Abstract: This study aims to present an overview of recent research in building energy-retrofitting strategy applications and analyzing them within the context of hot arid climate regions which is in this case study represented by the Kingdom of Saudi Arabia. The main goal of this research is to do an analytical study of recent research approaches to show where the primary gap in knowledge exists and outline which possible strategies are available that can be applied in future research. Also, the paper focuses on energy retrofitting strategies at a building envelop level. The study is limited to specific measures within the hot arid climate region. Scientific articles were carefully chosen as they met the expression criteria, such as retrofitting, energy-retrofitting, hot-arid, energy efficiency, residential buildings, which helped narrow the research scope. Then the papers were explored through descriptive analysis and justified results within the Saudi context in order to draw an overview of future opportunities from the field of study for the last two decades. The conclusions of the analysis of the recent research confirmed that the field of study had a research shortage on investigating actual applications and testing of newly introduced energy efficiency applications, lack of energy cost feasibility studies and there was also a lack of public awareness. In terms of research methods, it was found that simulation software was a major instrument used in energy retrofitting application research. The main knowledge gaps that were identified included the need for certain research regarding actual application testing; energy retrofitting strategies application feasibility; the lack of research on the importance of how strategies apply first followed by the user acceptance of developed scenarios.
Abstract: Cotton, as a strategic crop, plays an important role in providing human food and clothing need, because of its oil, protein, and fiber. Iran has been one of the largest cotton producers in the world in the past, but unfortunately, for economic reasons, its production is reduced now. One of the ways to reduce the cost of cotton production is to expand the mechanization of cotton harvesting. Iranian farmers do not accept the function of cotton harvesters. One reason for this lack of acceptance of cotton harvesting machines is the number of field losses on these machines. So, the majority of cotton fields are harvested by hand. Although the correct setting of the harvesting machine is very important in the cotton losses, the morphological properties of the cotton plant also affect the performance of cotton harvesters. In this study, the effect of some cotton morphological properties such as the height of the cotton plant, number, and length of sympodial and monopodial branches, boll dimensions, boll weight, number of carpels and bracts angle were evaluated on the performance of cotton picker. In this research, the efficiency of John Deere 9920 spindle Cotton picker is investigated on five different Iranian cotton cultivars. The results indicate that there was a significant difference between the five cultivars in terms of machine harvest efficiency. Golestan cultivar showed the best cotton harvester performance with an average of 87.6% of total harvestable seed cotton and Khorshid cultivar had the least cotton harvester performance. The principal component analysis showed that, at 50.76% probability, the cotton picker efficiency is affected by the bracts angle positively and by boll dimensions, the number of carpels and the height of cotton plants negatively. The seed cotton remains (in the plant and on the ground) after harvester in PCA scatter plot were in the same zone with boll dimensions and several carpels.
Abstract: Maintenance has evolved into an imperative function, and contributes significantly to efficient and effective equipment performance. Total Productive Maintenance (TPM) is an ideal approach to support the development and implementation of operation performance improvement. It systematically aims to understand the function of equipment, the service quality relationship with equipment and the probable critical equipment failure conditions. Implementation of TPM programmes need strategic planning and there has been little research applied in this area within Middle-East power plants. In the power sector of Abu Dhabi, technologically and strategically, the power industry is extremely important, and it thus needs effective and efficient equipment management support. The aim of this paper is to investigate barriers to successful TPM implementation in the Abu Dhabi power industry. The study has been conducted in the context of a leading power company in the UAE. Semi-structured interviews were conducted with 16 employees, including maintenance and operation staff, and senior managers. The findings of this research identified seven key barriers, thus: managerial; organisational; cultural; financial; educational; communications; and auditing. With respect to the understanding of these barriers and obstacles in TPM implementation, the findings can contribute towards improved equipment operations and maintenance in power organisations.
