Search results for: network screening

Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

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In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: Muhammad Aown Sammar Raza

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Environmental stresses are one of the major reasons for poor crop yield across the globe. Among the various environmental stresses, drought stress is the most damaging one, especially in arid and semi-arid regions. Wheat is the major staple food of many countries of the world, which is badly affected by drought stress. In order to fulfill the dietary needs of increasing population with depleting water resources there is a need to adopt technologies which result in sufficient crop yield with less water consumption. One of them is partial root zone drying. Keeping in view these conditions, a wire house experiment was conducted at agronomic research area of University College of Agriculture and Environmental Sciences, The Islamia University Bahawalpur during 2015, to screen out the different wheat varieties for partial root zone drying (PRD). Five approved local wheat varieties (V1= Galaxy-2013, V2= Punjab-2011, V3 = Faisalabad-2008, V4 = Lasani-2008 and V5 = V.8200) and two irrigation levels (I1= control irrigation and I2 = PRD irrigation) with completely randomized design having four replications were used in the experiment. Among the varieties, Galaxy-2013 performed the best and attained maximum plant height, leaf area, stomatal conductance, photosynthesis, total sugars, proline contents and antioxidant enzymes activities and minimum values of growth and physiological parameters were recorded in variety V.8200. For irrigation levels, higher values of growth, physiological and water related parameters were recorded in control treatment (I1) except leaf water potential, osmotic potential, total sugars and proline contents. However, enzyme activities were higher under PRD treatment for all varieties. It was concluded that Galaxy-2013 is the most compatible and V.8200 is the most susceptible variety for PRD, respectively and more quality traits and enzymatic activities were recorded under PRD irrigation as compared to control treatment.

Keywords: antioxidant enzymes activities, osmolytes concentration, partial root zone drying, photosynthetic rate, water relations, wheat

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Authors: Asma Rashid, Shazia Iram, Iftikhar Ahmad

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Mango sudden death is an emerging problem in Pakistan. As its prevalence is observed in almost all mango growing areas and severity varied from 2-5% in Punjab and 5-10% in Sindh. Symptoms on affected trees include bark splitting, discoloration of the vascular tissue, wilting, gummosis and at the end rapid death. Total of n= 45 isolates were isolated from different mango growing areas of Punjab and Sindh. Pathogenicity of these fungal isolates was tested through artificial inoculation method on different hosts (potato tubers, detached mango leaves, detached mango twigs and mango plants) under controlled conditions and all were proved pathogenic with varying degree of aggressiveness in reference to control. The findings of the present study proved that out of these four methods, potato tubers inoculation method was the most ideal as this fix the inoculums on the target site. Increased fungal growth and spore numbers may be due to soft tissues of potato tubers from which Ceratocystis isolates can easily pass. Lesion area on potato tubers was in the range of 7.09-0.14 cm2 followed by detached mango twigs which were ranged from 0.48-0.09 cm2). All pathological results were proved highly significant at P<0.05 through ANOVA but isolate to isolate showed non-significant behaviour but they have the positive effect on lesion area. Re-isolation of respective fungi was achieved with 100 percent success which results in the verification of Koch’s postulates. DNA of fungal pathogens was successfully extracted through phenol chloroform method. Amplification was done through ITS, b-tubulin gene, and Transcription Elongation Factor (EF1-a) gene primers and the amplified amplicons were sequenced and compared from NCBI which showed 99-100 % similarity with Ceratocystis manginecans. Fungus Ceratocystis manginecans formed one of strongly supported sub-clades through phylogenetic tree. Results obtained through this work would be supportive in establishment of relation of isolates with their region and will give information about pathogenicity level of isolates that would be useful to develop the management policies to reduce the afflictions in orchards caused by mango sudden death.

