trees were also performed to obtain the value of biomass that will be used as the CO2 absorption value. The CO2 absorption value that spread in Jakarta are classified into three classes: high, medium, and low. The distribution pattern of CO2 absorption value at green space in Jakarta dominance in the medium class with the distribution pattern is located in South Jakarta, East Jakarta, North Jakarta and West Jakarta. The distribution pattern of green space in Jakarta scattered randomly and more dominate in East Jakarta and South Jakarta

Keywords: carbon dioxide, DKI Jakarta, green space, SPOT-7, vegetation index

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Authors: Mimoza Canga, Irene Malagnino, Ruzhdie Qafmolla, Vergjini Mulo, Gresa Baboci, Vito Antonio Malagnino

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Background: Dental caries represents the most widespread pathology in childhood. The prevalence of dental caries varies with age, gender, socio economic status, geographical location, nutrition habits, and oral hygiene. Objective: The objective of the present longitudinal study is to show clearly the prevalence of dental caries in the children of age 6 and 7 years old in Vlore, Albania, in a two year time period with controls done every 6 months. Materials and methods: The present study was conducted on 530 children, with a controlled sample for a time period of 24 months from September 2019- September 2021. The children in the study had different economic and social backgrounds. The teeth controls were done by the dentists who work at the hospital of the city. The present study was conducted in accordance with Helsinki declaration. Permissions were obtained in written form, which allowed us to perform the observations. Parents had the right to withdraw their children at any time. Statistical analysis was performed using IBM SPSS Statistics 23.0. The significance level (α) was set at 0.05, whereas P-value and analysis of variance (ANOVA) were used to analyze the data. Results: The data of the present study showed that the age group of 6 years old had 139 or 52.3% of the children with dental caries and 127 or 47.7% of them had no dental caries, while at the age of 7 there were 184 or 69.7% of the children with dental caries problems in the permanent molars and 80 or 30.3% of them had no dental caries. In the present study, it was observed that there is a statistically significant association between age group and presence of caries. Children 7 years old had higher presence of dental caries (χ2 = 16.934 (df 1) p-value < 0.001). According to the present research, there is a statistically significant correlation between period of time and the presence of dental caries. Furthermore, in the actual research, it was established that in the time 18-24 months, the prevalence of dental caries was high (χ2=15,318 (df 1) p-value = 0.004). Conclusion: According to the results of the present study performed in Albania in a two year time period with controls done every 6 months, it is proved that the prevalence of dental caries was 17.4 percent higher among children 7 years old in comparison with the children 6 years old.

Keywords: age, children, dental caries, permanent molars

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Authors: Devieta Romadhon Saendardy

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Introduction: The case of aneurysmal subarachnoid hemorrhage (SAH) associated with intraventricular hemorrhage (IVH) in many way. In general, the anterior communicating artery and posterior circulation aneurysms cause Intraventricular Hemorrhage. The development of intraventricular hemorrhage (IVH) in aneurysmal subarachnoid hemorrhage (aSAH) is linked with higher mortality and poor neurological recovery. Case: This case report presents a 51-year-old female patient who developed IVH following SAH. The patient's Glasgow Coma Scale score was 14, the patient has a severe headache, and there were right extremity hemipharese neurological deficits. A non-contrast head CT scan revealed a massive intraventricular haemorrhage. In an hour, the patient got her headache and pharese worse. Discussion: Intraventricular hemorrhage is a serious complication of subarachnoid hemorrhage, necessitating prompt recognition and management. This case highlights the importance of a time management, medical management and surgical intervention to optimize outcomes in patients with intraventricular hemorrhage caused by subarachnoid hemorrhage. Placement of a shunt system improves clinical outcome in intraventricular hemorrhage.

Keywords: Intraventricular hemorrhage, subarachnoid hemorrhage, shunt, time

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Authors: Muluegziabher Semagne Mekonnen

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This study was intended to show the irrigation water requirements and evaluation of canal hydraulics steady state conditions to improve on scheme performance of the Meki-Ziway irrigation project. The methodology used was the CROPWAT 8.0 model to estimate the irrigation water requirements of five major crops irrigated in the study area. The results showed that for the whole existing and potential irrigation development area of 2000 ha and 2599 ha, crop water requirements were 3,339,200 and 4,339,090.4 m³, respectively. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. In this study Hydraulic Analysis of Irrigation Canals Using HEC-RAS Model was conducted in Meki-Ziway Irrigation Scheme. The HEC-RAS model was tested in terms of error estimation and used to determine canal capacity potential.

