Search results for: institutional network

Authors: Kelaiaia Mounia Samira, Labar Hocine, Mesbah Tarek, Kelaiaia samia

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The photovoltaic panel produces green power, and because of its availability across the globe, it can supply isolated loads (site away of the electrical network or difficult of access). Unfortunately this energy remains very expensive. The most application of these types of power needs storage devices, the Lithium batteries are commonly used because of its powerful storage capability. Using a solar panel or an array of panels without a controller that can perform MPPT will often result in wasted power, which results in the need to install more panels for the same power requirement. For devices that have the battery connected directly to the panel, this will also result in premature battery failure or capacity loss. In this paper it is proposed a modified P&O algorithm for the MPPT which takes in account the battery’s internal resistance vs temperature and stage of charging. Of course the temperature variation and irradiation of the PV panel are also introduced.

Keywords: modeling, battery, MPPT, charging, PV Panel

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Authors: Sasan Talebnezhad, Parviz Hamidia

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GPC and RMS analysis showed no distinct difference between PE 100 On, Off, and Reference grade. But FTIR spectra and multiple endothermic peaks obtained from SSA analysis, attributed to heterogeneity of ethylene sequence length, lamellar thickness and also the non-uniformity of short chain branching, showed sharp discrepancy and proposed a blend structure of high-density polyethylenes in PE 100 grade. Catalysis along with process parameters dictates poly blend PE 100 structure. This in-reactor blend is a mixture of compatible co-crystallized phases with different crystalinity, forming a physical semi hard and soft segment network responsible for improved impact properties in PE 100 pipe grade. We propose a new approach for PE100 evaluation that is more efficient than normal microstructure characterization.

Keywords: HDPE, pipe grade, in-reactor blend, hard and soft segments

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Authors: C. P. Autry, A. W. Roscoe, Mykhailo Magal

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We discuss the theoretical model underlying 2BPA (two-band peer authentication), a practical alternative to conventional authentication of entities and data in IoT. In essence, this involves assembling a virtual map of authentication assets in the network, typically leading to many paths of confirmation between any pair of entities. This map is continuously updated, confirmed, and evaluated. The value of authentication along multiple disjoint paths becomes very clear, and we require analogues of triangulation to extend authentication along extended paths and deliver it along all possible paths. We discover that if an attacker wants to make an honest node falsely believe she has authenticated another, then the length of the authentication paths is of little importance. This is because optimal attack strategies correspond to minimal cuts in the authentication graph and do not contain multiple edges on the same path. The authentication provided by disjoint paths normally is additive (in entropy).

Keywords: authentication, edge computing, industrial IoT, post-quantum resistance

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Authors: Nguyen The Hoang Anh, Tran Huy Hoang, Vu Tat Thang, T. T. Quyen Bui

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Mental state classification is an important step for realizing a control system based on electroencephalography (EEG) signals which could benefit a lot of paralyzed people including the locked-in or Amyotrophic Lateral Sclerosis. Considering that EEG signals are nonstationary and often contaminated by various types of artifacts, classifying thoughts into correct mental states is not a trivial problem. In this work, our contribution is that we present and realize a novel model which integrates different techniques: Independent component analysis (ICA), relative wavelet energy, and support vector machine (SVM) for the same task. We applied our model to classify thoughts in two types of experiment whether with two or three mental states. The experimental results show that the presented model outperforms other models using Artificial Neural Network, K-Nearest Neighbors, etc.

Keywords: EEG, ICA, SVM, wavelet

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Authors: Stylianos Kampakis

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This paper presents a new algorithm for neural networks called “Input Dropout with Aggressive Re-weighting” (IDAR) aimed specifically at datasets with many useless features. IDAR combines two techniques (dropout of input neurons and aggressive re weighting) in order to eliminate the influence of noisy features. The technique can be seen as a generalization of dropout. The algorithm is tested on two different benchmark data sets: a noisy version of the iris dataset and the MADELON data set. Its performance is compared against three other popular techniques for dealing with useless features: L2 regularization, LASSO and random forests. The results demonstrate that IDAR can be an effective technique for handling data sets with many useless features.

