Search results for: delay tolerant networks

Authors: Hui Luo, Zhenhong Li, Zhen Dong

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The analysis of multi-temporal InSAR (MTInSAR) such as persistent scatterer (PS) and small baseline subset (SBAS) techniques usually relies on temporal/spatial phase unwrapping (PU). Unfortunately, it always fails to unwrap the phase for two reasons: 1) spatial phase jump between adjacent pixels larger than π, such as layover and high discontinuous terrain; 2) temporal phase discontinuities such as time varied atmospheric delay. To overcome these limitations, a least-square based PU method is introduced in this paper, which incorporates baseline-combination interferograms and adjacent phase gradient network. Firstly, permanent scatterers (PS) are selected for study. Starting with the linear baseline-combination method, we obtain equivalent 'small baseline inteferograms' to limit the spatial phase difference. Then, phase different has been conducted between connected PSs (connected by a specific networking rule) to suppress the spatial correlated phase errors such as atmospheric artifact. After that, interval phase difference along arcs can be computed by least square method and followed by an outlier detector to remove the arcs with phase ambiguities. Then, the unwrapped phase can be obtained by spatial integration. The proposed method is tested on real data of TerraSAR-X, and the results are also compared with the ones obtained by StaMPS(a software package with 3D PU capabilities). By comparison, it shows that the proposed method can successfully unwrap the interferograms in urban areas even when high discontinuities exist, while StaMPS fails. At last, precise DEM errors can be got according to the unwrapped interferograms.

Keywords: phase unwrapping, time series, InSAR, urban areas

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Authors: Moh Hanif Mubarok, Muhammad Rivai

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The public's response to quality rice is very high. So it is necessary to set minimum standards in checking the quality of rice. Most rice quality measurements still use manual methods, which are prone to errors due to limited human vision and the subjectivity of testers. So, a gas detection system can be a solution that has high effectiveness and subjectivity for solving current problems. The use of gas sensors in testing rice quality must pay attention to several parameters. The parameters measured in this research are the percentage of rice water content, gas concentration, output voltage, and measurement time. Therefore, this research was carried out to identify carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄) gases in rice quality using a series of gas sensors using the Neural Network method.

Keywords: carbon dioxide, dinitrogen oxide, methane, semiconductor gas sensor, neural network

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Noxolo Mafu

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This study presents an overview of strategic planning in South African higher education institutions by tracing its trends and mystique in order to identify its impact. Over the democratic decades, strategic planning has become integral to institutional survival. It has been used as a potent tool by several institutions to catch up and surpass counterparts. While planning has always been part of higher education, strategic planning should be considered different. Strategic planning is primarily about development and maintenance of a strategic fitting between an institution and its dynamic opportunities. This presupposes existence of sets of stages that institutions pursue of which, can be regarded for assessment of the impact of strategic planning in an institution. The network theory serves guides the study in demystifying apparent organisational networks in strategic planning processes.

Keywords: network theory, strategy, planning, strategic planning, assessment, impact

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Okike Benjamin, E. J. D. Garba

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The protection of sensitive information against unauthorized access or fraudulent changes has been of prime concern throughout the centuries. Modern communication techniques, using computers connected through networks, make all data even more vulnerable to these threats. The researchers in this work propose a new encryption technique to be known as Merged Irregular Transposition Cipher. In this proposed encryption technique, a message to be encrypted will first of all be split into multiple parts depending on the length of the message. After the split, different keywords are chosen to encrypt different parts of the message. After encrypting all parts of the message, the positions of the encrypted message could be swapped to other position thereby making it very difficult to decrypt by any unauthorized user.

Keywords: information security, message splitting, pattern, sequence

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Authors: Mohamed A. Hammad, Dzul Azri Mohamed Noor, Syed Azhar Syed Sulaiman, Majed Ahmed Al-Mansoub, Muhammad Qamar