Abstract: Perceived risks play a major role in consumer intentions, behaviors, attitudes, and decisions about online shopping in the KSA. This paper investigates the influence of six perceived risk dimensions on Saudi consumers: product risk, information risk, financial risk, privacy and security risk, delivery risk, and terms and conditions risk empirically. To ensure the success of this study, a random survey was distributed to reflect the consumers’ perceived risk and to enable the generalization of the results. Data were collected from 323 respondents in the Kingdom of Saudi Arabia (KSA): 50 who had never shopped online and 273 who had done so. The results indicated that all six risks influenced the respondents’ perceptions of online shopping. The non-online shoppers perceived financial and delivery risks as the most significant barriers to online shopping. This was followed closely by performance, information, and privacy and security risks. Terms and conditions were perceived as less significant. The online consumers considered delivery and performance risks to be the most significant influences on internet shopping. This was followed closely by information and terms and conditions. Financial and privacy and security risks were perceived as less significant. This paper argues that introducing adequate legal solutions to addressing related problems arising from this study is an urgent need. This may enhance consumer trust in the KSA online market, increase consumers’ intentions regarding online shopping, and improve consumer protection.
Abstract: State Estimator became an intrinsic part of Energy Management Systems (EMS). The SCADA measurements received from the field are processed by the State Estimator in order to accurately determine the actual operating state of the power systems and provide that information to other real-time network applications. All EMS vendors offer a State Estimator functionality in their baseline products. However, setting up and ensuring that State Estimator consistently produces a reliable solution often consumes a substantial engineering effort. This paper provides generic recommendations and describes a simple practical approach to efficient tuning of State Estimator, based on the working experience with major EMS software platforms and consulting projects in many electrical utilities of the USA.
Abstract: Postural balance plays essential role throughout life in daily activities. Somatosensory, visual and vestibular inputs play the fundamental role in maintaining body equilibrium to balance the posture. The aim of this study was to find out electroencephalography (EEG) responses during balance activity of young people during Sensory Organization Balance Test. The outcome of this study will help to create the fitness and neurorehabilitation plan. 25 young people (25 ± 3.1 years) have been analyzed on Balance Master NeuroCom® with the coupling of Brain Vision 32 electrode wireless EEG system during the Sensory Organization Test. From the results it has been found that the balance score of samples is significantly higher under the influence of somatosensory input as compared to visual and vestibular input (p < 0.05). The EEG between somatosensory and visual input to balance the posture showed significantly higher (p < 0.05) alpha and beta activities during somatosensory input in somatosensory, attention and visual functions of the cortex whereas executive and motor functions of the cerebral cortex showed significantly higher (p < 0.05) alpha EEG activity during the visual input. The results suggest that somatosensory and attention function of the cerebral cortex has alpha and beta activity, respectively high during somatosensory and vestibular input in maintaining balance. In patients with balance impairments both physical and cognitive training, including neurofeedback will be helpful to improve balance abilities.
Abstract: The evolution in mobile broadband technologies has allowed to increase the download rates in users considering the current services. The evaluation of technical parameters at the link level is of vital importance to validate the quality and veracity of the connection, thus avoiding large losses of data, time and productivity. Some of these failures may occur between the eNodeB (Evolved Node B) and the user equipment (UE), so the link between the end device and the base station can be observed. LTE (Long Term Evolution) is considered one of the IP-oriented mobile broadband technologies that work stably for data and VoIP (Voice Over IP) for those devices that have that feature. This research presents a technical analysis of the connection and channeling processes between UE and eNodeB with the TAC (Tracking Area Code) variables, and analysis of performance variables (Throughput, Signal to Interference and Noise Ratio (SINR)). Three measurement scenarios were proposed in the city of Bogotá using QualiPoc, where two operators were evaluated (Operator 1 and Operator 2). Once the data were obtained, an analysis of the variables was performed determining that the data obtained in transmission modes vary depending on the parameters BLER (Block Error Rate), performance and SNR (Signal-to-Noise Ratio). In the case of both operators, differences in transmission modes are detected and this is reflected in the quality of the signal. In addition, due to the fact that both operators work in different frequencies, it can be seen that Operator 1, despite having spectrum in Band 7 (2600 MHz), together with Operator 2, is reassigning to another frequency, a lower band, which is AWS (1700 MHz), but the difference in signal quality with respect to the establishment with data by the provider Operator 2 and the difference found in the transmission modes determined by the eNodeB in Operator 1 is remarkable.