Keywords: neural networks, feature selection, regularization, aggressive reweighting

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Muhammad Omer Aijaz, Sajjad Haider, Fahad S. Al Mubddal, Yousef Al-Zeghayer, Waheed A. Al Masry

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The present study is focused on the preparation of chitosan-based blend and Semi-Interpenetrating Polymer Network (SEMI-IPN) with polyacrylonitrile (PAN). Blend Chitosan/Polyacrylonitrile (PAN) hydrogel films were prepared by solution blending and casting technique. Chitosan in the blend was cross-linked with epichlorohydrin (ECH) to prepare SEMI-IPN. The developed Chitosan/PAN blend and SEMI-IPN hydrogels were characterized with SEM, FTIR, TGA, and DSC. The result showed good miscibility between chitosan and PAN, crosslinking of chitosan in the blend, and improved thermal properties for SEMI-IPN. The swelling of the different blended and SEMI-IPN hydrogels samples were examined at room temperature. Blend (C80/P20) sample showed highest swelling (2400%) and fair degree of stability (28%) whereas SEMI-IPN hydrogel exhibited relatively low degree of swelling (244%) and high degree of aqueous stability (85.5%).

Keywords: polymer hydrogels, chitosan, SEMI-IPN, polyacrylonitrile, epichlorohydrin

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Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

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Authors: Noha Al Majid, Said Mazer, Moulhime El Bekkali, Catherine Algani, Mahmoud Mehdi

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A low noise figure (NF) and high linearity V-band Low Noise Amplifier (LNA) is reported in this article. The LNA compromises a three-stage cascode configuration. This LNA will be used as a part of a WPAN (Wireless Personal Area Network) receiver in the millimeter-wave band at 60 GHz. It is designed according to the MMIC technology (Monolithic Microwave Integrated Circuit) in PH 15 process from UMS foundry and uses a 0.15 μm GaAs PHEMT (Pseudomorphic High Electron Mobility Transistor). The particularity of this LNA compared to other LNAs in literature is its very low noise figure which is equal to 1 dB and its high linearity (IIP3 is about 22 dB). The LNA consumes 0.24 Watts, achieving a high gain which is about 23 dB, an input return loss better than -10 dB and an output return loss better than -8 dB.

Keywords: low noise amplifier, V-band, MMIC technology, LNA, amplifier, cascode, pseudomorphic high electron mobility transistor (PHEMT), high linearity

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Authors: Richard Tanaka, Ying Zhu

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This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

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Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

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The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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Authors: Riko Wahyudi, Rezky Lasekti Wicaksono, Ayu Satya Damayanti, Ridhasepta Multi Kenrosa

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Implementing Forest Management Unit (FMU) is considered as the best solution for forest management in developing countries. However, when FMU has been formed, many parties then blame the FMU and assume it is not working on. Currently, there are two main issues that make FMU not be functional i.e. institutional and financial issues. This paper is addressing financial issues to make FMUs in Aceh Province can be functional. A mixed financing scheme is proposed here, both direct and indirect financing. The direct financing scheme derived from two components i.e. public funds and businesses. Non-tax instruments of intergovernmental fiscal transfer (IFT) system and FMU’s businesses are assessed. Meanwhile, indirect financing scheme is conducted by assessing public funds within villages around forest estate as about 50% of total villages in Aceh Province are located surrounding forest estate. Potential instruments under IFT system are forest and mining utilization royalties. In order to make these instruments become direct financing for FMU, interventions on allocation and distribution aspects of them are conducted. In the allocation aspect, alteration in proportion of allocation is required as the authority to manage forest has shifted from district to province. In the distribution aspect, Government of Aceh can earmark usage of the funds for FMUs. International funds for climate change also encouraged to be domesticated and then channeled through these instruments or new instrument under public finance system in Indonesia. Based on FMU’s businesses both from forest products and forest services, FMU can impose non-tax fees for each forest product and service utilization. However, for doing business, the FMU need to be a Public Service Agency (PSA). With this status, FMU can directly utilize the non-tax fees without transferring them to the state treasury. FMU only need to report the fees to Ministry of Finance. Meanwhile, indirect financing scheme is conducted by empowering villages around forest estate as villages in Aceh Province is receiving average village fund of IDR 800 million per village in 2017 and the funds will continue to increase in subsequent years. These schemes should be encouraged in parallel to establish a mixed financing scheme in order to ensure sustainable financing for FMU in Aceh Province, Indonesia.