Keywords: artificial inoculation, mango, Ceratocystis manginecans, phylogenetic, screening

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Authors: Ali Ocholi

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The study was conducted to analyze the impact of agro-allied industries on rural dwellers in Benue state, Nigeria. Stratified random sampling technique was used to select the respondents for the study. Primary data were collected through the use of structured questionnaires administered on 366 respondents from the selected communities; the data were analyzed using both descriptive and inferential statistics. The result of Mann-Whitney (U) statistics showed that water availability (14350) and good road network (15082.00) were the only social impact derived from the industries by the rural dwellers. The study recommended that right and proper policies and programmes should be put in place by the government to mandate all private and public agro-allied industries to embark on projects that would be in favour of the rural dwellers where the agro-allied industries are situated.

Keywords: agriculture, agro-allied industry, rural dwellers, Benue state

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Authors: Mohadese Motahari

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In general, we consider the phenomenon of "fandism" or extreme fandom to be an aspect of fandom for a person, a group, or a collection, which leads to extreme support for them. So, for example, we consider a fan or a "fanatic" (which literally means a "fanatical person") to be a person who is extremely interested in a certain topic or topics and has a special passion and fascination for that issue. It may also be beyond the scope of logic and normal behavior of the society. With the expansion of the media and the advancement of technology, the phenomenon of fandom also underwent many changes and not only became more intense, but a large economy was also formed alongside it, and it is becoming more and more important every day. This economy, which emerged from the past with the formation of the first media, has now taken a different form with the development of media and social networks, as well as the change in the interaction between celebrities and audiences. Earning huge amounts of money with special methods in every social network and every media is achieved through fans and fandoms. In this article, we have studied the relationship between fans and famous people with reference to the economic debates surrounding it.

Keywords: fandism, famous people, social media, new media

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Authors: Chia-Chen Wu, Chih-Fu Wu, Pey-Weng Lien, Kai-Chieh Lin

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In the past, the most comprehensively adopted light source was incandescent light bulbs, but with the appearance of LED light sources, traditional light sources have been gradually replaced by LEDs because of its numerous superior characteristics. However, many of the standards do not apply to LEDs as the two light sources are characterized differently. This also intensifies the significance of studies on LEDs. As a Kansei design study investigating the visual glare produced by traffic arrows implemented with LEDs, this study conducted a semantic analysis on the styles of traffic arrows used in domestic and international occasions. The results will be able to reduce drivers’ misrecognition that results in the unsuccessful arrival at the destination, or in traffic accidents. This study started with a literature review and surveyed the status quo before conducting experiments that were divided in two parts. The first part involved a screening experiment of arrow samples, where cluster analysis was conducted to choose five representative samples of LED displays. The second part was a semantic experiment on the display of arrows using LEDs, where the five representative samples and the selected ten adjectives were incorporated. Analyzing the results with Quantification Theory Type I, it was found that among the composition of arrows, fletching was the most significant factor that influenced the adjectives. In contrast, a “no fletching” design was more abstract and vague. It lacked the ability to convey the intended message and might bear psychological negative connotation including “dangerous,” “forbidden,” and “unreliable.” The arrow design consisting of “> shaped fletching” was found to be more concrete and definite, showing positive connotation including “safe,” “cautious,” and “reliable.” When a stimulus was placed at a farther distance, the glare could be significantly reduced; moreover, the visual evaluation scores would be higher. On the contrary, if the fletching and the shaft had a similar proportion, looking at the stimuli caused higher evaluation at a closer distance. The above results will be able to be applied to the design of traffic arrows by conveying information definitely and rapidly. In addition, drivers’ safety could be enhanced by understanding the cause of glare and improving visual recognizability.

Keywords: LED, arrow, Kansei research, preferred imagery

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Authors: Kedwadee Sombultawee, Sakun Boon-Itt

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This research demonstrates a systematic literature review of 62 peer-reviewed articles published in academic journals from 2000-2016 focusing on the operation and marketing interface area. The findings show the three major clusters of recent research domains, which is a review of the alignment between operations and marketing, identification of variables that impact the company and analysis of the effect of interface. Moreover, the Main Path Analysis (MPA) is mapped to show the knowledge structure of the operation and marketing interface issue. Most of the empirical research focused on company performance and new product development then analyzed the data by the structural equation model or regression. Whereas, some scholars studied the conflict of these two functions and proposed the requirement or step for alignment. Finally, the gaps in the literature are provided for future research directions.

