Search results for: backward chaining inference

Authors: Partha Sarathi Mondal, Srabani Sanyal

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Different geomorphic agents produce a different landforms pattern. Similarly rivers also have a distinct and diverse landforms pattern. And even, within a river course different and distinct assemblage of landforms i.e. morphological variability are seen. These morphological variability are produced by different river processes. Channel and floodplain morphology helps to interpret river processes. Consequently morphological variability can be used as an important tool for assessing river processes, hydrological connectivity and river health, which will help us to draw inference about river processes and therefore, management of river health. The present study is documented on West Rapti river, a trans-boundary river flowing through Nepal and India, from its source to confluence with Ghaghra river in India. The river shows a significant morphological variability throughout its course. The present study tries to find out factors and processes responsible for the morphological variability of the river and in which way it can be applied in river management practices. For this purpose channel and floodplain morphology of West Rapti river was mapped as accurately as possible and then on the basis of process-form interactions, inferences are drawn to understand factors of morphological variability. The study shows that the valley setting of West Rapti river, in the Himalayan region, is confined and somewhere partly confined whereas, channel of the West Rapti river is single thread in most part of Himalayan region and braided in valley region. In the foothill region valley is unconfined and channel is braided, in middle part channel is meandering and valley is unconfined, whereas, channel is anthropogenically altered in the lower part of the course. Due to this the morphology of West Rapti river is highly diverse. These morphological variability are produced by different geomorphic processes. Therefore, for any river management it is essential to sustain these morphological variability so that the river could not cross the geomorphic threshold and environmental flow of the river along with the biodiversity of riparian region is maintained.

Keywords: channel morphology, environmental flow, floodplain morphology, geomorphic threshold

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Authors: Eman W. Boghdady, A. R. Shehata, M. A. Azem

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Database (DB) security demands permitting authorized users and prohibiting non-authorized users and intruders actions on the DB and the objects inside it. Organizations that are running successfully demand the confidentiality of their DBs. They do not allow the unauthorized access to their data/information. They also demand the assurance that their data is protected against any malicious or accidental modification. DB protection and confidentiality are the security concerns. There are four types of controls to obtain the DB protection, those include: access control, information flow control, inference control, and cryptographic. The cryptographic control is considered as the backbone for DB security, it secures the DB by encryption during storage and communications. Current cryptographic techniques are classified into two types: traditional classical cryptography using standard algorithms (DES, AES, IDEA, etc.) and chaos cryptography using continuous (Chau, Rossler, Lorenz, etc.) or discreet (Logistics, Henon, etc.) algorithms. The important characteristics of chaos are its extreme sensitivity to initial conditions of the system. In this paper, DB-security systems based on chaotic algorithms are described. The Pseudo Random Numbers Generators (PRNGs) from the different chaotic algorithms are implemented using Matlab and their statistical properties are evaluated using NIST and other statistical test-suits. Then, these algorithms are used to secure conventional DB (plaintext), where the statistical properties of the ciphertext are also tested. To increase the complexity of the PRNGs and to let pass all the NIST statistical tests, we propose two hybrid PRNGs: one based on two chaotic Logistic maps and another based on two chaotic Henon maps, where each chaotic algorithm is running side-by-side and starting from random independent initial conditions and parameters (encryption keys). The resulted hybrid PRNGs passed the NIST statistical test suit.

Keywords: algorithms and data structure, DB security, encryption, chaotic algorithms, Matlab, NIST

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Authors: Ting Shen, Spyros Konstantopoulos