Keywords: forest management, public funds, mixed financing, village

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Authors: Fatimah AlSaiari

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In recent years, newspapers in the United Kingdom have been no longer just a means of sharing news about what happens in the world; they are also used to influence target readers by having them become more up-to-date, well-informed, entertained, exasperated, delighted, and infuriated. To achieve these objectives and maintain influence on public opinion, journalists use a particular language in which they can convey emotions and opinions, organize their discourse, and establish solidarity with their audience. This type of language has been widely analyzed under different labels, such as evaluation, appraisal, and stance. There is a considerable amount of linguistic and non-linguistic research devoted to analyzing this type of interpersonal language in journalistic discourse, and most of these studies were carried out to challenge the traditional assumptions of the objectivity and impartiality of news reporting. However, very little research has been undertaken on evaluative language in newspaper institutional editorials, and there is hardly any systematic or exhaustive analysis of this type of language in British tabloid and broadsheet newspapers. This study will attempt to provide new insights into the nature of authorial and non-authorial evaluation in leading articles in popular and quality British newspapers, along with their targets, sources, and discourse functions. The study will also attempt to develop a framework of evaluation that can be applied to evaluative lexical items in newspaper opinion texts. The framework is both theory-driven (i.e., it builds on and modifies previous frameworks of evaluation such as appraisal theory and parameter-based approach) and data-driven (i.e., it elicits the evaluative categories from the analysis of the corpus, which helps in the development of the current framework). To achieve this aim, a corpus of 140 leading articles were selected. The findings revealed that the tabloids tended to express their stance through explicitness, dramatization, frequent reference to social actors’ emotions and beliefs, and exaggeration in negativity, while the broadsheets preferred to express their stance through mitigation ambiguity and implicitness. conceptual themes and propositions were more preferable targets for expressing stance in the broadsheets while human behavior and characters were preferable targets for the tabloids.

Keywords: appraisal theory, evaluative language, British newspapers, broadsheets & tabloids, evaluative adjectives

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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Authors: Sanchai Ratthanakwan

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This research aims to study situations and characteristics of the problems facing the urban poor. The data and information are collected by focus group and in-depth interview leader and members of Four Regions Slum Network, community representatives and the social welfare officer. The research can be concluded that the problems of the urban poor faced with three major problems: Firstly, the shortage of housing and stability issues in housing; secondly, the problem of substandard quality of life; and thirdly, the debt problem. The study found that a solution will be found in two ways: First way is the creation of housing for the urban poor in slums or community intrusion by the state. Second way is the stability in the housing and subsistence provided by the community center called “housing stability”.

Keywords: urban poor, social welfare, Bangkok metropolis, housing stability

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Authors: Chalee Thammarat

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Mobile phones are equipped with increased short-range communication functionality called Near Field Communication (or NFC for short). NFC needs no pairing between devices but suitable for little amounts of data in a very restricted area. A number of researchers presented authentication techniques for NFC communications, however, they still lack necessary authentication, particularly mutual authentication and security qualifications. This paper suggests a new authentication protocol for NFC communication that gives mutual authentication between devices. The mutual authentication is a one of property, of security that protects replay and man-in-the-middle (MitM) attack. The proposed protocols deploy a limited-use offline session key generation and use of distribution technique to increase security and make our protocol lightweight. There are four sub-protocols: NFCAuthv1 is suitable for identification and access control and NFCAuthv2 is suitable for the NFC-enhanced phone by a POS terminal for digital and physical goods and services.

Keywords: cryptographic protocols, NFC, near field communications, security protocols, mutual authentication, network security

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Authors: Danilo López, Edwin Rivas, Fernando Pedraza

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Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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Authors: B. Rusyidi

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Since 2009, the Indonesian Ministry of Social Affairs has been implementing Program Kesejahteraan Sosial Anak (PKSA) (Child Welfare Program) a conditional cash transfer program that targets neglected children, children with disabilities, street children, children in conflict with the law, and children in need of special protection, all from poor households. PKSA integrates three elements: Transfer of cash, care and social services through social workers, and institutional childcare assistance. This qualitative study analyzed the roles and the challenges of social workers in implementing PKSA and lays out recommendations to inform policy changes. Data were collected in late 2014 from national and local government and non-government child welfare agencies, social workers, and childcare institution representatives through interviews and Focused Group Discussions (FGDs). Field work took place in six districts in the provinces of Jakarta, Central Java and South Sulawesi. The study found that the social workers’ role was significant in facilitating cash transfer, providing education and guidance, and linking children and families to basic social services. This improved utilization of basic social services enhanced children and families’ behaviors and contributed to the well being of the children. However, only a small number of childcare institutions have social workers, leaving many children and families without care and social service linkages, depriving them of rehabilitative components to help them regain their social functions. Some social workers reported their struggles with heavy workloads, lack of professional competencies and training, limited job security, and inadequate professional acknowledgment from other professions. Parts of those challenges were due to the centralized nature of the program and the lack of shared vision and commitment about the child protection system among related government agencies both at the national and local levels. The study highlights the necessity to implement an integrated child protection system, decentralize the PKSA program, and increase the number, competence, case management, and management and monitoring of social workers. The most recent progress of the program and its impacts on social workers are also discussed.