Keywords: operations management, marketing, interface, systematic literature review

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Yanchun Zuo, Yingao Liu, Wei Liu, Le Yu, Run Huang, Lixin Guo

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Electric field detection is important in many application scenarios. The traditional strategy is measuring the electric field with a man walking around in the area under test. This strategy cannot provide a satisfactory measurement accuracy. To solve the mentioned problem, an autopilot measurement system is divided. A mini-car is produced, which can travel in the area under test according to respect to the program within the CPU. The electric field measurement platform (EFMP) carries a central computer, two horn antennas, and a vector network analyzer. The mini-car stop at the sampling points according to the preset. When the car stops, the EFMP probes the electric field and stores data on the hard disk. After all the sampling points are traversed, an electric field map can be plotted. The proposed system can give an accurate field distribution description of the chamber.

Keywords: autopilot mini-car measurement system, electric field detection, field map, static zone measurement

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Authors: Syed Mamoon Siyar, Fayaz Ali, Sajjad Ahmad, Samina Jahandad, George Kontakiotis, Hammad T. Janjuhah, Assimina Antonarakou, Waqas Naseem

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The Cretaceous Chichali Formation in the Chanda-01, Chanda-02, Chanda-03 and Mela-05 wells and the oil samples from Chanda-01 and Chanda-01 wells located in the Kohat Basin, Pakistan, were analyzed with the objectives of evaluating the hydrocarbon generation potential, source, thermal maturity and depositional of organic matter, and oil-source correlation by employing geochemical screening techniques and biomarker studies. The total organic carbon (TOC) values in Chanda-02, Chanda-03 and Mela-05 indicate, in general, poor to fair, fair and fair to good source rock potential with low genetic potential, respectively. The nature of organic matter has been determined by standard cross plots of Rock Eval pyrolysis parameters, indicating that studied cuttings from the Chichali Formation dominantly contain type III kerogen at present and show maturity for oil generation in the studied wells. The organic petrographic study also confirmed the vitrinite (type III) as a major maceral in the investigated Chichali Shales and its reflectance values show maturity for oil. The different ratios of non-biomarkers and biomarkers i.e., steranes, terpenes and aromatics parameters, indicate the marine source of organic matter deposited in the anoxic environment for the Chichali Formation in Chanda-01 and Chanda-02 wells and mixed source input of organic matter deposited in suboxic conditions for oil in the same wells. The CPI, and different biomarkers parameters such as C29 S/S+R, ββ/αα+ββ), M29/H30, Ts/Ts+Tm, H31 (S/S+R) and aromatic compounds methyl phenanthrene index (MPI) and organic petrographic analysis (vitrinite reflectance) suggest mature stage of oil generation for Chichali Shales and oil samples in the study area with little high thermal maturity in case of oils. Based on source and thermal maturity biomarkers and non-biomarkers parameters, the produced oils have no correlation with the Cretaceous Chichali Formation in the studied Chanda-01 and Chanda-02 wells in Kohat Basin, Pakistan, but it has been suggested that these oils have been generated by the strata containing high terrestrial organic input compare to Chichali Shales.

Keywords: Organic geochemistry, Chichali Shales and crude oils, Kohat Basin, Pakistan

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Authors: Elmabruk Laias

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IEEE Standard 802.16 provides QoS (Quality of Service) for the applications such as Voice over IP, video streaming and high bandwidth file transfer. With the ability of broadband wireless access of an IEEE 802.16 system, a WiMAX TDD frame contains one downlink subframe and one uplink subframe. The capacity allocated to each subframe is a system parameter that should be determined based on the expected traffic conditions. a proper resource allocation scheme for packet transmissions is imperatively needed. In this paper, we present a new resource allocation scheme, called additional bandwidth yielding (ABY), to improve transmission efficiency of an IEEE 802.16-based network. Our proposed scheme can be adopted along with the existing scheduling algorithms and the multi-priority scheme without any change. The experimental results show that by using our ABY, the packet queuing delay could be significantly improved, especially for the service flows of higher-priority classes.

