Search results for: commuter line vending machine

Authors: Mukul Anand

Abstract:

Quality oriented affordable shelter for all has always been the key issue in the housing sector of our country. Homelessness is the acute form of housing need. It is a paradox that in spite of innumerable government initiated programmes for affordable housing, certain section of society is still devoid of shelter. About nineteen million (18.78 million) households grapple with housing shortage in Urban India in 2012. In Indian scenario there is major mismatch between the people for whom the houses are being built and those who need them. The prime force faced by public authorities in facilitation of quality housing for all is high cost of construction. The present paper will comprehend executable techniques for dilution of cost factor in housing the homeless. The key actors responsible for delivery of cheap housing stock such as capacity building, resource optimization, innovative low cost building material and indigenous skeleton housing system will also be incorporated in developing these techniques. Time performance, which is an important angle of above actors, will also be explored so as to increase the effectiveness of low cost housing. Along with this best practices will be taken up as case studies where both conventional techniques of housing and innovative low cost housing techniques would be cited. Transportation consists of approximately 30% of total construction budget. Thus use of alternative local solutions depending upon the region would be covered so as to highlight major components of low cost housing. Government is laid back regarding base line information on use of innovative low cost method and technique of resource optimization. Therefore, the paper would be an attempt to bring to light simpler solutions for achieving low cost housing.

Keywords: construction, cost, housing, optimization, shelter

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Authors: K. P. K. S. Lahirushan, W. G. V. Gunasekara

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Main purpose of this study is to identifying the impact of government expenditure on economic growth in Asian Countries. Consequently, Fist, objective is to analyze whether government expenditure causes economic growth in Asian countries vice versa and then scrutinizing long-run equilibrium relationship exists between them. The study completely based on secondary data. The methodology being quantitative that includes econometrical techniques of cointegration, panel fixed effects model and granger causality in the context of panel data of Asian countries; Singapore, Malaysia, Thailand, South Korea, Japan, China, Sri Lanka, India and Bhutan with 44 observations in each country, totaling to 396 observations from 1970 to 2013. The model used is the random effects panel OLS model. As with the above methodology, the study found the fascinating outcome. At first, empirical findings exhibit a momentous positive impact of government expenditure on Gross Domestic Production in Asian region. Secondly, government expenditure and economic growth indicate a long-run relationship in Asian countries. In conclusion, there is a unidirectional causality from economic growth to government expenditure and government expenditure to economic growth in Asian countries. Hence the study is validated that it is in line with the Keynesian theory and Wagner’s law as well. Consequently, it can be concluded that role of government would play a vital role in economic growth of Asian Countries .However; if government expenditure did not figure out with the economy’s needs it might be considerably inspiration the economy in a negative way so that society bears the costs.

Keywords: Asian countries, government expenditure, Keynesian theory, Wagner’s theory, random effects panel ols model

Procedia PDF Downloads 341

Authors: Bahareh Montakhabi

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Earthquake is known as one of the deadliest natural disasters, with a high potential for damage to life and property. Some of Iran's cities were completely destroyed after major earthquakes, and the people of the region suffered a lot of mental, financial and psychological damage. Tehran is one of the cities located on the fault line. According to experts, the only city that could be severely damaged by a moderate earthquake in Earthquake Engineering Intensity Scale (EEIS) (70% destruction) is Tehran because Tehran is built precisely on the fault. Seismic risk assessment (SRA) of cities in the scale of urban areas and neighborhoods is the first phase of the earthquake crisis management process, which can provide the information required to make optimal use of available resources and facilities in order to reduce the destructive effects and consequences of an earthquake. This study has investigated strategies to promote safety and reduce the vulnerability of worn-out urban textures in the District 12 of Tehran to the potential risk of earthquake aimed at prioritizing the factors affecting the vulnerability of worn-out urban textures to earthquake crises and how to reduce them, using the analytical-exploratory method, analytical hierarchy process (AHP), Expert choice and SWOT technique. The results of SWAT and AHP analysis of the vulnerability of the worn-out textures of District 12 to internal threats (1.70) and external threats (2.40) indicate weak safety of the textures of District 12 regarding internal and external factors and a high possibility of damage.