Keywords: child protection, conditional cash transfer, program decentralization, social worker, working conditions

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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: 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: Zineb Emrane

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This abstract addresses the issue of radicalization of young people in a context with background of radicalization, in North of Morocco, 5 terrorist of Madrid's Attacts on 11th March, were coming from this context. It were developed a study pilot that describing young people perception about the main causes that lead and motivate for radicalization. Whenever we talk about this topic, we obtain information from studies and investigations by specialists in field, but we don’t give voice to the protagonists who in many cases are victims, specifically, young people at social risk because of social factors. Extremist radicalization is an expanding phenomenon, that affect young people, in north of Morocco. They live in a context with radical background and at risk of social exclusion, their social, economic and familiar needs make them vulnerable. The extremist groups take advantage of this vulnerability to involve them in a process of radicalization, offering them an alternative environment where they can found all they are looking for. This study pilot approaches the main causes that lead and motivates young people to become radicals, analyzing their context with emphasis on influencing factors, and bearing in mind the analysis of young people about how the radical background affect them and their opinion this phenomenon. The pilot study was carried out through the following actions: - Group dynamics with young people to analyze the process of violent radicalization of young people. -A participatory workshop with members of organizations that work directly with young people at risk of radicalization. -Interviews with institutional managers -Participant observation. The implementation of actions has led to the conclusion that young people define violent radicalization as a sequential process, depending on the stage, it can be deconstructed. Young people recognize that they stop feeling belonging to their family, school and neighborhood when they see behavior contrary to what they consider good and evil. The emotional rupture and the search for references outside their circle, push them to sympathize with groups that have an extremist ideology and that offer them what they need. The radicalization is a process with different stages, the main causes and the factors which lead young people to use extremist violence are related their low level of belonging feeling to their context, and lack of critical thinking about important issues. The young people are in a vulnerable stage, searching their identity, a space in which they can be accepted, and when they don't find it they are easily manipulated and susceptible to being attracted by extremist groups.

Keywords: exclusion, radicalization, vulnerability, youth

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Authors: Shehu Usman Rano Aliyu

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Despite the significance of finance as a major trade lubricant, evidence in the literature alludes to its scarcity and increasing cost, especially in developing countries where small and medium-scale enterprises are worst affected. The creation of the African Continental Free Trade Area (AFCFTA) in 2018, an organ of the African Union (AU), was meant to serve as a beacon for deepening economic integration through the removal of trade barriers inhibiting intra-African trade and movement of persons, among others. Hence, this research explores the role Islamic trade finance (ITF) could play in spurring intra- and inter-African trade. The study involves six countries; Egypt, Kenya, Malaysia, Morocco, Nigeria, and Saudi Arabia, and employs survey research, a total of 430 sample data, and SmartPLS Structural Equation Modelling (SEM) techniques in its analyses. We find strong evidence that Shari’ah, legal and regulatory compliance issues of the ITF institutions rhythm with the internal, national, and international compliance requirements equally as the unique instruments applied in ITF. In addition, ITF was found to be largely driven by global economic and political stability, socially responsible finance, ethical and moral considerations, risk-sharing, and resilience of the global Islamic finance industry. Further, SMEs, Governments, and Importers are the major beneficiary sectors. By and large, AfCFTA’s protocols align with the principles of ITF and are therefore suited for the proliferation of Islamic finance in the continent. And, while AML/KYC and BASEL requirements, compliance to AAOIFI and IFSB standards, paucity of Shari'ah experts, threats to global security, and increasing global economic uncertainty pose as major impediments, the future of ITF would be shaped by a greater need for institutional and policy support, global economic cum political stability, robust regulatory framework, and digital technology/fintech. The study calls for the licensing of more ITF institutions in the continent, participation of multilateral institutions in ITF, and harmonization of Shariah standards.