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During the past three decades, class size effects have been a focal debate in education. The idea of having smaller class is enormously popular among parents, teachers and policy makers. The rationale of its popularity is that small classroom could provide a better learning environment in which there would be more teacher-pupil interaction and more individualized instruction. This early stage benefits would also have a long-term positive effect. It is a common belief that reducing class size may result in increases in student achievement. However, the empirical evidence about class-size effects from experimental or quasi-experimental studies has been mixed overall. This study sheds more light on whether class size reduction impacts reading achievement in eight European countries: Bulgaria, Germany, Hungary, Italy, Lithuania, Romania, Slovakia, and Slovenia. We examine class size effects on reading achievement using national probability samples of fourth graders. All eight European countries had participated in the Progress in International Reading Literacy Study (PIRLS) in 2001, 2006 and 2011. Methodologically, the quasi-experimental method of instrumental variables (IV) has been utilized to facilitate causal inference of class size effects. Overall, the results indicate that class size effects on reading achievement are not significant across countries and years. However, class size effects are evident in Romania where reducing class size increases reading achievement. In contrast, in Germany, increasing class size seems to increase reading achievement. In future work, it would be valuable to evaluate differential class size effects for minority or economically disadvantaged student groups or low- and high-achievers. Replication studies with different samples and in various settings would also be informative. Future research should continue examining class size effects in different age groups and countries using rich international databases.

Keywords: class size, reading achievement, instrumental variables, PIRLS

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Authors: Farahnaz Karami

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Routing is an important, challenging task in mobile ad hoc networks due to node mobility, lack of central control, unstable links, and limited resources. An ant colony has been found to be an attractive technique for routing in Mobile Ad Hoc Networks (MANETs). However, existing swarm intelligence based routing protocols find an optimal path by considering only one or two route selection metrics without considering correlations among such parameters making them unsuitable lonely for routing real time applications. Fuzzy logic combines multiple route selection parameters containing uncertain information or imprecise data in nature, but does not have multipath routing property naturally in order to provide load balancing. The objective of this paper is to design a routing algorithm using fuzzy logic and ant colony that can solve some of routing problems in mobile ad hoc networks, such as nodes energy consumption optimization to increase network lifetime, link failures rate reduction to increase packet delivery reliability and providing load balancing to optimize available bandwidth. In proposed algorithm, the path information will be given to fuzzy inference system by ants. Based on the available path information and considering the parameters required for quality of service (QoS), the fuzzy cost of each path is calculated and the optimal paths will be selected. NS2.35 simulation tools are used for simulation and the results are compared and evaluated with the newest QoS based algorithms in MANETs according to packet delivery ratio, end-to-end delay and routing overhead ratio criterions. The simulation results show significant improvement in the performance of these networks in terms of decreasing end-to-end delay, and routing overhead ratio, and also increasing packet delivery ratio.

Keywords: mobile ad hoc networks, routing, quality of service, ant colony, fuzzy logic

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Authors: Jorge Anibal Restrepo Morales, Sonia Martín Gómez

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A model based on a logical framework was developed to quantify SMEs' internationalization capacity. To do so, linguistic variables, such as human talent, infrastructure, innovation strategies, FTAs, marketing strategies, finance, etc. were integrated. It is argued that a company’s management of international markets depends on internal factors, especially capabilities and resources available. This study considers internal factors as the biggest business challenge because they force companies to develop an adequate set of capabilities. At this stage, importance and strategic relevance have to be defined in order to build competitive advantages. A fuzzy inference system is proposed to model the resources, skills, and capabilities that determine the success of internationalization. Data: 157 linguistic variables were used. These variables were defined by international trade entrepreneurs, experts, consultants, and researchers. Using expert judgment, the variables were condensed into18 factors that explain SMEs’ export capacity. The proposed model is applied by means of a case study of the textile and clothing cluster in Medellin, Colombia. In the model implementation, a general index of 28.2 was obtained for internationalization capabilities. The result confirms that the sector’s current capabilities and resources are not sufficient for a successful integration into the international market. The model specifies the factors and variables, which need to be worked on in order to improve export capability. In the case of textile companies, the lack of a continuous recording of information stands out. Likewise, there are very few studies directed towards developing long-term plans, and., there is little consistency in exports criteria. This method emerges as an innovative management tool linked to internal organizational spheres and their different abilities.