Keywords: HEC-RAS, irrigation, hydraulic. canal reach, capacity

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Authors: Jamal Wiwoho, Pujiyono, Triyanto

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Terrorism is a real enemy for all countries, including Indonesia. Bomb attacks in some parts of Indonesia are proof that Indonesia has serious problems with terrorism. Perpetrators of terror are arrested and imprisoned, and some of them were executed. However, this method did not succeed in stopping the terrorist attacks. Former terrorists continue to carry out bomb attacks. Therefore, this paper proposes a program towards deradicalization efforts of former terrorists through entrepreneurship. This is necessary because it is impossible to change their radical ideology. The program is also motivated by understanding that terrorists generally come from poor families. This program aims to occupy their time with business activities so there is no time to plan and carry out bomb attacks. This research is an empirical law study. Data were collected by literature study, observation, and in-depth interviews. Data were analyzed with the Miles and Huberman interactive model. The results show that the entrepreneurship program is effective to prevent terrorist attack. Former terrorists are busy with their business. Therefore, they have no time to carry out bomb attacks.

Keywords: deradicalization, terrorism, terrorists, entrepreneurship

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Authors: Nuruddeen Abubakar Adamu

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Background: Global health nursing describes health-related work across borders and focuses more on the differences between the nurses’ role between countries and identified why nursing care in particular country differs from another. It also helps in analyzing the health issues and concerns that transcend national borders class, race, ethnicity and culture. The primary objective of this study is to introduce the concept of global health nursing. And the article also argues for the need for global health nursing. Methods This review assesses available evidence, both published and unpublished, on issues relating to the global health nursing and the nurse's role in global health. The review is qualitative based. Results: Globalization, modern technologies, travel, migration and changes in diseases trend globally has made the nursing role to become more diverse and less traditional. These issues change the nurse’s role in the healthcare industry to become enormous and very challenging. This article considers response to issues of emerging global health nursing concept, challenges, purposes, global health nursing activities in both developed and developing countries and the nurse's role globally in maternal-newborn health; preparedness for advocacy in global health within a framework of social justice, equity; and health system strengthening globally. Conclusion: Global health nursing goes beyond the intervention to care for a patient with a particular health problem but, however health is interconnected to political, economic and social context and therefore this explains the need of a multi-professional and multi-sectoral approach to achieve the goal of global health and the need for global health nursing. Global health equity can be promoted and if the profile of nursing and nurses will be raised and enable nurses to be aware of global health issues so as to enable them to work to their full maximum potential, to attain greater health outcome and wellness.

Keywords: global health nursing, double burden of diseases, globalization, health equity

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Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

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We have conducted the optimal synthesis of root-mean-squared objective filter to estimate the state vector in the case if within the observation channel with memory the anomalous noises with unknown mathematical expectation are complement in the function of the regular noises. The synthesis has been carried out for linear stochastic systems of continuous-time.

Keywords: mathematical expectation, filtration, anomalous noise, memory

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Authors: Hafida Bouarfa, Mohamed Abed

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The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.

Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability

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Authors: Ranjini Ramanath, Nanjunda P. Swamy

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Construction has existed in our lives since time immemorial. However, unlike any other industry, construction projects have their own unique challenges – project type, purpose and end use of the project, geographical conditions, logistic arrangements, largely unorganized manpower and requirement of diverse skill sets, etc. These unique characteristics bring in their own level of risk and uncertainties to the project, which cause the project to deviate from its planned objectives of time, cost, quality, etc. over the many years, there have been significant developments in the way construction projects are conceptualized, planned, and managed. With the rapid increase in the population, increased rate of urbanization, there is a growing demand for infrastructure development, and it is required that the projects are delivered timely, and efficiently. In an age where ‘Time is Money,' implementation of new techniques of project management is required in leading to successful projects. This paper proposes a different approach to project management, which if applied in construction projects, can help in the accomplishment of the project objectives in a faster manner.