Abstract: Since the discovery of the manuscript, mechanical methods for storing, transferring and using the information have evolved into digital methods over the time. In this process, libraries that are the center of the information have also become digitized and become accessible from anywhere and at any time in the world by taking on a structure that has no physical boundaries. In this context, some criteria for information obtained from digital libraries have become more important for users. This paper evaluates the user criteria from different perspectives that make a digital library more useful. The Step-Wise Weight Assessment Ratio Analysis-Weighted Aggregated Sum Product Assessment (SWARA-WASPAS) method is used with flexibility and easy calculation steps for the evaluation of digital library criteria. Three different digital libraries are evaluated by information technology experts according to five conflicting main criteria, ‘interface design’, ‘effects on users’, ‘services’, ‘user engagement’ and ‘context’. Finally, alternatives are ranked in descending order.
Abstract: This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.
Abstract: In this study, we will aim to analyze how the period of the state of emergency in Turkey lead to gaps in law and the formation of areas in which there was a complete lack of supervision. The state of emergency that was proclaimed following the coup attempt of July 15, 2016, continued until July 18, 2018, that is to say, 2 years, without taking into account whether the initial circumstances persisted. As part of this work, we claim that the state of emergency provided the executive power with important tools for governing, which it took constant use. We can highlight how the concern for security at the center of the basic considerations of the people in a city was exploited as a foundation by the military power in Turkey to interfere in the political, legal and social spheres. The constitutions of 1924, 1961 and 1982 entrusted the army with the role of protector of the integrity of the state. This became an instrument at the hands of the military to legitimize their interventions in the name of public security. Its interventions in the political field are indeed politically motivated. The constitution, the legislative and regulatory systems are modified and monopolized by the military power that dominates the legislative, regulatory and judicial power, leading to a state of exception. With the political convulsions over a decade, the government was able to usurp the instrument called the state of exception. In particular, the decree-laws of the state of emergency, which the executive makes frequent and generally abusive use, became instruments in the hands of the government to take measures that it wishes to escape from the rules and the pre-established control mechanisms. Thus the struggle against the political opposition becomes more unbalanced and destructive. To this must also be added the ineffectiveness of ex-post controls and domestic remedies. This research allows us to stress how a legal concept such as "the state of emergency" can be politically exploited to make it a legal weapon that continues to produce victims.
Abstract: Taking Japanese and Chinese animation industry as research objects with a detailed analysis and comparison of the industrial models and status quo in two countries, this study fully reveals the development mechanism and internal and external situations of the industry. It is believed that the Japanese animation industry's continuous pursuit of low-cost production models, virtuous recycling mechanisms, and active expansion of overseas markets are valuable experiences; whereas China needs to strengthen national and local support for animation and emphasis on the protection of the copyright. The targeted and forward-looking suggestions and conclusions proposed in this study provides not only an insight into the animation industry but also inspirations for development in the animation industry around the world through an analysis of experiences and shortcomings.
Abstract: This paper presents a method for single image dehazing based on dark channel prior (DCP). The property that the intensity of the dark channel gives an approximate thickness of the haze is used to estimate the transmission and atmospheric light. Instead of constant atmospheric light, the proposed method employs scene depth to estimate spatially varying atmospheric light as it truly occurs in nature. Haze imaging model together with the soft matting method has been used in this work to produce high quality haze free image. Experimental results demonstrate that the proposed approach produces better results than the classic DCP approach as color fidelity and contrast of haze free image are improved and no over-saturation in the sky region is observed. Further, lifting Haar wavelet transform is employed to reduce overall execution time by a factor of two to three as compared to the conventional approach.
Abstract: Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.