Keywords: risk management, vulnerability, worn-out textures, earthquake

Procedia PDF Downloads 187

Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

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Authors: Raju Ranjha, Surbhi Aggarwal

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Background: Inflammation plays an important role in infectious and non-infectious diseases. MiRNA is also reported to play role in inflammation and associated cancers. Chemokine CXCL12 is also known to play role in inflammation and various cancers. CXCL12/CXCR4 chemokine axis was involved in pathogenesis of IBD specially UC. Supplementation of CXCL12 induces homing of dendritic cells to spleen and enhances control of plasmodium parasite in BALB/c mice. We looked at the regulation of CXCL12β by miRNA in UC colitis. Prolonged inflammation of colon in UC patient increases the risk of developing colorectal cancer. We looked at the expression differences of CXCl12β and its targeting miRNA in cancer susceptible area of colon of UC patients. Aim: Aim of this study was to find out the expression regulation of CXCL12β by miRNA in inflammation. Materials and Methods: Biopsy samples and blood samples were collected from UC patients and non-IBD controls. mRNA expression was analyzed using microarray and real-time PCR. CXCL12β targeting miRNA were looked by using online target prediction tools. Expression of CXCL12β in blood samples and cell line supernatant was analyzed using ELISA. miRNA target was validated using dual luciferase assay. Results and conclusion: We found miR-200a regulate the expression of CXCL12β in UC. Expression of CXCL12β was increased in cancer susceptible part of colon and expression of its targeting miRNA was decreased in the same part of colon. miR-200a regulate CXCL12β expression in inflammation and may be an important therapeutic target in inflammation associated cancer.

Keywords: inflammation, miRNA, regulation, CXCL12

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Authors: Lamis Naddaf, Yuval Tabach

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In this research, we identified the missense genetic variants that have the potential to enhance resistance against cancer. Such field has not been widely explored, as researchers tend to investigate mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution, and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and can have significant implications on improved risk estimation, diagnostics, prognosis and even for personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and picked up the alleles that showed a correlation with the species’ cancer resistance. We predicted 250 protecting variants (PVs) with a 0.01 false discovery rate and more than 20 thousand PVs with a 0.25 false discovery rate. Cancer resistance in Mammals and reptiles was significantly predicted by the number of PVs a species has. Moreover, Genes enriched with the protecting variants are enriched in pathways relevant to tumor suppression like pathways of Hedgehog signaling and silencing, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are more abundant in healthy people compared to cancer patients within different human races.

Keywords: comparative genomics, machine learning, cancer resistance, cancer-protecting alleles

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Authors: Carolin Lutz, Jörg Matthes, Patrick Waibel, Ulrich Precht, Krassimir Garbev, Günter Beuchle, Uwe Schweike, Peter Stemmermann, Hubert B. Keller

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Online measurement of the product quality is a challenging task in cement production, especially in the production of Celitement, a novel environmentally friendly hydraulic binder. The mineralogy and chemical composition of clinker in ordinary Portland cement production is measured by X-ray diffraction (XRD) and X ray fluorescence (XRF), where only crystalline constituents can be detected. But only a small part of the Celitement components can be measured via XRD, because most constituents have an amorphous structure. This paper describes the development of algorithms suitable for an on-line monitoring of the final processing step of Celitement based on NIR-data. For calibration intermediate products were dried at different temperatures and ground for variable durations. The products were analyzed using XRD and thermogravimetric analyses together with NIR-spectroscopy to investigate the dependency between the drying and the milling processes on one and the NIR-signal on the other side. As a result, different characteristic parameters have been defined. A short overview of the Celitement process and the challenging tasks of the online measurement and evaluation of the product quality will be presented. Subsequently, methods for systematic development of near-infrared calibration models and the determination of the final calibration model will be introduced. The application of the model on experimental data illustrates that NIR-spectroscopy allows for a quick and sufficiently exact determination of crucial process parameters.

Keywords: calibration model, celitement, cementitious material, NIR spectroscopy

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Authors: Shota Nagata, Kazuya Okubo, Toru Fujii

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The purpose of this study is to investigate the proper condition in extracting carbon fibers as the reinforcement of composite molded by injection method. Recycled carbon fibers were extracted from wasted CFRP by pyrolyzing epoxy matrix of CFRP under air atmosphere at different temperature conditions 400, 600 and 800°C in this study. Recycled carbon fiber reinforced polypropylene (RCF/PP) pellets were prepared using twin screw extruder. The RCF/PP specimens were molded into dumbbell shaped specimens using injection molding machine. The tensile strength of recycled carbon fiber was decreased with rising pyrolysis temperature from 400 to 800°C. However, superior mechanical properties of tensile strength, tensile modulus and fracture strain of RCF/PP specimen were obtained when the extracting temperature was 600°C. Almost fibers in RCF/PP specimens were aligned in the mold filling direction in this study when the extracting temperature was 600°C. To discuss the results, the failure mechanisms of RCF/PP specimens was shown schematically. Finally, it was concluded that the temperature condition at 600°C should be selected in extracting carbon fibers as the reinforcement of RCF/PP composite molded by injection method.