Keywords: critical chain project management methodology, critical chain, project management, construction management

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Authors: Binyamien Ibrahim Rasoul

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Controlled burning of rice husk can produce amorphous rice husk ash (RHA) with high silica content which can significantly enhance the properties of concrete. This study has been undertaken to investigate the relationship between the incineration temperatures and time to produce RHA with ultimate reactivity. The rice husk samples were incinerated in an electrical muffle furnace at 350°C, 400°C, 425°C 450°C, 475°C, and 500°C for 60 and 90 minutes, respectively. The silica structure in the Rice Husk Ash (RHA) was determined using X-Ray diffraction analysis, while chemical properties obtained using X-Ray Fluorescence. The results show that RHA appeared to be the totally amorphous when the husk incineration up to 425°C for 60 and even at 90 minutes. However, with increased temperature to 450°C, 475°C and 500°C, traces of crystalline silica (quartz) were detected. However, cannot be taken into account as it does not affect on the ash structure. In conclusion, the result gives an idea of the temperature and the time required to produce ash from rice husk with totally amorphous form.

Keywords: rice husk ash, silica, compressive strength, tensile strength, X-Ray diffraction, X-R florescence, pozzolanic activity

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Authors: Konstanca Nikolajevic, Nicolas Belanger, David Duvivier, Rabie Ben Atitallah, Abdelhakim Artiba

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Finding the optimal 3D path of an aerial vehicle under flight mechanics constraints is a major challenge, especially when the algorithm has to produce real-time results in flight. Kinematics models and Pythagorian Hodograph curves have been widely used in mobile robotics to solve this problematic. The level of difficulty is mainly driven by the number of constraints to be saturated at the same time while minimizing the total length of the path. In this paper, we suggest a pragmatic algorithm capable of saturating at the same time most of dimensioning helicopter 3D trajectories’ constraints like: curvature, curvature derivative, torsion, torsion derivative, climb angle, climb angle derivative, positions. The trajectories generation algorithm is able to generate versatile complex 3D motion primitives feasible by a helicopter with parameterization of the curvature and the climb angle. An upper ”motion primitives’ concatenation” algorithm is presented based. In this article we introduce a new way of designing three-dimensional trajectories based on what we call the ”Dubins gliding symmetry conjecture”. This extremely performing algorithm will be soon integrated to a real-time decisional system dealing with inflight safety issues.

Keywords: robotics, aerial robots, motion primitives, helicopter

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Authors: Hsu-Yung Cheng, Kuo-Chang Hsu, Chi-Chang Chan, Mei-Hui Tseng, Chih-Chang Yu, Ya-Sheng Liu

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Photovoltaics modules are usually not installed horizontally to avoid water or dust accumulation. However, the measured irradiance data on tilted surfaces are rarely available since installing pyranometers with various tilt angles induces high costs. Therefore, estimating solar irradiance on tilted surfaces is an important research topic. In this work, artificial neural networks (ANN) are utilized to construct the transfer model to estimate solar irradiance on tilted surfaces. Instead of predicting tilted irradiance directly, the proposed method estimates the differences between the horizontal irradiance and the irradiance on a tilted surface. The outputs of the ANNs in the proposed design are differential values. The experimental results have shown that the proposed ANNs with differential outputs can substantially improve the estimation accuracy compared to ANNs that estimate the titled irradiance directly.

Keywords: photovoltaics, artificial neural networks, tilted irradiance, solar energy

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Authors: Mark R. Leipnik, Dahlia Durga, Linda Johnson-Bhola