Keywords: IEEE 802.16, WiMAX, OFDMA, resource allocation, uplink-downlink mapping

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Authors: Melikhaya Skhephe, Robert Mawuli Kwasi Boadzo, Zanoxolo Berington Gobingca

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This research study sought to examine parental monitoring of learners’ cell phone use in the Eastern Cape, South Africa. To this end, the researchers employed a quantitative approach. Data were obtained through questionnaires, with a sample of 15 parents having been purposively selected. The findings revealed that parents are unaware that they have to monitor the learner’s cell phone. Another finding was that parents in the 21-century did not support the use of mobile phones in education. The researchers recommend that parent’s discussion forums be created to educate parents on how a cell phone can be used in education. Cellphone companies need to be encouraged to educate parents on how they monitor cell phones used by learners. Another recommendation was that network providers need to restrict access to searching on the internet according to age.

Keywords: parental monitoring, app blocking services, learner’s cell phone use, cell phone

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Authors: C. Hamamura, V. Gialluca

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Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

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Authors: Ismael Ávila, José Reynaldo F. Filho, Vasco Varanda Picchi

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The ever-growing consumer awareness of food provenance in Brazil is driving the creation of a trusted ecosystem around the animal protein supply chain. The traceability and accountability requirements of such an ecosystem demand a blockchain layer to strengthen the weak links in that chain. For that, direct involvement of the companies in the blockchain transactions, including as validator nodes of the network, implies formalizing a partnership with the consortium behind the ecosystem. Yet, their compliance standards usually require that a formal governance structure is in place before they agree with any membership terms. In light of such a strategic role of blockchain governance, the paper discusses a framework for tailoring a governance model for a blockchain-based solution aimed at the meat supply chain and evaluates principles and attributes in terms of their relevance to the development of a robust trust ecosystem.

Keywords: blockchain, governance, trust ecosystem, supply chain, traceability

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Authors: J. Waita, S. Wamuhu, J. Makoyo, M. Rachel, T. Ngangari, W. Christine, M. Zipporah

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Contraceptive use is one of the key global strategies to alleviate maternal mortality. Global efforts through advocating for contraceptive uptake and service provision has led improved contraceptive prevalence. In Kenya maternal mortality rate has remained a challenged despites efforts by government and non-governmental organizations. Objective: To describe the uptake of contraceptives among women in Tunza Clinics, Kenya. Design and Methods: Ps Kenya through health care marketing fund is implementing a family planning program among its 350 Tunza fractional franchise facilities. Through private partnership, private owned facilities in low socio-economic areas are recruited and trained on contraceptive technology update. The providers are supported through facilitative supervision through a mobile based application Health Network Quality Improvement System (HNQIS) and interpersonal communication through 150 community based volunteers. The data analyzed in this paper was collected between January to July 2017 to show the uptake of modern Contraceptives among women in the Tunza franchise, method mix, age and distribution among the age bracket. Further analysis compares two different service delivery strategies; outreach and walk ins. Supportive supervision HNQIS scores was analyzed. Results: During the time period, a total of 132121 family planning clients were attended in 350 facilities. The average age of clients was 29.6 years. The average number of clients attended in the facilities per month was 18874. 73.7 %( n=132121) of the clients attended in the Tunza facilities were aged above 25 years while 22.1% 20-24 years and 4.2% 15-19 years. On contraceptive method mix, intra uterine device insertions clients contributed to 7.5%, implant insertions 15.3%, pills 11.2%, injections 62.7% while condoms and emergency pills had 2.7% and 0.6% respectively. Analysis of service delivery strategy indicated more than 79% of the clients were walk ins while 21% were attended to during outreaches. Uptake of long term contraceptive methods during outreaches was 73% of the clients while short term modern methods were 27%. Health Network Quality Improvement system assessment scores indicated 51% of the facilities scored over 90%, 25% scoring 80-89% while 21% scored below 80%. Conclusion: Preference for short term methods by women is possibly associated to cost as they are cheaper and easy to administer. When the cost of intra uterine device Implants is meant affordable during outreaches, the uptake is observed to increase. Making intra uterine device and implants affordable to women is a key strategy in increasing contraceptive prevalence hence averting maternal mortality.