Keywords: CFRP, recycled carbon fiber, injection molding, mechanical properties, fiber orientation, failure mechanism

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Authors: Abderrahmane Kechich, Othmane Abdelkhalek

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Static converters behave as nonlinear loads that inject harmonic currents into the grid and increase the consumption of the inactive power. On the other hand, the increased use of sensitive equipment requires the application of sinusoidal voltages. As a result, the electrical power quality control has become a major concern in the field of power electronics. In this context, the active power conditioner (UPQC) was developed. It combines both serial and parallel structures; the series filter can protect sensitive loads and compensate for voltage disturbances such as voltage harmonics, voltage dips or flicker when the shunt filter compensates for current disturbances such as current harmonics, reactive currents and imbalance. This double feature is that it is one of the most appropriate devices. Calculating parameters is an important step and in the same time it’s not easy for that reason several researchers based on trial and error method for calculating parameters but this method is not easy for beginners researchers especially what about the controller’s parameters, for that reason this paper gives a mathematical way to calculate of almost all of UPQC parameters away from trial and error method. This paper gives also a new approach for calculating of PI regulators parameters for purpose to have a stable UPQC able to compensate for disturbances acting on the waveform of line voltage and load current in order to improve the electrical power quality.

Keywords: UPQC, Shunt active filer, series active filer, PI controller, PWM control, dual-loop control

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Authors: Justin Tang

Abstract:

Balance tests are frequently used to diagnose concussions on the sidelines of sporting events. Manual scoring, however, is labor intensive and subjective, and many concussions go undetected. This study institutes a novel approach to conducting the Balance Error Scoring System (BESS) more quantitatively using Microsoft’s gaming system Kinect, which uses a contactless sensor and several cameras to receive data and estimate body limb positions. Using a machine learning approach, Visual Gesture Builder, and a deterministic approach, MATLAB, we tested whether the Kinect can differentiate between “correct” and erroneous stances of the BESS. We created the two separate solutions by recording test videos to teach the Kinect correct stances and by developing a code using Java. Twenty-two subjects were asked to perform a series of BESS tests while the Kinect was collecting data. The Kinect recorded the subjects and mapped key joints onto their bodies to obtain angles and measurements that are interpreted by the software. Through VGB and MATLAB, the videos are analyzed to enumerate the number of errors committed during testing. The resulting statistics demonstrate a high correlation between manual scoring and the Kinect approaches, indicating the viability of the use of remote tracking devices in conducting concussion tests.

Keywords: automated, concussion detection, contactless sensors, microsoft kinect

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: U. Achutha Kini, S. S. Sharma, K. Jagannath, P. R. Prabhu, M. C. Gowri Shankar

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Aluminium matrix composites with alumina reinforcements give superior mechanical & physical properties. Their applications in several fields like automobile, aerospace, defense, sports, electronics, bio-medical and other industrial purposes are becoming essential for the last several decades. In the present work, fabrication of hybrid composite was done by Stir casting technique using Al 6061 as a matrix with alumina and silicon carbide (SiC) as reinforcement materials. The weight percentage of alumina is varied from 2 to 4% and the silicon carbide weight percentage is maintained constant at 2%. Hardness and wear tests are performed in the as cast and heat treated conditions. Age hardening treatment was performed on the specimen with solutionizing at 550°C, aging at two temperatures (150 and 200°C) for different time durations. Hardness distribution curves are drawn and peak hardness values are recorded. Hardness increase was very sensitive with respect to the decrease in aging temperature. There was an improvement in wear resistance of the peak aged material when aged at lower temperature. Also increase in weight percent of alumina, increases wear resistance at lower temperature but opposite behavior was seen when aged at higher temperature.