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There is a progressive increase in the prevalence of early onset Type 2 diabetes mellitus. Early detection of Type 2 diabetes enhances the length and/or quality of life which might result from a reduction in the severity, frequency or prevent or delay of its long-term complications. The study aims to determine the onset age for the first diagnosis of Type 2 diabetes mellitus. A retrospective study conducted in the endocrine clinic at Hospital Pulau Pinang in Penang, Malaysia, January- December 2016. Records of 519 patients with Type 2 diabetes mellitus were screened to collect demographic data and determine the age of first-time diabetes mellitus diagnosis. Patients classified according to the age of diagnosis, gender, and ethnicity. The study included 519 patients with age (55.6±13.7) years, female 265 (51.1%) and male 254 (48.9%). The ethnicity distribution was Malay 191 (36.8%), Chinese 189 (36.4%) and Indian 139 (26.8%). The age of Type 2 diabetes diagnosis was (42±14.8) years. The female onset of diabetes mellitus was at age (41.5±13.7) years, while male (42.6±13.7) years. Distribution of diabetic onset by ethnicity was Malay at age (40.7±13.7) years, Chinese (43.2±13.7) years and Indian (42.3±13.7) years. Diabetic onset was classified by age as follow; ≤20 years’ cohort was 33 (6.4%) cases. Group >20- ≤40 years was 190 (36.6%) patients, and category >40- ≤60 years was 270 (52%) subjects. On the other hand, the group >60 years was 22 (4.2%) patients. The range of diagnosis was between 10 and 73 years old. Conclusion: Malay and female have an earlier onset of diabetes than Indian, Chinese and male. More than half of the patients had diabetes between 40 and 60 years old. Diabetes mellitus is becoming more common in younger age <40 years. The age at diagnosis of Type 2 diabetes mellitus has decreased with time.

Keywords: age of onset, diabetes diagnosis, diabetes mellitus, Malaysia, outpatients, type 2 diabetes, retrospective study

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Authors: S. Ghanaraja, Subrata Ray, S. K. Nath

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Particle reinforced Metal Matrix Composite (MMC) succeeds in synergizing the metallic matrix with ceramic particle reinforcements to result in improved strength, particularly at elevated temperatures, but adversely it affects the ductility of the matrix because of agglomeration and porosity. The present study investigates the outcome of tensile properties in a cast and hot forged composite reinforced simultaneously with coarse and fine particles. Nano-sized alumina particles have been generated by milling mixture of aluminum and manganese dioxide powders. Milled particles after drying are added to molten metal and the resulting slurry is cast. The microstructure of the composites shows good distribution of both the size categories of particles without significant clustering. The presence of nanoparticles along with coarser particles in a composite improves both strength and ductility considerably. Delay in debonding of coarser particles to higher stress is due to reduced mismatch in extension caused by increased strain hardening in presence of the nanoparticles. However, higher addition of powder mix beyond a limit results in deterioration of mechanical properties, possibly due to clustering of nanoparticles. The porosity in cast composite generally increases with the increasing addition of powder mix as observed during process and on forging it has got reduced. The base alloy and nanocomposites show improvement in flow stress which could be attributed to lowering of porosity and grain refinement as a consequence of forging.

Keywords: aluminium, alumina, nano-particle reinforced composites, porosity

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Authors: Dina Dahood Dabash

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Refugee camps are habitually defined as receptive sites, transient spaces of exile and nondescript depoliticized places of exception. However, such arguments form partial sides of reality, especially in countries that are geopolitically challenged and rely immensely on international aid. In Jordan, the dynamics brought with the floating population of refugees (Palestinian amongst others) have resulted in spatial after-effects that cannot be easily overlooked. For instance, Palestine refugee camps have turned by time into socioeconomic centers of gravity and cores of spatial evolution. Yet, such a position is not instantaneous. Amongst various reasons, it can be related, according to this paper, to a distinctive institutional climate that has been co-produced by the refugees, host community and the state. This paper aims to investigate the evolution of urban and spatial regulations in Jordan between 1948 and 1995, more specifically, state regulations, community regulations and refugee-self-regulation that all dynamically interacted that period. The paper aims to unpack the relations between refugee camps and their environs to further explore the agency of such floating populations in establishing rooted networks that extended the time and place boundaries. The paper’s argument stems from the fact that the spatial configuration of urban systems is not only an outcome of a historical evolutionary process but is also a result of interactions between the actors. The research operationalizes Marka camp in Jordan as a case study. Marka Camp is one of the six "emergency" camps erected in 1968 to shelter 15,000 Palestine refugees and displaced persons who left the West Bank and Gaza Strip. Nowadays, camp shelters more than 50,000 refugees in the same area of land. The camp is located in Russeifa, a city in Zarqa Governorate in Jordan. Together with Amman and Zarqa, Russeifa is part of a larger metropolitan area that acts as a home to more than half of Jordan’s businesses. The paper aspires to further understand the post-conflict strategies which were historically applied in Jordan and can be employed to handle more recent geopolitical challenges such as the Syrian refugee crisis. Methodological framework: The paper traces the evolution of the refugee-camp regulating norms in Jordan, parallel with the horizontal and vertical evolution of the Marka camp and its surroundings. Consequently, the main methods employed are historical and mental tracing, Interviews, in addition to using available Aerial and archival photos of the Marka camp and its surrounding.