Keywords: business strategy, exports, internationalization, fuzzy set methods

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Authors: Shafiqul Islam, Cordia Chu

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Bangladesh is one of the most vulnerable countries to climate related disasters such as flood and cyclone. Exploring from the semi-structured in-depth interviews of 38 stakeholders and literature review, this study examined the public spending distribution process in DRR. This paper demonstrates how the processes of political economy-enclosure, exclusion, encroachment, and entrenchment hinder the Disaster Risk Reduction (DRR) efforts of Department of Disaster Management (DDM) such as distribution of flood centres, cyclone centres and 40 days employment generation programs. Enclosure refers to when DRR projects allocated to less vulnerable areas or expand the roles of influencing actors into the public sphere. Exclusion refers to when DRR projects limit affected people’s access to resources or marginalize particular stakeholders in decision-making activities. Encroachment refers to when allocation of DRR projects and selection of location and issues degrade the environmental affect or contribute to other forms of disaster risk. Entrenchment refers to when DRR projects aggravate the disempowerment of common people worsen the concentrations of wealth and income inequality within a community. In line with United Nations (UN) Sustainable Development Goals (SDGs), Hyogo and Sendai Frameworks, in the case of Bangladesh, DRR policies implemented under the country’s national five-year plan, disaster-related acts and rules. These policies and practices have somehow enabled influential-elites to mobilize and distribute resources through bureaucracies. Exclusionary forms of fund distribution of DRR exist at both the national and local scales. DRR related allocations have encroached through the low land areas development project without consulting local needs. Most severely, DRR related unequal allocations have entrenched social class trapping the backward communities vulnerable to climate related disasters. Planners and practitioners of DRR need to take necessary steps to eliminate the potential risks from the processes of enclosure, exclusion, encroachment, and entrenchment happens in project fund allocations.

Keywords: Bangladesh, disaster risk reduction, fund distribution, political economy

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Authors: Nalla Somaiah, Praveen Kumar

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Scaling of transistors and, hence, interconnects is very important for the enhanced performance of microelectronic devices. Scaling of devices creates significant complexity, especially in the multilevel interconnect architectures, wherein current crowding occurs at the corners of interconnects. Such a current crowding creates hot-spots at the respective corners, resulting in non-uniform temperature distribution in the interconnect as well. This non-uniform temperature distribution, which is exuberated with continued scaling of devices, creates a temperature gradient in the interconnect. In particular, the increased current density at corners and the associated temperature rise due to Joule heating accelerate the electromigration induced failures in interconnects, especially at corners. This has been the classic reliability issue associated with metallic interconnects. Herein, it is generally understood that electromigration induced damages can be avoided if the length of interconnect is smaller than a critical length, often termed as Blech length. Interestingly, the effect of non-negligible temperature gradients generated at these corners in terms of thermomigration and electromigration-thermomigration coupling has not attracted enough attention. Accordingly, in this work, the interplay between the electromigration and temperature gradient induced mass transport was studied using standard Blech structure. In this particular sample structure, the majority of the current is forcefully directed into the low resistivity metallic film from a high resistivity underlayer film, resulting in current crowding at the edges of the metallic film. In this study, 150 nm thick Cu metallic film was deposited on 30 nm thick W underlayer film in the configuration of Blech structure. Series of Cu thin strips, with lengths of 10, 20, 50, 100, 150 and 200 μm, were fabricated. Current density of ≈ 4 × 1010 A/m² was passed through Cu and W films at a temperature of 250ºC. Herein, along with expected forward migration of Cu atoms from the cathode to the anode at the cathode end of the Cu film, backward migration from the anode towards the center of Cu film was also observed. Interestingly, smaller length samples consistently showed enhanced migration at the cathode end, thus indicating the existence of inverse Blech length effect in presence of temperature gradient. A finite element based model showing the interplay between electromigration and thermomigration driving forces has been developed to explain this observation.