Abstract: Since the beginning of the 20th century, sportswear has a major contribution to the impact of fashion on our lives. Nowadays, the embracing of sportswear fashion/looks is undoubtedly noticeable, as the modern consumer searches for high comfort and linear aesthetics for its clothes. This compromise lead to the arise of the athleisure trend. Athleisure surges as a new style area that combines both wearability and fashion sense, differentiated from the archetypal sportswear, usually associated to “gym clothes”. Additionally, the possibility to functionalize and implement new technologies have shifted and progressively empowers the connection between the concepts of physical activities practice and well-being, allowing clothing to be more interactive and responsive with its surroundings. In this study, a design inspired in retro and urban lifestyle was envisioned, engineering textile structures that can respond to external stimuli. These structures are enhanced to be responsive to heat, water vapor and humidity, integrating shape memory polymers (SMP) to improve the breathability and heat-responsive behavior of the textiles and zinc oxide nanoparticles (ZnO NPs) to heighten the surface hydrophobic properties. The best results for hydrophobic exhibited superhydrophobic behavior with water contact angle (WAC) of more than 150 degrees. For the breathability and heat-response properties, SMP-coated samples showed an increase in water vapour permeability values of about 50% when compared with non SMP-coated samples. These innovative technological approaches were endorsed to design innovative clothing, in line with circular economy and eco-design principles, by assigning a substantial degree of mutability and versatility to the clothing. The development of a coat and shirt, in which different parts can be purchased separately to create multiple products, aims to combine the technicality of both the fabrics used and the making of the garments. This concept translates itself into a real constructive mechanism through the symbiosis of high-tech functionalities and the timeless design that follows the athleisure aesthetics.
Abstract: The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.
Abstract: Landfilling of organic waste is still the predominant waste management method in the USA and Canada. Strategic plans for waste diversion from landfills are needed to increase material recovery and energy generation from waste. In this paper, we carried out a statistical survey on waste flow in the two cities New York and Montréal and estimated the energy recovery potential for each case. Data collection and analysis of the organic waste (food waste, yard waste, etc.), paper and cardboard, metal, glass, plastic, carton, textile, electronic products and other materials were done based on the reports published by the Department of Sanitation in New York and Service de l'Environnement in Montréal. In order to calculate the gas generation potential of organic waste, Buswell equation was used in which the molar mass of the elements was calculated based on their atomic weight and the amount of organic waste in New York and Montréal. Also, the higher and lower calorific value of the organic waste (solid base) and biogas (gas base) were calculated. According to the results, only 19% (598 kt) and 45% (415 kt) of New York and Montréal waste were diverted from landfills in 2017, respectively. The biogas generation potential of the generated food waste and yard waste amounted to 631 million m3 in New York and 173 million m3 in Montréal. The higher and lower calorific value of food waste were 3482 and 2792 GWh in New York and 441 and 354 GWh in Montréal, respectively. In case of yard waste, they were 816 and 681 GWh in New York and 636 and 531 GWh in Montréal, respectively. Considering the higher calorific value, this amount would mean a contribution of around 2.5% energy in these cities.
Abstract: Bacterial Cellulose (BC) is a structural organic compound produced in the anaerobic process. This material can be a useful eco-friendly substitute for commercial textiles that are used in industries today. BC is easily and sustainably produced and has the capabilities to be used as a replacement in textiles. However, BC is extremely fragile when it completely dries. This research was conducted to improve the mechanical properties of the BC by reinforcing with an organic polymer and exfoliated graphite (EG). The BC films were grown over a period of weeks in a green tea and kombucha solution at 30 °C, then cleaned and added to an enhancing solution. The enhancing solutions were a mixture of 2.5 wt% polymer and 2.5 wt% latex solution, a 5 wt% polymer solution, a 0.20 wt% graphite solution and were each allowed to sit in a furnace for 48 h at 50 °C. Tensile test samples were prepared and tested until fracture at a strain rate of 8 mm/min. From the research with the addition of a 5 wt% polymer solution, the flexibility of the BC has significantly improved with the maximum strain significantly larger than that of the base sample. The addition of EG has also increased the modulus of elasticity of the BC by about 25%.
Abstract: In light of the repercussions of the 2008 global economic crisis, the response of the United Arab Emirates economy and growth, and the vast construction activities that are undergoing, there is a need to investigate the relationship between construction activities and the Gross Domestic Product (GDP). This study aims to investigate the causality relationship between the construction industry in the United Arab Emirates and the GDP of the country in the last decade. For that, this study will investigate the relationship between the growth of the GDP and the growth of construction activities and their value addition to the economy. To ascertain this relationship, Granger Causality method is used to identify the causality between the time-dependent series.
Abstract: In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.
Abstract: We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.