Keywords: contraceptives, contraceptive uptake, low socio economic, supportive supervision

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Authors: K. Senthil Kumar, A. Vasumalaikannan

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In this paper, teleoperation of the quadrotor using Internet with Force feedback is addressed. Teleoperation with Force feedback is the ability to remotely control a robot, where contact (obstacle) or environment (wind gust etc) information (force feedback) is communicated from the quadrotor to the master joystick and thus giving the operator a sense of telepresence. The stability and performance of such a teleoperator is highly dependent on the amount of time delay present in the control loop. This problem is further complicated given the fact that for network based communication the time delay is itself time varying and highly non deterministic. In this paper, a novel method using Neural based Smith Predictor at the master side the stability is achieved. The performance of the system even during worst case scenario is within acceptable.

Keywords: teleoperation, quadrotor, neural smith predictor, time delay

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Authors: T. Urushadze, R. Khvedelidze, L. Kutateladze, M. Jobava, T. Burduli, T. Alexidze

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There is an increasing interest in reliable, wasteless, ecologically friendly technologies. About 40% of enzymes produced all over the world are used for production of syrups with high concentration of glucose-fructose. One of such technologies complies obtaining fermentable sugar glucose from raw materials containing starch by means of amylases. In modern alcohol-producing factories this process is running in two steps, involving two enzymes of different origin: bacterial α-amylase and fungal glucoamylase, as generally fungal amylases are less thermostable as compared to bacterial amylases. Selection of stable and operable at 700С and higher temperatures enzyme preparation with both α- and glucoamylase activities will allow conducting this process in one step. S. Durmishidze Institute of Biochemistry and Biotechnology owns unique collection of mycelial fungi, isolated from different ecological niches of Caucasus. As a result of screening our collection 39 strains poducing amylases were revealed. Most of them belong to the genus Aspergillus. Optimum temperatures of action of selected amylases from three producers were estableshed to be within the range 67-80°C. A. niger B-6 showed higher α-amylase activity at 67°C, and glucoamylase activity at 62°C, A. niger 6-12 showed higher α-amylase activity at 72°C, and glucoamylase activity at 65°C, Aspergillus niger p8-3 showed higher activities at 82°C and 70°C, for α-amylase and glucoamylase activities, respectively. Exhaustive hydrolysis process of starch solutions of different concentrations (3, 5, 15, and 30 %) with cultural liquid and technical preparation of Aspergillus niger p8-3 enzyme was studied. In case of low concentrations exhaustive hydrolysis of starch lasts 40–60 minutes, in case of high concentrations hydrolysis takes longer time. 98, 6% yield of glucose can be reached at incubation during 12 hours with enzyme cultural liquid and 8 hours incubation with technical preparation of the enzyme at gradual increase of temperature from 50°C to 82°C during the first 20 minutes and further decrease of temperature to 70°C. Temperature setting for high yield of glucose and high hydrolysis (pasteurizing), optimal for activity of these strains is the prerequisite to be able to carry out hydrolysis of starch to glucose in one step, and consequently, using one strain, what will be economically justified.

Keywords: amylase, glucose hydrolisis, stability, starch

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Authors: Mehmet Hakan Karaata, Ali Hamdan, Omer Yusuf Adam Mohamed

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Consider a distributed system that delivers messages from a process to another. Such a system is often required to deliver each message to its destination regardless of whether or not the system components experience arbitrary forms of faults. In addition, each message received by the destination must be a message sent by a system process. In this paper, we first identify the necessary and sufficient conditions to detect some restricted form of Byzantine faults referred to as modifying Byzantine faults. An observable form of a Byzantine fault whose effect is limited to the modification of a message metadata or content, timing and omission faults, and message replay is referred to as a modifying Byzantine fault. We then present a distributed protocol to detect modifying Byzantine faults using optimal number of messages over node-disjoint paths.