Keywords: hybrid composite, hardness test, wear test, heat treatment, pin on disc wear testing machine

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Authors: Essam Mansour

Abstract:

The key purpose of this study is to show information-seeking behaviour of Kuwaiti Judges (KJs). Being one of the few studies about the information needs and information-seeking behaviour conducted in Arab and developing countries, this study is a pioneer one among many studies conducted in information seeking, especially with this significant group of information users. The authors tried to investigate this seeking behavior in terms of KJs' thoughts, perceptions, motivations, techniques, preferences, tools and barriers met when seeking information. The authors employed a questionnaire, with a response rate 77.2 percent. This study showed that most of KJs were likely to be older, educated and with a work experience ranged from new to old experience. There is a statistically reliable significant difference between KJs' demographic characteristics and some sources of information, such as books, encyclopedias, references and mass media. KJs were using information moderately to make a decision, to be in line with current events, to collect statistics and to make a specific/general research. The office and home were the most frequent location KJs were accessing information from. KJs' efficiency level of the English language is described to be moderately good, and a little number of them confirmed that their efficiency level of French was not bad. The assistance provided by colleagues, followed by consultants, translators, sectaries and librarians were found to be most strong types of assistance needed when seeking information. Mobile apps, followed by PCs, information networks (the Internet) and information databases were the highest technology tool used by KJs. Printed materials, followed by non-printed and audiovisual materials were the most preferred information formats KJs use. The use of languages, the recency of information and the place of information, the deficit role of the library to deliver information were at least significant barriers to KJs when seeking information.

Keywords: information users, information-seeking behaviour, information needs, judges, Kuwait

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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Authors: Ahmet Taşan, Süha Tirkeş, Yavuz Öztürk, Zafer Bingül

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Friction stir welding (FSW) is a joining process in the solid state, which eliminates problems associated with the material melting and solidification, such as cracks, residual stresses and distortions generated during conventional welding. Among the most important advantages of FSW are; easy automation, less distortion, lower residual stress and good mechanical properties in the joining region. FSW is a recent approach to metal joining and although originally intended for aluminum alloys, it is investigated in a variety of metallic materials. The basic concept of FSW is a rotating tool, made of non-consumable material, specially designed with a geometry consisting of a pin and a recess (shoulder). This tool is inserted as spinning on its axis at the adjoining edges of two sheets or plates to be joined and then it travels along the joining path line. The tool rotation axis defines an angle of inclination with which the components to be welded. This angle is used for receiving the material to be processed at the tool base and to promote the gradual forge effect imposed by the shoulder during the passage of the tool. This prevents the material plastic flow at the tool lateral, ensuring weld closure on the back of the pin. In this study, two 4 mm Kevlar^® plates which were produced with the Kevlar^® fabrics, are analyzed with COMSOL Multiphysics in order to investigate the weldability via FSW. Thereafter, some experimental investigation is done with an appropriate workbench in order to compare them with the analysis results.

Keywords: analytical modeling, composite materials welding, friction stir welding, heat generation

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Authors: Begüm Terzi, Özlem Ateş Sönmezoğlu, Ahmet Yildirim

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Drought is the most important factor that limiting the production and productivity of wheat in the world. The yield of wheat, which is one of the most important crop in the world, reduced depend on drought. Researches to minimize effects of drought are one of the most important about breeding of drought resistant varieties. In recent years, benefiting from the drought resistance wild species and rapid advances in molecular biology studies, researches about drought have been accelerated and number of studies were made on molecular plant breeding which included the molecular mechanisms related to drought resistance. The aim of the present study was characterization of some bread wheat lines for drought tolerance which commonly cultivated in different location of Turkey. In this study, registered 9 bread wheat varieties which on the physiological tests about drought tolerance and 10 bread wheat line has been developed by Transitional Zone Agricultural Research Institute were used. SSR, STS, RAPD and SNP markers that associated with drought tolerance were used. The polymorphisms of the markers were determined by screening of two control varieties. For these purpose 40 molecular markers were used and 12 markers of them were polymorphic among the drought tolerance and the drought sensitive varieties. Control varieties were screened using polymorphic markers. All the DNAs on the genotypes will be searched for the presence of QTLs mapped to different chromosomes. Result of the research, the studied genotypes will be grouped according to drought tolerance and will be detected drought tolerance varieties by molecular markers. In addition, the results will be compared also with physiological tests. The drought tolerant wheat genotypes may be used in breeding studies related to drought stress.