Keywords: forced migration, Palestine refugee camps, spatial agency, urban regulations

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Authors: Firas M. Tuaimah

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This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity. The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: short-term load forecasting, artificial neural networks, back propagation learning, hourly load demand

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Authors: Umar Mujahid, Greatzel Unabia, Hongsik Choi, Binh Tran

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Radio Frequency Identification (RFID) is one of the most commonly used technologies in IoTs and Wireless Sensor Networks which makes the devices identification and tracking extremely easy to manage. Since RFID uses wireless channel for communication, which is open for all types of adversaries, researchers have proposed many Ultralightweight Mutual Authentication Protocols (UMAPs) to ensure security and privacy in a cost-effective manner. These UMAPs involve simple bitwise logical operators such as XOR, AND, OR & Rot, etc., to design the protocol messages. However, most of these UMAPs were later reported to be vulnerable against many malicious attacks. In this paper, we have presented a detailed overview of some eminent UMAPs and also discussed the many security attacks on them. Finally, some recommendations and suggestions have been discussed, which can improve the design of the UMAPs.

Keywords: RFID, Ultralightweight, UMAP, SASI

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Authors: Carolina Senabre, Sergio Valero, Miguel Lopez, Antonio Gabaldon

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This paper presents a comprehensive survey of the short-term load forecasting (STLF). Since the behavior of consumers and producers continue changing as new technologies, it is an ongoing process, and moreover, new policies become available. The results of a research study for the Spanish Transport System Operator (REE) is presented in this paper. It is presented the improvement of the forecasting accuracy in the Balearic Islands considering the introduction of meteorological variables, such as temperature to reduce forecasting error. Variables analyzed for the forecasting in terms of overall accuracy are cloudiness, solar radiation, and wind velocity. It has also been analyzed the type of days to be considered in the research.

Keywords: short-term load forecasting, power demand, neural networks, load forecasting

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Authors: Sally A. El Awdan, Gehad A. Abdel Jaleel, Dalia O Saleh, Manal Badawi

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Background: Diabetes is a metabolic disease that affects a wide range of people worldwide and results in serious complications. Streptozotocin (STZ) causes selective cytotoxicity in the pancreatic β-cell, and it has been extensively used to induce diabetes mellitus in rats. The present study investigated the effects of diosmin and chrysin alone or in combination with each other on glucose level and on liver in STZ diabetic rats. Methods: In this study, rats were divided into six experimental groups (normal, untreated STZ-diabetic (60 mg/kg B.W., IP), treated STZ-diabetic with glycazide (10 mg/kg B.W, oral), treated STZ-diabetic with diosmin (100 mg/kg B. W., oral), treated STZ-diabetic with chrysin (80 mg/kg B.W., oral), treated STZ-diabetic with diosmin (50 mg/kg B.W, oral) + chrysin (40 mg/kg B.W., oral). After 2 weeks blood samples were withdrawn and glucose was measured. Animals were anaesthetized with an intraperitoneal injection of sodium pentobarbital (60 mg/kg), and sacrificed for dissecting liver. Results: Throughout the experimental period, all treatments significantly (P<0.05) lowered serum glucose, AST, ALT, triglyceride, cholesterol, IL-6, TNF-α and IL-1β. Moreover, the treated diabetic rats showed higher levels of reduced glutathione (P<0.05) in the liver compared to the diabetic control rats and inhibited diabetes-induced elevation in the levels of malondialdehyde in liver. The results of this study clearly demonstrated that diosmin and chrysin possess several treatment-oriented properties, including the control of hyperglycemia, antioxidant effects and anti-inflammatory effects. Conclusion: Considering these observations, it appears that diosmin and chrysin may be a useful supplement to delay the developmentof diabetes and its complications.