Keywords: Byzantine faults, distributed systems, fault detection, network protocols, node-disjoint paths

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Authors: Andreas Hirseland, Lukas Kerschbaumer

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In Germany, during the past years there constantly are about one million long term unemployed who did not benefit from the prospering labor market while most short term unemployed did. Instead, they are continuously dependent on welfare and sometimes precarious short-term employment, experiencing work poverty. Long term unemployment thus turns into a main obstacle to regular employment, especially if accompanied by other impediments such as low level education (school/vocational), poor health (especially chronical illness), advanced age (older than fifty), immigrant status, motherhood or engagement in care for other relatives. Almost two thirds of all welfare recipients have multiple impediments which hinder a successful transition from welfare back to sustainable and sufficient employment. Hiring them is often considered as an investment too risky for employers. Therefore formal application schemes based on formal qualification certificates and vocational biographies might reduce employers’ risks but at the same time are not helpful for long-term unemployed and welfare recipients. The panel survey ‘Labor market and social security’ (PASS; ~15,000 respondents in ~10,000 households), carried out by the Institute of Employment Research (the research institute of the German Federal Labor Agency), shows that their chance to get back to work tends to fall to nil. Only 66 cases of such unlikely transitions could be observed. In a sequential explanatory mixed-method study, the very scarce ‘success stories’ of unlikely transitions from long term unemployment to work were explored by qualitative inquiry – in-depth interviews with a focus on biography accompanied by qualitative network techniques in order to get a more detailed insight of relevant actors involved in the processes which promote the transition from being a welfare recipient to work. There is strong evidence that sustainable transitions are influenced by biographical resources like habits of network use, a set of informal skills and particularly a resilient way of dealing with obstacles, combined with contextual factors rather than by job-placement procedures promoted by Job-Centers according to activation rules or by following formal paths of application. On the employer’s side small and medium-sized enterprises are often found to give job opportunities to a wider variety of applicants, often based on a slow but steadily increasing relationship leading to employment. According to these results it is possible to show and discuss some limitations of (German) activation policies targeting welfare dependency and long-term unemployment. Based on these findings, indications for more supportive small scale measures in the field of labor-market policies are suggested to help long-term unemployed with multiple impediments to overcome their situation.

Keywords: against-all-odds, economic sociology, long-term unemployment, mixed-methods

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Authors: Anubhav Shrivastava, Lakshya Bhat, Shivarudraswamy

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Distributed Generation is the need of the hour. With current advancements in the DG technology, there are some major issues that need to be tackled in order to make this method of generation of energy more efficient and feasible. Among other problems, the control in voltage is the major issue that needs to be addressed. This paper focuses on control of voltage using reactive power control of DGs with the help of fuzzy logic. The membership functions have been defined accordingly and the control of the system is achieved. Finally, with the help of simulation results in Matlab, the control of voltage within the tolerance limit set (+/- 5%) is achieved. The voltage waveform graphs for the IEEE 14 bus system are obtained by using simple algorithm with MATLAB and then with fuzzy logic for 14 bus system. The goal of this project was to control the voltage within limits by controlling the reactive power of the DG using fuzzy logic.

Keywords: distributed generation, fuzzy logic, matlab, newton raphson, IEEE 14 bus, voltage regulation, radial network

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Authors: Abdollah Kavousi Fard

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This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.

Keywords: microgrid, renewable energy sources, reconfiguration, optimization

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Authors: Praveen S. Muthukumarana, Achala C. Aponso

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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.

Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis

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Authors: Jean Gray C. Achapero, Mary Margareth P. Ancheta, Patricia Anjelika A. Angeles, Shannon Denzel S. Ao Tai, Carl Brandon C. Barlis, Chrislen Mae B. Benavidez

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Health literacy and awareness of Polycystic ovarian syndrome (PCOS) is a global issue that is under-addressed in the Philippines. Conducting a thorough review of the country's ability to recognize and comprehend the severity of the syndrome should be undertaken, as early treatment is essential to avoid further disorder complications. This research aims to assess the health literacy and awareness of the female residents of Barangay Dagatan, Sabang, and Marauoy Lipa, Batangas on PCOS. It followed a cross-sectional study, and data gathering was done through a pre-assessment using the Single Item Literacy Screener (SILS) and an online population-based survey questionnaire about PCOS awareness. The participants, as based on the objectives and purposive sampling method, were females aged 18-45 years old. Data were analyzed statistically using STATA 13.1 software. The study showed that 339 (76%) out of 444 respondents passed the SILS meaning the residents have proficient health literacy. Among the 339 respondents, 87% (287) had previous knowledge about PCOS. The respondents showed minimal awareness of PCOS symptoms which could be attributed to its broad spectrum of information. Respondents were shown to be most knowledgeable about PCOS physiology, treatment, beliefs, and its remedies. The respondents’ age had no significant association with their health literacy (p=0.31) and PCOS awareness (p=0.60). A significant association was noted, however, in their educational attainment linked with their health literacy (p=<0.0001) and PCOS awareness (p=0.001). It is suggested that reproductive health education even in the lower year levels must be optimized and Local Government Unit (LGU)/Non-Government Organization (NGO)-held seminars should be conducted for knowledge reinforcement. Reliable health information should be more accessible to the public and clinicians must emphasize the importance of the majority of early screening as part of routine physical examination for women of reproductive age to increase health literacy and awareness about PCOS and actively engage in the management of the disease.

Keywords: age, awareness, educational attainment, health literacy, polycystic ovarian syndrome

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Authors: Marko Jankovic, Aleksandra Knezevic, Maja Cupic, Dragana Vujic, Zeljko Zecevic, Borko Gobeljic, Marija Simic, Tanja Jovanovic

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The human cytomegalovirus (CMV) is a notorious pathogen in the pediatric transplant setting. Although studies on factors in complicity with CMV infection abound, the role of age, gender, allogeneic hematopoietic stem cell transplantation (alloHSCT) modality, and underlying disease as regards CMV infection and viral load in children are poorly explored. We examined the significance of various factors related to the risk of CMV infection and viral load in Serbian children and adolescents undergoing alloHSCT. This was a prospective single centre study of thirty two pediatric patients in receipt of alloHSCT for various malignant and non-malignant disorders. Screening for active viral infection was performed by regular weekly monitoring. The Real-Time PCR method was used for CMV DNA detection and quantitation. Statistical analysis was performed using the IBM SPSS Statistics v20 software. Chi-square test was used to evaluate categorical variables. Comparison between scalar and nominal data was done by Wilcoxon-Mann-Whitney test. Pearson correlation was applied for studying the association between patient age and viral load. CMV was detected in 23 (71.9%) patients. Infection occurred significantly more often (p=0.015) in patients with haploidentical donors. The opposite was noted for matched sibling grafts (p=0.006). The viral load was higher in females (p=0.041) and children in the aftermath of alloHSCT with malignant diseases (p=0.019). There was no significant relationship between the viral infection dynamics and overt medical consequences. This is the first study of risk factors for CMV infection in Serbian pediatric alloHSCT patients. Transplanted patients presented with a high incidence of CMV viremia. The HLA compatibility of donated graft is associated with the frequency of CMV positive events. Age, gender, underlying disease, and medically relevant events were not conducive to occurrences of viremia. Notably, substantial viral burdens were evidenced in females and patients with neoplastic diseases. Studies comprising larger populations are clearly needed to scrutinize current results.