Keywords: bread wheat, drought, molecular marker, Triticum aestivum

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Authors: Young Kwon Yang, Bo Rang Park, Hyo Eun Lee, Tea Won Kim, Eun Ji Choi, Jin Chul Park

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To develop an artificial intelligence based automatic ventilation system, recent research trends were analyzed and analyzed. This research method is as follows. In the field of architecture and window technology, the use of artificial intelligence, the existing study of machine learning model and the theoretical review of the literature were carried out. This paper collected journals such as Journal of Energy and Buildings, Journal of Renewable and Sustainable Energy Reviews, and articles published on Web-sites. The following keywords were searched for articles from 2000 to 2016. We searched for the above keywords mainly in the title, keyword, and abstract. As a result, the global artificial intelligence market is expected to grow at a CAGR of 14.0% from USD127bn in 2015 to USD165bn in 2017. Start-up investments in artificial intelligence increased from the US $ 45 million in 2010 to the US $ 310 million in 2015, and the number of investments increased from 6 to 54. Although AI is making efforts to advance to advanced countries, the level of technology is still in its infant stage. Especially in the field of architecture, artificial intelligence (AI) is very rare. Based on the data of this study, it is expected that the application of artificial intelligence and the application of architectural field will be revitalized through the activation of artificial intelligence in the field of architecture and window.

Keywords: artificial intelligence, window, fine dust, thermal comfort, ventilation system

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Authors: Ibrahim S. Seddiek, Nader R. Ammar

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One of the most important equipment that affects the performance of passenger ships is the air conditioning system, which in turn consumes considerable electric loads. In this paper, the waste heat energies of exhaust gases and jacket cooling water of marine diesel engines for these ships are analyzed to be used as heat sources for absorption refrigeration unit (ARU). Economic and environmental analysis of the absorption refrigeration cycle operated with the two heat sources that use lithium bromide as absorbent is carried out. In addition, environmental and economic analysis for the absorption cycle is performed. As a case study, high-speed passenger vessel operating in the Red Sea area has been investigated. The results show that a considerable specific economic benefit could be achieved in case of applying absorption air condition that operates by water cooling system over that operates by main engine exhaust gases. Environmentally, applying ARU machine during cruise will reduce total ship’s fuel consumption by about 104 ton per year. This will result in reducing NOₓ, SOₓ, and CO₂ emissions with cost-effectiveness of 6.99 $/kg, 18.44 $/kg, and 0.117 $/kg, respectively.

Keywords: ship emissions, IMO, lithium bromide-water ARU, analysis, thermodynamic, economic and environmental analysis

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Authors: Nazife Duygu Bagci

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Collocations are an important part of vocabulary knowledge, and it is a subject that has recently attracted attention, while still in need of more research. The aim of this study is to answer three research questions related to the collocational knowledge of Turkish university level EFL learners at different proficiency levels of English. The first research question aims to compare the pre-intermediate (PIN) and the advanced (ADV) level learners’ collocational knowledge at receptive and productive levels. The second one is to analyze the performance of the PIN and the ADV students in two main collocation categories; lexical and grammatical. Lastly, the performance of both groups are focused on to find the collocation type (among verb-noun, adjective- noun, adjective-preposition, noun-preposition collocation types) they show the best performance in. Two offline tests were used to answer these questions. The results show that there is a significant difference between the PIN and the ADV groups at both receptive and productive levels. It can be concluded that proficiency is an important criterion in collocational knowledge, and learners do not necessarily know the collocates of the vocabulary items that they know. Although there is no significant difference between the PIN group’s performance in lexical and grammatical collocations, the ADV group showed a better performance in lexical collocations. Lastly, the PIN group at receptive and the ADV group at both receptive and productive levels showed the best performance in verb-noun collocations, which is in line with the previous research focusing on different collocation types.