Keywords: Blech structure, electromigration, temperature gradient, thin films

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Authors: Desalegn Feyissa Desu

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Drug therapy problem is a significant challenge to provide high quality health care service for the patients. It is associated with morbidity, mortality, increased hospital stay, and reduced quality of life. Moreover, pediatric patients are quite susceptible to drug therapy problems. Thus this study aimed to assess drug therapy problem and its contributing factors among pediatric patients diagnosed with infectious disease admitted to pediatric ward of Jimma university medical center, from April 1 to June 30, 2018. Prospective observational study was conducted among pediatric patients with infectious disease admitted from April 01 to June 30, 2018. Drug therapy problems were identified by using Cipolle’s and strand’s drug related problem classification method. Patient’s written informed consent was obtained after explaining the purpose of the study. Patient’s specific data were collected using structured questionnaire. Data were entered into Epi data version 4.0.2 and then exported to statistical software package version 21.0 for analysis. To identify predictors of drug therapy problems occurrence, multiple stepwise backward logistic regression analysis was done. The 95% CI was used to show the accuracy of data analysis and statistical significance was considered at p-value < 0.05. A total of 304 pediatric patients were included in the study. Of these, 226(74.3%) patients had at least one drug therapy problem during their hospital stay. A total of 356 drug therapy problems were identified among two hundred twenty six patients. Non-compliance (28.65%) and dose too low (27.53%) were the most common type of drug related problems while disease comorbidity [AOR=3.39, 95% CI= (1.89-6.08)], Polypharmacy [AOR=3.16, 95% CI= (1.61-6.20)] and more than six days stay in hospital [AOR=3.37, 95% CI= (1.71-6.64) were independent predictors of drug therapy problem occurrence. Drug therapy problems were common in pediatric patients with infectious disease in the study area. Presence of comorbidity, polypharmacy and prolonged hospital stay were the predictors of drug therapy problem in study area. Therefore, to overcome the significant gaps in pediatric pharmaceutical care, clinical pharmacists, Pediatricians, and other health care professionals have to work in collaboration.

Keywords: drug therapy problem, pediatric, infectious disease, Ethiopia

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Authors: Emmanuel Chinaguh, Kehinde Adeosun

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Nigerians die untimely, with 55.75 years of life expectancy, which is 17.45 below the world average of 73.2 (Worldometer, 2020). This is due, among other factors, to the country's limited access to high-quality healthcare. To increase access to good and affordable healthcare services, the National Health Insurance Authority (NHIA) Bill 2022 – which repealed the National Health Insurance Scheme Act 2004 – was passed into law. Applying Jacob Mey’s (2001) pragmatics act (pract) theory, this study explores how NHIA seeks to actualise these healthcare goals by characterising the general situational prototype or pragmemes and pragmatic acts in institutional communications. Data was sourced from the NHIA operational guidelines, which has 147 pages and four sections, and shared posters on NHIA Nigeria Twitter Handle with 14,200 followers. Digital humanities tools, like AntConc and Voyant, were engaged in the data analysis for text encoding and data visualisation. This study identifies these discourse tokens in the data: advertisement and programmes, standards and accreditation, records and information, and offences and penalties. Advertisement and programmes pract facilitating, propagating, prospecting, advising and informing; standards and accreditation, and records and information pract stating, informing and instructing; and offences and penalties pract stating and sanctioning. These practs combined to advance the goals of affordable care and universal accessibility to quality healthcare services. The pragmatic acts were marked by these pragmatic tools: shared situational knowledge (SSK), relevance (REL), reference (REF) and inference (INF). This paper adds to the understanding of health insurance discourse in Nigeria as a mediated social practice that promotes the health of Nigerians.

Keywords: affordable care, NHIA, Nigeria’s health insurance discourse, pragmatic acts.