Keywords: diabetes, streptozocin, chrysin, rat, diosmin, cytokines

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Authors: Monsuru Oyenola Popoola, Oladapo Samson Abiola, Wusamotu Alao Adeniji

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The prevalent and incessant abandonment of road construction projects are alarming that it creates several negative effects to social, economic and environmental values of the project. The purpose of this paper is to investigate and determined the various causes and effects of abandoning road construction projects in Nigeria. Likert Scale questionnaire design was used to administered and analysed the data obtained for the stydy. 135 (Nr) questionnaires were completed and retrieved from the respondents, out of 200 (Nr) questionnaires sent out, representing a response rate of 67.5%. The analysis utilized the Relative Importance Index (R.I.I.) method and the results are presented in tabular form. The findings confirms that at least 20 factors were the causes of road projects abandonment in Nigeria with most including Leadership Instability, Improper Project Planning, Inconsistence in government policies and Design, Contractor Incompetence, Economy Instability and Inflation, Delay in remittance of money, Improper financial analysis, Poor risk management, Climatic Conditions, Improper Project Estimates etc. The findings also show that at least eight (8) effect were identified on the system, and these include; Waste of Financial Resources, Loss of economic value, Environmental degradation, Loss of economic value, Reduction in standard of living, Litigation and Arbitration, etc. The reflection is that allocating reasonable finance, developing appropriate and effective implementation plans and monitoring, evaluation and reporting on development project activities by key actors should enhance in resolving the problem of road projects abandonment.

Keywords: road construction, abandonment of road projects, climatic condition, project planning, contractor

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Authors: Tomas Makaras

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Sticklebacks (Gasterosteiformes) are increasingly used in ecological and evolutionary research and become well-established role as model species for biologists. However, ecotoxicology studies concerning behavioural effects in sticklebacks regarding stress responses, mainly induced by chemical mixtures, have hardly been addressed. Moreover, although many authors in their studies emphasised the similarity between three-spined and nine-spined stickleback in morphological, neuroanatomical and behavioural adaptations to environmental changes, several comparative studies have revealed considerable differences between these species in and their susceptibility and resistance to variousstressors in laboratory experiments. The hypothesis of this study was that three-spined and nine-spined stickleback species will demonstrate apparent differences in response patterns and sensitivity to metal-based chemicals stimuli. For this purpose, we investigated the swimming behaviour (including mortality rate based on 96-h LC50 values) of two ecologically similar three-spined (Gasterosteusaculeatus) and nine-spined sticklebacks (Pungitiuspungitius) to short-term (up to 24 h) metal mixture (MIX) exposure. We evaluated the relevance and efficacy of behavioural responses of test species in the early toxicity assessment of chemical mixtures. Fish exposed to six (Zn, Pb, Cd, Cu, Ni and Cr) metals in the mixture were either singled out by the Water Framework Directive as priority or as relevant substances in surface water, which was prepared according to the environmental quality standards (EQSs) of these metals set for inland waters in the European Union (EU) (Directive 2013/39/EU). Based on acute toxicity results, G. aculeatus found to be slightly (1.4-fold) more tolerant of MIX impact than those of P. pungitius specimens. The performed behavioural analysis showed the main effect on the interaction between time, species and treatment variables. Although both species exposed to MIX revealed a decreasing tendency in swimming activity, these species’ responsiveness to MIX was somewhat different. Substantial changes in the activity of G. aculeatus were established after 3-h exposure to MIX solutions, which was 1.43-fold lower, while in the case of P. pungitius, 1.96-fold higher than established 96-h LC50 values for each species. This study demonstrated species-specific differences in response sensitivity to metal-based water pollution, indicating behavioural insensitivity of P. pungitiuscompared to G. aculeatus. While many studies highlight the usefulness and suitability of nine-spined sticklebacks for evolutionary and ecological research, attested by their increasing popularity in these fields, great caution must be exercised when using them as model species in ecotoxicological research to probe metal contamination. Meanwhile, G. aculeatus showed to be a promising bioindicator species in the environmental ecotoxicology field.