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Kaieteur is the most iconic National Park in the rainforest-clad nation of Guyana in South America. However, the magnificent 226-meter-high waterfall at its center is virtually inaccessible by surface transportation, and the occasional charter flights to the small airstrip in the park are too expensive for many tourists and residents. Thus, the largest waterfall in all of Amazonia, where the Potaro River plunges over a single free drop twice as high as Victoria Falls, remains preserved in splendid isolation inside a 57,000-hectare National Park established by the British in 1929, in the deepest recesses of a remote jungle canyon. Kaieteur Falls are largely unseen firsthand, but images of the falls are depicted on the Guyanese twenty dollar note, in every Guyanese tourist promotion, and on many items in the national capital of Georgetown. Georgetown is only 223-241 kilometers away from the falls. The lack of a single mileage figure demonstrates there is no single overland route. Any journey, except by air, involves changes of vehicles, a ferry ride, and a boat ride up a jungle river. It also entails hiking for many hours to view the falls. Surface access from Georgetown (or any city) is thus a 3-5 day-long adventure; even in the dry season, during the two wet seasons, travel is a particularly sticky proposition. This journey was made overland by the paper's co-author Dahlia Durga. This paper focuses on potential ways to improve overland tourist access to Kaieteur National Park from Georgetown. This is primarily a GIS-based analysis, using multiple criteria to determine the least cost means of creating all-weather road access to the area near the base of the falls while minimizing distance and elevation changes. Critically, it also involves minimizing the number of new bridges required to be built while utilizing the one existing ferry crossings of a major river. Cost estimates are based on data from road and bridge construction engineers operating currently in the interior of Guyana. The paper contains original maps generated with ArcGIS of the potential routes for such an overland connection, including the one deemed optimal. Other factors, such as the impact on endangered species habitats and Indigenous populations, are considered. This proposed infrastructure development is taking place at a time when Guyana is undergoing the largest boom in its history due to revenues from offshore oil and gas development. Thus, better access to the most important tourist attraction in the country is likely to happen eventually in some manner. But the questions of the most environmentally sustainable and least costly alternatives for such access remain. This paper addresses those questions and others related to access to this magnificent natural treasure and the tradeoffs such access will have on the preservation of the currently pristine natural environment of Kaieteur Falls.

Keywords: nature tourism, GIS, Amazonia, national parks

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Authors: Ananta Kumar Das, Sujit Kumar Chakrabarti

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Architectural tactics such as heartbeat, ping-echo, encapsulate, encrypt data are techniques that are used to achieve quality attributes of a system. Detecting architectural tactics has several benefits: it can aid system comprehension (e.g., legacy systems) and in the estimation of quality attributes such as safety, security, maintainability, etc. Architectural tactics are typically spread over the source code and are implicit. For large codebases, manual detection is often not feasible. Therefore, there is a need for automated methods of detection of architectural tactics. This paper presents a formalization of the heartbeat architectural tactic and a program analytic approach to detect this tactic in source code. The experiment of the proposed method is done on a set of Java applications. The outcome of the experiment strongly suggests that the method compares well with a manual approach in terms of its sensitivity and specificity, and far supersedes a manual exercise in terms of its scalability.

Keywords: software architecture, architectural tactics, detecting architectural tactics, program analysis, AST, alias analysis

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Authors: Soner Cubuk, Mirgul Kosif, M. Vezir Kahraman, Ece Kok Yetimoglu

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Boron is an essential trace element for the completion of the life circle for organisms. Suitable methods for the determination of boron have been proposed, including acid - base titrimetric, inductively coupled plasma emission spectroscopy flame atomic absorption and spectrophotometric. However, the above methods have some disadvantages such as long analysis times, requirement of corrosive media such as concentrated sulphuric acid and multi-step sample preparation requirements and time-consuming procedures. In this study, a selective and reusable fluorescent sensor for boron based on glycosyloxyethyl methacrylate was prepared by photopolymerization. The response characteristics such as response time, pH, linear range, limit of detection were systematically investigated. The excitation/emission maxima of the membrane were at 378/423 nm, respectively. The approximate response time was measured as 50 sec. In addition, sensor had a very low limit of detection which was 0.3 ppb. The sensor was successfully used for the determination of boron in water samples with satisfactory results.

Keywords: boron, fluorescence, photopolymerization, polymeric sensor

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Authors: Mahdi Shamsi, Tohid Yousefi Rezaii, Siavash Eftekharifar

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Compressed sensing (CS) is a new powerful mathematical theory concentrating on sparse signals which is widely used in signal processing. The main idea is to sense sparse signals by far fewer measurements than the Nyquist sampling rate, but the reconstruction process becomes nonlinear and more complicated. Common dilemma in sparse signal recovery in CS is the lack of knowledge about sparsity order of the signal, which can be viewed as model order selection procedure. In this paper, we address the problem of sparsity order estimation in sparse signal recovery. This is of main interest in situations where the signal sparsity is unknown or the signal to be recovered is approximately sparse. It is shown that the proposed method also leads to some kind of signal denoising, where the observations are contaminated with noise. Finally, the performance of the proposed approach is evaluated in different scenarios and compared to an existing method, which shows the effectiveness of the proposed method in terms of order selection as well as denoising.