Keywords: allogeneic hematopoietic stem cell transplantation, children, cytomegalovirus, risk factors, viral load

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Authors: Vijay Kr. Yadav, Nilam Rathi

Abstract:

Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

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Authors: Ayyaz Hussain, Tariq Sadad

Abstract:

Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

Procedia PDF Downloads 121

Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

Abstract:

Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Shaimaa Eltanani, Thangal Yumnamcha, Ahmed S. Ibrahim

Abstract:

Purpose: Mitochondria dysfunction is central to breaking the barrier integrity of retinal endothelial cells (RECs) in various blinding eye diseases such as diabetic retinopathy and retinopathy of prematurity. Therefore, we aimed to dissect the role of different mitochondrial components, specifically, those of oxidative phosphorylation (OxPhos), in maintaining the barrier function of RECs. Methods: Electric cell-substrate impedance sensing (ECIS) technology was used to assess in real-time the role of different mitochondrial components in the total impedance (Z) of human RECs (HRECs) and its components; the capacitance (C) and the total resistance (R). HRECs were treated with specific mitochondrial inhibitors that target different steps in OxPhos: Rotenone for complex I; Oligomycin for ATP synthase; and FCCP for uncoupling OxPhos. Furthermore, data were modeled to investigate the effects of these inhibitors on the three parameters that govern the total resistance of cells: cell-cell interactions (Rb), cell-matrix interactions (α), and cell membrane permeability (Cm). Results: Rotenone (1 µM) produced the greatest reduction in the Z, followed by FCCP (1 µM), whereas no reduction in the Z was observed after the treatment with Oligomycin (1 µM). Following this further, we deconvoluted the effect of these inhibitors on Rb, α, and Cm. Firstly, rotenone (1 µM) completely abolished the resistance contribution of Rb, as the Rb became zero immediately after the treatment. Secondly, FCCP (1 µM) eliminated the resistance contribution of Rb only after 2.5 hours and increased Cm without considerable effect on α. Lastly, Oligomycin had the lowest impact among these inhibitors on Rb, which became similar to the control group at the end of the experiment without noticeable effects on Cm or α. Conclusion: These results demonstrate differential roles for complex I, complex V, and coupling of OxPhos in maintaining the barrier functionality of HRECs, in which complex I being the most important component in regulating the barrier functionality and the spreading behavior of HRECs. Such differences can be used in investigating gene expression as well as for screening selective agents that improve the functionality of complex I to be used in the therapeutic approach for treating REC-related retinal diseases.

Keywords: human retinal endothelial cells (hrecs), rotenone, oligomycin, fccp, oxidative phosphorylation, oxphos, capacitance, impedance, ecis modeling, rb resistance, α resistance, and barrier integrity

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Authors: N. Meddeb, A. M. Makhlouf, M. A. Ben Ayed

Abstract:

Due to the real-time requirement of message in Vehicular Ad hoc NETworks (VANET), it is necessary to authenticate vehicles to achieve security, efficiency, and conditional privacy-preserving. Privacy is of utmost relevance in VANETs. For this reason, we have proposed a new protocol called ‘Multilevel Authentication Protocol’ (MAP) that considers different vehicle categories. The proposed protocol is based on our Multilevel Authentication protocol for Vehicular networks (MAVnet). But the MAP leads to human safety, where the priority is given to the ambulance vehicles. For evaluation, we used the Java language to develop a demo application and deployed it on the Network Security Simulation (Nessi2). Compared with existing authentication protocols, MAP markedly enhance the communication overhead and decreases the delay of exchanging messages while preserving conditional privacy.

Keywords: Vehicular Ad hoc NETworks (VANET), vehicle categories, safety, databases, privacy, authentication, throughput, delay

Procedia PDF Downloads 280

Authors: Ali Heydarimoghim

Abstract:

In this paper, the optimal placement of charging and discharging stations is done to determine the location and capacity of the stations, reducing the cost of electric vehicle owners' losses, reducing the cost of distribution system losses, and reducing the costs associated with the stations. Also, observing the permissible limits of the bus voltage and the capacity of the stations and their distance are considered as constraints of the problem. Given the traffic situation in different areas of a city, we estimate the amount of energy required to charge and the amount of energy provided to discharge electric vehicles in each area. We then introduce the electricity distribution system of the city in question. Following are the scenarios for introducing the problem and introducing the objective and constraint functions. Finally, the simulation results for different scenarios are compared.

Keywords: charging & discharging stations, hybrid vehicles, optimization, replacement

Procedia PDF Downloads 125