Keywords: AfCFTA, islamic trade finance, murabaha, letter of credit, forwarding

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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: Rebecca K. Blais, Lindsey Monteith, Hallie Tannahill

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Military sexual trauma (MST) includes sexual harassment or assault that occurred during military service. Studies conducted to date on the association of MST with mental health and suicide outcomes are generally circumscribed to either active duty or veteran samples, precluding a thorough analysis of developmental trajectories of distress following MST within the context of ongoing (vs. discharged from) military service. The Military Social Science Laboratory has collected data on mixed service samples of men and women service members, addressing this important literature gap. The purpose of this study was to examine the association of MST, suicide risk, PTSD, depression, alcohol use, and posttraumatic cognitions using two separate samples, which collectively allow for a comprehensive examination of the development of distress following MST. The first sample consisted of 1389 men and women service members and veterans with varying levels of MST severity, including no MST, harassment-only MST, and assault MST. The second sample consisted of 400 men and women service members, all reporting the highest severity of MST, assault MST. In both samples, roughly half reported being discharged from service. Participants completed self-report measures of MST exposure severity, suicide ideation, suicide risk, PTSD, depression, alcohol misuse, and posttraumatic cognitions, as well as perceptions of how the military responded to their MST. Relative to those still serving in the US military, veterans were more likely to endorse suicidal ideation, higher PTSD symptoms, and higher depression symptoms if they felt the military mishandled their experience of MST (referred to as perceived institutional betrayal). However, among those reporting the most severe MST, veterans reported lower alcohol misuse and more adaptive posttraumatic cognitions. These findings suggest that those separated from the military experience different posttraumatic aftermath following MST relative to those who are currently serving in the military. Such findings suggest critical differences in the developmental trajectory of distress, necessitating different interventions to successfully reduce distress and dysfunction. Additional analyses will explore the impact of gender on these associations and explore full mechanistic models of distress grouped by discharged status.

Keywords: military sexual trauma, PTSD, suicide, developmental trajectories, depression

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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: Swati Srivastava, Mattia Lauriola, Yuval Gilad, Adi Kimchi, Yosef Yarden

Abstract:

The glucocorticoid receptor (GR) has been proposed to play important, but incompletely understood roles in cancer. Glucocorticoids (GCs) are widely used as co-medication of various carcinomas, due to their ability to reduce the toxicity of chemotherapy. Furthermore, GR antagonism has proven to be a strategy to treat triple negative breast cancer and castration-resistant prostate cancer. These observations suggest differential GR involvement in cancer subtypes. The goal of our study has been to elaborate the current understanding of GR signaling in tumor progression and metastasis. Our study involves two cellular models, non-tumorigenic breast epithelial cells (MCF10A) and Ewing sarcoma cells (CHLA9). In our breast cell model, the results indicated that the GR agonist dexamethasone inhibits EGF-induced mammary cell migration, and this effect was blocked when cells were stimulated with a GR antagonist, namely RU486. Microarray analysis for gene expression revealed that the mechanism underlying inhibition involves dexamenthasone-mediated repression of well-known activators of EGFR signaling, alongside with enhancement of several EGFR’s negative feedback loops. Because GR mainly acts primarily through composite response elements (GREs), or via a tethering mechanism, our next aim has been to find the transcription factors (TFs) which can interact with GR in MCF10A cells.The TF-binding motif overrepresented at the promoter of dexamethasone-regulated genes was predicted by using bioinformatics. To validate the prediction, we performed high-throughput Protein Complementation Assays (PCA). For this, we utilized the Gaussia Luciferase PCA strategy, which enabled analysis of protein-protein interactions between GR and predicted TFs of mammary cells. A library comprising both nuclear receptors (estrogen receptor, mineralocorticoid receptor, GR) and TFs was fused to fragments of GLuc, namely GLuc(1)-X, X-GLuc(1), and X-GLuc(2), where GLuc(1) and GLuc(2) correspond to the N-terminal and C-terminal fragments of the luciferase gene.The resulting library was screened, in human embryonic kidney 293T (HEK293T) cells, for all possible interactions between nuclear receptors and TFs. By screening all of the combinations between TFs and nuclear receptors, we identified several positive interactions, which were strengthened in response to dexamethasone and abolished in response to RU486. Furthermore, the interactions between GR and the candidate TFs were validated by co-immunoprecipitation in MCF10A and in CHLA9 cells. Currently, the roles played by the uncovered interactions are being evaluated in various cellular processes, such as cellular proliferation, migration, and invasion. In conclusion, our assay provides an unbiased network analysis between nuclear receptors and other TFs, which can lead to important insights into transcriptional regulation by nuclear receptors in various diseases, in this case of cancer.

Keywords: epidermal growth factor, glucocorticoid receptor, protein complementation assay, transcription factor

Procedia PDF Downloads 229

Authors: Elmabruk Laias

Abstract:

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

Procedia PDF Downloads 479

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

Abstract:

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

Procedia PDF Downloads 165