Keywords: compressed sensing, data denoising, model order selection, sparse representation

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Authors: Youngji Lee, Yonghyeon Jeon, Sunyoung Bu, Philsu Kim

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The aim of this paper is to construct an algorithm of time step control for the error correction method most recently developed by one of the authors for solving stiff initial value problems. It is achieved with the generalized Chebyshev polynomial and the corresponding error correction method. The main idea of the proposed scheme is in the usage of the duplicated node points in the generalized Chebyshev polynomials of two different degrees by adding necessary sample points instead of re-sampling all points. At each integration step, the proposed method is comprised of two equations for the solution and the error, respectively. The constructed algorithm controls both the error and the time step size simultaneously and possesses a good performance in the computational cost compared to the original method. Two stiff problems are numerically solved to assess the effectiveness of the proposed scheme.

Keywords: stiff initial value problem, error correction method, generalized Chebyshev polynomial, node points

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Authors: Simona Pileviciene

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On 24th January 2014, Lithuania notified two primary cases of African swine fever (ASF) in wild boars. The animals were tested positive for ASF virus (ASFV) genome by real-time PCR at the National Reference Laboratory for ASF in Lithuania (NRL), results were confirmed by the European Union Reference Laboratory for African swine fever (CISA-INIA). Intensive wild and domestic animal monitoring program was started. During the period of 2014-2017 ASF was confirmed in two large commercial pig holding with the highest biosecurity. Pigs were killed and destroyed. Since 2014 ASF outbreak territory from east and south has expanded to the middle of Lithuania. Diagnosis by PCR is one of the highly recommended diagnostic methods by World Organization for Animal Health (OIE) for diagnosis of ASF. The aim of the present study was to compare singleplex real-time PCR assays to a duplex assay allowing the identification of ASF and internal control in a single PCR tube and to compare primers, that target the p72 gene (ASF 250 bp and ASF 75 bp) effectivity. Multiplex real-time PCR assays prove to be less time consuming and cost-efficient and therefore have a high potential to be applied in the routine analysis. It is important to have effective and fast method that allows virus detection at the beginning of disease for wild boar population and in outbreaks for domestic pigs. For experiments, we used reference samples (INIA, Spain), and positive samples from infected animals in Lithuania. Results show 100% sensitivity and specificity.

Keywords: African swine fewer, real-time PCR, wild boar, domestic pig

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Authors: Samira Gharehkhani, Seyed Farid Seyed Shirazi, Abdolreza Gharehkhani, Hooman Yarmand, Ahmad Badarudin, Rushdan Ibrahim, Salim Newaz Kazi

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Nanocrystalline cellulose (NCC) were prepared by acid hydrolysis and ultrasound treatment of bleached Acacia mangium fibers. The obtained rod-shaped nanocrystals showed a uniform size. The results showed that NCC with high crystallinity can be obtained using 64 wt% sulfuric acid. The effect of synthesis condition was investigated. Different reaction times were examined to produce the NCC and the results revealed that an optimum reaction time has to be used for preparing the NCC. Morphological investigation was performed using the transmission electron microscopy (TEM). Fourier transform infrared (FTIR) spectroscopy and thermogravimetric analysis (TGA) were performed. X-ray diffraction (XRD) analysis revealed that the crystallinity increased with successive treatments. The NCC suspension was homogeneous and stable and no sedimentation was observed for a long time.

Keywords: acid hydrolysis, nanocrystalline cellulose, nano material, reaction time

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Authors: Awf A. Al-Khan, Michael J. Day, Judith Nimmo, Mourad Tayebi, Stewart D. Ryan, Samantha J. Richardson, Janine A. Danks

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Osteosarcoma (OS) is the most common type of malignant primary bone tumour in dogs. In addition to their critical roles in bone formation and remodeling, parathyroid hormone-related protein (PTHrP) and its receptor (PTHR1) are involved in progression and metastasis of many types of tumours in humans. The aims of this study were to determine the localisation and expression levels of PTHrP and PTHR1 in canine OS tissues using immunohistochemistry and to investigate if this expression is correlated with survival time. Formalin-fixed, paraffin-embedded tissue samples from 44 dogs with known survival time that had been diagnosed with primary osteosarcoma were analysed for localisation of PTHrP and PTHR1. Findings showed that both PTHrP and PTHR1 were present in all OS samples. The dogs with high level of PTHR1 protein (16%) had decreased survival time (P<0.05) compared to dogs with less PTHR1 protein. PTHrP levels did not correlate with survival time (P>0.05). The results of this study indicate that the PTHR1 is expressed differently in canine OS tissues and this may be correlated with poor prognosis. This may mean that PTHR1 may be useful as a prognostic indicator in canine OS and could represent a good therapeutic target in OS.