Keywords: acute toxicity, comparative behaviour, metal mixture, swimming activity

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Authors: Tessa E. Reid, Vanessa N. Kavamura, Maider Abadie, Adriana Torres-Ballesteros, Mark Pawlett, Ian M. Clark, Jim Harris, Tim Mauchline

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The deleterious effect of chemical fertilizer on rhizobacterial diversity has been well documented using 16S rRNA gene amplicon sequencing and predictive metagenomics. Biofertilization is a cost-effective and sustainable alternative; improving strategies depends on isolating beneficial soil microorganisms. Although culturing is widespread in biofertilization, it is unknown whether the composition of cultured isolates closely mirrors native beneficial rhizobacterial populations. This study aimed to determine the relative abundance of culturable plant growth-promoting rhizobacteria (PGPR) isolates within total soil DNA and how potential PGPR populations respond to chemical fertilization in a commercial wheat variety. It was hypothesized that PGPR will be reduced in fertilized relative to unfertilized wheat. Triticum aestivum cv. Cadenza seeds were sown in a nutrient depleted agricultural soil in pots treated with and without nitrogen-phosphorous-potassium (NPK) fertilizer. Rhizosphere and rhizoplane samples were collected at flowering stage (10 weeks) and analyzed by culture-independent (amplicon sequence variance (ASV) analysis of total rhizobacterial DNA) and -dependent (isolation using growth media) techniques. Rhizosphere- and rhizoplane-derived microbiota culture collections were tested for plant growth-promoting traits using functional bioassays. In general, fertilizer addition decreased the proportion of nutrient-solubilizing bacteria (nitrate, phosphate, potassium, iron and, zinc) isolated from rhizocompartments in wheat, whereas salt tolerant bacteria were not affected. A PGPR database was created from isolate 16S rRNA gene sequences and searched against total soil DNA, revealing that 1.52% of total community ASVs were identified as culturable PGPR isolates. Bioassays identified a higher proportion of PGPR in non-fertilized samples (rhizosphere (49%) and rhizoplane (91%)) compared to fertilized samples (rhizosphere (21%) and rhizoplane (19%)) which constituted approximately 1.95% and 1.25% in non-fertilized and fertilized total community DNA, respectively. The analyses of 16S rRNA genes and deduced functional profiles provide an in-depth understanding of the responses of bacterial communities to fertilizer; this study suggests that rhizobacteria, which potentially benefit plants by mobilizing insoluble nutrients in soil, are reduced by chemical fertilizer addition. This knowledge will benefit the development of more targeted biofertilization strategies.

Keywords: bacteria, fertilizer, microbiome, rhizoplane, rhizosphere

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Authors: F. Pal-Fam, S. Keszthelyi

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Phytosanitary condition of sunflower (Helianthus annuus L.) was endangered by several phytopathogenic agents, mainly microfungi, such as Sclerotinia sclerotiorum, Diaporthe helianthi, Plasmopara halstedtii, Macrophomina phaseolina and so on. There are more agrotechnical and chemical technologies against them, for instance, tolerant hybrids, crop rotations and eventually several in-crop chemical treatments. There are different fungicide treatment methods in sunflower in Hungarian agricultural practice in the quest of obtaining healthy and economic plant products. Besides, there are many choices of useable active ingredients in Hungarian sunflower protection. This study carried out into the examination of the effect of five different fungicide active substances (found on the market) and three different application modes (early; late; and early and late treatments) in a total number of 9 sample plots, 0.1 ha each other. Five successive vegetation periods have been investigated in long term, between 2013 and 2017. The treatments were: 1)untreated control; 2) boscalid and dimoxystrobin late treatment (July); 3) boscalid and dimoxystrobin early treatment (June); 4) picoxystrobin and cyproconazole early treatment; 5) picoxystrobin and cymoxanil and famoxadone early treatment; 6) picoxystrobin and cyproconazole early; cymoxanil and famoxadone late treatments; 7) picoxystrobin and cyproconazole early; picoxystrobin and cymoxanil and famoxadone late treatments; 8) trifloxystrobin and cyproconazole early treatment; and 9) trifloxystrobin and cyproconazole both early and late treatments. Due to the very different yearly weather conditions different phytopathogenic fungi were dominant in the particular years: Diaporthe and Alternaria in 2013; Alternaria and Sclerotinia in 2014 and 2015; Alternaria, Sclerotinia and Diaporthe in 2016; and Alternaria in 2017. As a result of treatments ‘infection frequency’ and ‘infestation rate’ showed a significant decrease compared to the control plot. There were no significant differences between the efficacies of the different fungicide mixes; all were almost the same effective against the phytopathogenic fungi. The most dangerous Sclerotinia infection was practically eliminated in all of the treatments. Among the single treatments, the late treatment realised in July was the less efficient, followed by the early treatments effectuated in June. The most efficient was the double treatments realised in both June and July, resulting 70-80% decrease of the infection frequency, respectively 75-90% decrease of the infestation rate, comparing with the control plot in the particular years. The lowest yield quantity was observed in the control plot, followed by the late single treatment. The yield of the early single treatments was higher, while the double treatments showed the highest yield quantities (18.3-22.5% higher than the control plot in particular years). In total, according to our five years investigation, the most effective application mode is the double in-crop treatment per vegetation time, which is reflected by the yield surplus.