Keywords: collocational knowledge, EFL, language proficiency, testing

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Authors: Habson Batubara, Patawari, Lisa Mery, Mohammad Syaichuddin, Sitti Faridah, Hamzah, Akmal, Abdul Gafur, Iman Sudrajad, Lideman, Yuani Mundaya, Kamaruddin, Muslimin, Herlina Jompa, Joula Sondack, Nani Undap, Suciati, Elisa Winanda, Arfandi Amin, Suciati

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This study aims to determine the status of the law, legislation, and its implementation against Foreign Nationals (WNA) Illegal Fishing Business Actors in the waters of the Indonesian Exclusive Economic Zone (EEZ), based on the Indonesian Positive Law and UNCLOS 1982. The research method used is normative juridical with a qualitative approach to study the Fisheries Criminal Verdict (Tipikan) and the Bitung District Court / Fisheries SIPP from 2019 to 2020. The results showed that cases of Illegal Fishing by Foreign Nationals (WNA) in the Indonesian Exclusive Economic Zone (EEZ) were examined, tried, and decided in accordance with the fisheries law, criminal sanctions were not in accordance with and contrary to Indonesian positive law, both criminal law and fisheries law, but followed and were in line with UNCLOS Year 1982. Legal status and responsibility are only imposed on the master as the leader on board the ship as the representative of the ship owner/company. Meanwhile, the application of Indonesia's positive law to Unclos in 1982 was only in the form of fines and confiscation of evidence as an effort to seek compensation for illegal fishing activities in the waters of the Indonesian Exclusive Zone (EEZ).

Keywords: EEZ, illegal fishing, WNA, positive law, Unclos 1982

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Authors: Suraj Nair, Aravindkumar Vijayalingam, Alexander Perzylo, Alois Knoll

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In the last decade robotics research and development activities have grown rapidly, especially in the domain of service robotics. Integrating service robots into human occupied spaces such as homes, offices, hospitals, etc. has become increasingly worked upon. The primary motive is to ease daily lives of humans by taking over some of the household/office chores. However, several challenges remain in systematically integrating such systems in human shared work-spaces. In addition to sensing and indoor-navigation challenges, programmability of such systems is a major hurdle due to the fact that the potential user cannot be expected to have knowledge in robotics or similar mechatronic systems. In this paper, we propose a cognitive system for service robotics which allows non-expert users to easily model system behaviour in an underspecified manner through abstract tasks and objects associated with them. The system uses domain knowledge expressed in the form of an ontology along with logical reasoning mechanisms to infer all the missing pieces of information required for executing the tasks. Furthermore, the system is also capable of recovering from failed tasks arising due to on-line disturbances by using the knowledge base and inferring alternate methods to execute the same tasks. The system is demonstrated through a coffee fetching scenario in an office environment using a mobile robot equipped with sensors and software capabilities for autonomous navigation and human-interaction through natural language.

Keywords: cognitive robotics, reasoning, service robotics, task based systems

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

Abstract:

The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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Authors: Akinyemi Tomiwa

Abstract:

The microstructure of rainfall is important for predicting and modeling various environmental processes, such as rainfall interception by vegetation, soil erosion, and radar signals in rainfall. This rain microstructure was studied with a vertically pointing Micro Rain Radar (MRR) located at a tropical location in Akure South West Nigeria (7o 15’ N, 5o 15’ E). This research utilizes two years of data (2018 and 2019), and the data obtained comprises rainfall parameters such as Rain rates, radar reflectivity, liquid water content, fall velocity and Drop Size Distribution (DSD) based on vertical profiles. The measurement and variations of rain microstructure of these parameters with heights for different rain types were presented from ground level up to the height of 4800 m at 160 m range gates. It has been found that the convective, stratiform and mixed, which are the three major rain types, have different rain microstructures at different heights and were evaluated in this research. The correlation coefficient and the regression line equation were computed for each rain event. The highest rain rate and liquid water content were observed within the height range of 160-4800. It was found that a good correlation exists between the measured parameters. Hence it shows that specific liquid water content increases with increasing rain rate for both stratiform and convective rain types in this part of the world. The results can be very useful for a better understanding of rain structure over tropical regions.

Keywords: rain microstructure, drop size distribution, rain rates, stratiform, convective.

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Authors: Zhen Li, Chang Liu, Ping Zhang

Abstract:

These Glaciers are thought of as natural water reservoirs and are of vital importance to hydrological models and industrial production, and glacial changes act as significant indicators of climate change. The glacier snowline can be used as an indicator of the equilibrium line, which may be a key parameter to study the effect of climate change on glaciers. Using Google Earth Engine, we select optical satellite imageries and implement the Otsu thresholding method on a near-infrared band to detect snowline altitudes (SLAs) of 26 glaciers in three regions of the eastern Tibetan Plateau. Three different study regions in the eastern Tibetan Plateau have different climate regimes, which are Sepu Kangri (SK, maritime glacier), Bu’Gyai Kangri (BK, continental glacier) and west of Qiajajima (WQ, continental glacier), along a latitudinal transect from south to north. We analyzed the effects of climatic factors on the SLA changes from 1995 to 2016. SLAs are fluctuating upward, and the rising values are 100 m, 60 m, and 34 m from south to north during the 22 years. We also observed that the climatic factor that affects the variability of SLA gradually changes from precipitation to temperature from south to north. The northern continental glaciers are mainly affected by temperature, and the southern maritime glaciers affected by precipitation. Owing to the influence of primary climatic factors, continental glaciers are found to have higher SLAs on the south slope, while maritime glaciers have higher SLAs on the north slope.

Keywords: climate change, glacier, snowline altitude, tibetan plateau

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Authors: Zahra Hamedani

Abstract:

Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

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Authors: Lucky Dartsa Wakawa, Friday Nwabueze Ogana, Temitope Elizabeth Adeniyi

Abstract:

Timely and reliable information on the status of a forest is essential for assessing the extent of regeneration and degradation. However, when such information is lacking effective forest management practices becomes impossible. Therefore, this study assessed the tree species composition, richness, diversity, structure of Oluwa forest reserve with the view of ascertaining it conservation status. A systematic line transect was used in the laying of eight (8) temporary sample plots (TSPs) of size 50m x 50m. Trees with Dbh ≥ 10cm in the selected plots were enumerated, identified and measured. The results indicate that 535 individual trees were enumerated cutting across 26 families and 58 species. The family Sterculiaceae recorded the highest number of species (10) and occurrence (112) representing 17.2% and 20.93% respectively. Celtis zenkeri is the species with the highest number of occurrence of tree per hectare and importance value index (IVI) of 59 and 53.81 respectively. The reserve has the Margalef's index of species richness, Shannon-Weiner diversity Index (H') and Pielou's Species Evenness Index (EH) of 9.07, 3.43 and 0.84 respectively. The forest has a mean Dbh (cm), mean height (m), total basal area/ha (m2) and total volume/ha (m3) of 24.7, 16.9, 36.63 and 602.09 respectively. The important tropical tree species identified includes Diospyros crassiflora Milicia excels, Mansonia altisima, Triplochiton scleroxylon. Despite the level of exploitation in the forest, the forest seems to be resilience. Given the right attention, it could regenerate and replenish to save some of the original species composition of the reserve.

Keywords: forest conservation, forest structure, Lowland tropical forest, South-west Nigeria

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Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

Abstract:

The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

Abstract:

Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Daphine Namara, Jeremy I. Schwartz, Andrew K. Tusubira, Willi McFarland, Caroline Birungi, Fred C. Semitala, Martin Muddu

Abstract:

Emerging evidence suggests a possible association between hyperglycemia and dolutegravir (DTG), a preferred first-line antiretroviral agent in sub-Saharan Africa (SSA). There is a need for rigorous studies to validate this association in the face of increasing DTG use and the burden of non-communicable diseases among people living with HIV (PLHIV). We conducted a case-control study to assess the risk of hyperglycemia associated with the use of DTG among PLHIV attending Mulago ISS Clinic in Kampala. Cases had hyperglycemia, while controls had no hyperglycemia, as confirmed by fasting plasma glucose and oral glucose tolerance tests. Demographic, laboratory, and clinical data were collected using interviewer-administered questionnaires and medical record abstraction. The analysis compared cases and controls on DTG use prior to diagnosis of hyperglycemia while controlling for potential confounders using multivariable logistic regression. We included 204 cases and 231 controls. In multivariable analysis, patients with prior DTG use had seven times greater odds of subsequent diagnosis of hyperglycemia compared to those who had non-DTG-based regimens (adjusted odds ratio [aOR] 7.01, 95% CI 1.96-25.09). The odds of hyperglycemia also increased with age (56 years and above vs. 18-35, aOR 12.38, 95% CI 3.79-40.50) and hypertension (aOR 5.78, 95% CI 2.53-13.21). Our study demonstrates a strong association between prior DTG exposure and subsequent diagnosis of hyperglycemia. Given the benefits of DTG, wide-scale use, and the growing burden of diabetes mellitus (DM) in SSA, there is a need for systematic screening for hyperglycemia and consideration of alternate regimens for those at risk for DM.

Keywords: HIV, hyperglycemia, doluteravir, diabetes

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