Keywords: dog, expression, osteosarcoma, parathyroid hormone receptor 1 (PTHR1), parathyroid hormone-related protein (PTHrP), survival

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Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

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The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

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Authors: Raymond Limen Njinga

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The comparator factors (Fc) for miniature research reactors are of great importance in the field of nuclear physics as it provide accurate bases for the evaluation of elements in all form of samples via ko-NAA techniques. The Fc was initially simulated theoretically thereafter, series of experiments were performed to validate the results. In this situation, the experimental values were obtained using the alloy of Au(0.1%) - Al monitor foil and a neutron flux setting of 5.00E+11 cm-2.s-1. As was observed in the inner irradiation position, the average experimental value of 7.120E+05 was reported against the theoretical value of 7.330E+05. In comparison, a percentage deviation of 2.86 (from theoretical value) was observed. In the large case of the outer irradiation position, the experimental value of 1.170E+06 was recorded against the theoretical value of 1.210E+06 with a percentage deviation of 3.310 (from the theoretical value). The estimation of equivalent dose rate at 5m from neutron flux of 5.00E+11 cm-2.s-1 within the neutron energies of 1KeV, 10KeV, 100KeV, 500KeV, 1MeV, 5MeV and 10MeV were calculated to be 0.01 Sv/h, 0.01 Sv/h, 0.03 Sv/h, 0.15 Sv/h, 0.21Sv/h and 0.25 Sv/h respectively with a total dose within a period of an hour was obtained to be 0.66 Sv.

Keywords: neutron flux, comparator factor, NAA techniques, neutron energy, equivalent dose

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Danilo López, Edwin Rivas, Leyla López

Abstract:

This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.

Keywords: cognitive radio, base station, best effort, MLPNN, prediction, real time

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Authors: Juliana da Silva Cardoso, Cláudia Correia, Rita Gomes, Carolina Fraga, Inês Cascais, Sara Monteiro, Beatriz Teixeira, Sandra Ribeiro, Carolina Andrade, Cláudia Oliveira, Diana Gonzaga, Catarina Prior, Inês Vaz Matos

Abstract:

The average daily screen time (ST) has been increasing in children, even at young ages. This seems to be associated with a higher incidence of neurodevelopmental disorders, and as the time of exposure increases, the greater is the functional impact. This study aims to compare the daily ST of toddlers and preschoolers previously and during the COVID-19 pandemic. A questionnaire was applied by telephone to parents/caregivers of children between 1 and 5 years old, followed up at 4 primary care units belonging to the Group of Primary Health Care Centers of Western Porto, Portugal. 520 children were included: 52.9% male, mean age 39.4 ± 13.9 months. The mean age of first exposure to screens was 13.9 ± 8.0 months, and most of the children were exposed to more than one screen daily. Considering the WHO recommendations, before the COVID-19 pandemic, 385 (74.0%) and 408 (78.5%) children had excessive ST during the week and the weekend, respectively; during the lockdown, these values increased to 495 (95.2%) and 482 (92.7%). Maternal education and both the child's median age and the median age of first exposure to screens had a statistically significant association with excessive ST, with OR 0.2 (p = 0.03, CI 95% 0.07-0.86), OR 1.1 (p = 0.01, 95% CI 1.05-1.14) and OR 0.9 (p = 0.05, 95% CI 0. 87-0.98), respectively. Most children in this sample had a higher than recommended ST, which increased with the onset of the COVID-19 pandemic. These results are worrisome and point to the need for urgent intervention.

Keywords: COVID-19 pandemic, preschoolers, screen time, toddlers

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Authors: Qian Liu, Steve Furber

Abstract:

To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

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Authors: Janne Engblom, Elias Oikarinen

Abstract:

A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

Procedia PDF Downloads 1508