Keywords: fungicides, treatments, phytopathogens, sunflower

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Authors: Zaid Jamal Saeed Almahmoud

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Our increasing reliance on electricity, with inefficient consumption trends, has resulted in several economical and environmental threats. These threats include wasting billions of dollars, draining limited resources, and elevating the impact of climate change. As a solution, the smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing the peak power consumption under a fixed delay requirement is a significant problem in the smart grid. In addition, matching demand to supply is a key requirement for the success of the future electricity. In this work, we consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-Hard, we propose two versions of a heuristic algorithm for solving this problem. Our theoretical analysis and experimental results show that our proposed heuristics outperform existing methods by providing a better approximation to the optimal solution. In addition, we consider dynamic pricing methods to minimize the peak load and match demand to supply in the smart grid. Our contribution is the proposal of generic, as well as customized pricing heuristics to minimize the peak demand and match demand with supply. In addition, we propose optimal pricing algorithms that can be used when the maximum deadline period of the power jobs is relatively small. Finally, we provide theoretical analysis and conduct several experiments to evaluate the performance of the proposed algorithms.

Keywords: heuristics, optimization, smart grid, peak demand, power supply

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Authors: Aravind Mohan Krishnan

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This paper identifies a research gap in the literature on tourism entrepreneurship in Malawi, Africa, and investigates how entrepreneurs from the Malawian tourism sector discover and exploit business opportunities. In particular, the importance of prior experience and business networks in the opportunity development process is debated. Another area of empirical research examined here is the opportunity recognition-venture creation sequence. While Malawi presents fruitful business opportunities, exploiting these opportunities into fully realized business ideas is a real challenge due to the country’s difficult business environment and poor promotional and marketing efforts. The study concludes by calling for further research in Sub-Saharan Africa in order to develop our understanding of entrepreneurship in this (African) context.

Keywords: entrepreneurship, Malawi, opportunities, tourism

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Authors: Victor Rocha Carvalho

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The Bonner Sphere Spectrometry was used to obtain the average energy, the fluence rate, and radioprotection quantities such as the personal and ambient dose equivalent of the ²⁴¹AmLi and ²⁴¹AmF isotopic neutron sources used in the Neutron Metrology Laboratory - LN. The counts of the sources were performed with six different spherical moderators around the detector. Through this, the neutron spectrum was obtained by means of the software named NeuraLN, developed by the LN, that uses the neural networks technique. The 241AmLi achieved a result close to the literature, and 241AmF, which contains few published references, acquired a result with a slight variation from the literature. Therefore, besides fulfilling its objective, the work raises questions about a possible standard of the ²⁴¹AmLi and about the lack of work with the ²⁴¹AmF.

Keywords: nuclear physics, neutron metrology, neutron spectrometry, bonner sphere spectrometers

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Authors: Sanju Vaidya, Aihua Li

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Vulnerability measures and topological indices are crucial in solving various problems such as the stability of the communication networks and development of mathematical models for chemical compounds. In 1947, Harry Wiener introduced a topological index related to molecular branching. Now there are more than 100 topological indices for graphs. For example, Hosoya polynomials (also called Wiener polynomials) were introduced to derive formulas for certain vulnerability measures and topological indices for various graphs. In this paper, we will find a relation between the Hosoya polynomials of any graph and its Mycielskian graph. Additionally, using this we will compute vulnerability measures, closeness and betweenness centrality, and extended Wiener indices. It is fascinating to see how Hosoya polynomials are useful in the two diverse fields, cybersecurity and chemistry.

Keywords: hosoya polynomial, mycielskian graph, graph vulnerability measure, topological index

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Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Midhun Xavier

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This paper introduces a method to verify multi-agent systems in industrial control systems using blockchain technology. The proposed solution enables to record and verify each process that occurs while generating a customized product using Ethereum-based smart contracts. Node-Red software agents are developed with the help of semantic web technologies, and these software agents interact with IEC 61499 function blocks to execute the processes. The agent associated with each mechatronic component and its controller can communicate with the blockchain to record various events that occur during each process, and the latter smart contract helps to verify these process orders of the customized product.

Keywords: blockchain, Ethereum, node-red, IEC 61499, multi-agent system, MQTT

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Authors: Cristian F.T. Montenegro, Luís F. N. Lourenço, Maurício B. C. Salles, Renato M. Monaro

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More PV systems have been connected to the electrical network each year. As the number of PV systems increases, some issues affecting grid operations have been identified. This paper studied the impacts related to changes in solar irradiance on a distribution/sub-transmission network, considering variations due to moving clouds and daily cycles. Using MATLAB/Simulink software, a solar farm of 30 MWp was built and then implemented to a test network. From simulations, it has been determined that irradiance changes can have a significant impact on the grid by causing voltage fluctuations outside the allowable thresholds. This work discussed some local control strategies and grid reinforcements to mitigate the negative effects of the irradiance changes on the grid.

Keywords: reactive power control, solar irradiance, utility-scale PV systems, voltage fluctuations

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Authors: Ahmed Stifi, Sascha Gentes, Fritz Gehbauer

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The construction industry is perhaps one of the oldest industry of the world. The ancient monuments like the egyptian pyramids, the temples of Greeks and Romans like Parthenon and Pantheon, the robust bridges, old Roman theatres, the citadels and many more are the best testament to that. The industry also has a symbiotic relationship with other . Some of the heavy engineering industry provide construction machineries, chemical industry develop innovative construction materials, finance sector provides fund solutions for complex construction projects and many more. Construction Industry is not only mammoth but also very complex in nature. Because of the complexity, construction industry is prone to various tribulations which may have the propensity to hamper its growth. The comparitive study of this industry with other depicts that it is associated with a state of tardiness and delay especially when we focus on the managerial aspects and the study of triple constraint (time, cost and scope). While some institutes says the complexity associated with it as a major reason, others like lean construction, refers to the wastes produced across the construction process as the prime reason. This paper introduces corruption as one of the prime factors for such delays.To support this many international reports and studies are available depicting that construction industry is one of the most corrupt sectors worldwide, and the corruption can take place throught the project cycle comprising project selection, planning, design, funding, pre-qualification, tendering, execution, operation and maintenance, and even through the reconstrction phase. It also happens in many forms such as bribe, fraud, extortion, collusion, embezzlement and conflict of interest and the self-sufficient. As a solution to cope the corruption in construction industry, the paper introduces the integrity as a key factor and build a new integrity framework to develop and implement an integrity management system for construction companies and construction projects.

Keywords: corruption, construction industry, integrity, lean construction

Procedia PDF Downloads 362

Authors: Ankit Shai

Abstract:

CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

Procedia PDF Downloads 275

Authors: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

Procedia PDF Downloads 63

Authors: Mehrnaz Mostafavi

Abstract:

Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

Procedia PDF Downloads 54

Authors: Elabed Saud

Abstract:

This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

Procedia PDF Downloads 701

Authors: Noor A. Hakim

Abstract:

Several studies in the developed countries investigated the prevalence of diabetes and obesity among individuals from different socioeconomic levels and suggested lower rates among the higher socioeconomic groups. However, studies evaluating diabetes risk and prevalence of obesity among the population of middle- to high-income status in developing countries are limited. The aim of this study is to evaluate the risk of developing type-2 diabetes mellitus (T2DM) and the weight status of female students in private universities in Jeddah City, Saudi Arabia. This is a cross-sectional study of 121 female students aged ≤ 25 years old was conducted; participants were recruited from two private universities. Diabetes risk was evaluated using the Finnish Diabetes Risk Score. Anthropometric measurements were assessed, and body-mass-index (BMI) was calculated. Diabetes risk scores indicated that 35.5% of the female students had a slightly elevated risk, and 10.8% had a moderate to high risk to develop T2DM. One-third of the females (29.7%) were overweight or obese. The majority of the normal weight and underweight groups were classified to have a low risk of diabetes, 22.2% of the overweight participants were classified to have moderate to high risk, and over half of the obese participants (55.5%) were classified to be at the moderate to high-risk category. Conclusions: Given that diabetes risk is alarming among the population in Saudi Arabia, healthcare providers should utilize a simple screening tool to identify high-risk individuals and initiate diabetes preventive strategies to prevent, or delay, the onset of T2DM and improve the quality of life.

Keywords: risk of type 2 diabetes, weight status, college students, socioeconomic status

Procedia PDF Downloads 159