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Authors: Yong Chen

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To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Vahid Ebrahimipour

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Word representation and context meaning of text-based documents play an essential role in knowledge modeling. Business procedures written in natural language are meant to store technical and engineering information, management decision and operation experience during the production system life cycle. Context meaning representation is highly dependent upon word sense, lexical relativity, and sematic features of the argument. This paper proposes a method for lexical semantic analysis and context meaning representation of maintenance activity in a mass production system. Our approach constructs a straightforward lexical semantic approach to analyze facilitates semantic and syntactic features of context structure of maintenance report to facilitate translation, interpretation, and conversion of human-readable interpretation into computer-readable representation and understandable with less heterogeneity and ambiguity. The methodology will enable users to obtain a representation format that maximizes shareability and accessibility for multi-purpose usage. It provides a contextualized structure to obtain a generic context model that can be utilized during the system life cycle. At first, it employs a co-occurrence-based clustering framework to recognize a group of highly frequent contextual features that correspond to a maintenance report text. Then the keywords are identified for syntactic and semantic extraction analysis. The analysis exercises causality-driven logic of keywords’ senses to divulge the structural and meaning dependency relationships between the words in a context. The output is a word contextualized representation of maintenance activity accommodating computer-based representation and inference using OWL/RDF.

Keywords: lexical semantic analysis, metadata modeling, contextual meaning extraction, ontology modeling, knowledge representation

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Authors: G. Medkour Ishak-Boushaki, A. Taibi, M. Allab

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Quantitative environmental radioactivity measurements are needed to determine the level of exposure of a population to ionizing radiations and for the assessment of the associated risks. Gamma spectrometry remains a very powerful tool for the analysis of radionuclides present in an environmental sample but the basic problem in such measurements is the low rate of detected events. Using large environmental samples could help to get around this difficulty but, unfortunately, new issues are raised by gamma rays attenuation and self-absorption. Recently, a new method has been suggested, to detect and identify without quantification, in a short time, a gamma ray of a low count source. This method does not require, as usually adopted in gamma spectrometry measurements, a pulse height spectrum acquisition. It is based on a chronological record of each detected photon by simultaneous measurements of its energy ε and its arrival time τ on the detector, the pair parameters [ε,τ] defining an event mode sequence (EMS). The EMS serials are analyzed sequentially by a Bayesian approach to detect the presence of a given radioactive source. The main object of the present work is to test the applicability of this sequential approach in radioactive environmental materials detection. Moreover, for an appropriate health oversight of the public and of the concerned workers, the analysis has been extended to get a reliable quantification of the radionuclides present in environmental samples. For illustration, we consider as an example, the problem of detection and quantification of 238U. Monte Carlo simulated experience is carried out consisting in the detection, by a Ge(Hp) semiconductor junction, of gamma rays of 63 keV emitted by 234Th (progeny of 238U). The generated EMS serials are analyzed by a Bayesian inference. The application of the sequential Bayesian approach, in environmental radioactivity analysis, offers the possibility of reducing the measurements time without requiring large environmental samples and consequently avoids the attached inconvenient. The work is still in progress.

Keywords: Bayesian approach, event mode sequence, gamma spectrometry, Monte Carlo method

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Authors: Ambrish Tiwari, Sudhasini Panda, Archana Singh, Kalpana Luthra, S. K. Sharma

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Introduction: On the basis of available literature we know that various host factors play a role in outcome of Tuberculosis (TB) infection by modulating innate immunity. One such factor is Inducible Nitric Oxide Synthase enzyme (iNOS) which help in the production of Nitric Oxide (NO), an antimicrobial agent. Expression of iNOS is in control of various host factors in which Vitamin D along with its nuclear receptor Vitamin D receptor (VDR) is one of them. Vitamin D along with its receptor also produces cathelicidin (antimicrobicidal agent). With this background, we attempted to investigate the levels of Vitamin D and NO along with their associated molecules in tuberculosis patients and household contacts as compared to healthy controls and assess the implication of these findings in susceptibility to tuberculosis (TB). Study subjects and methods: 100 active TB patients, 75 household contacts, and 70 healthy controls were taken. VDR and iNOS mRNA levels were studied using real-time PCR. Serum VDR, cathelicidin, iNOS levels were measured using ELISA. Serum Vitamin D levels were measured in serum samples using chemiluminescence based immunoassay. NO was measured using colorimetry based kit. Results: VDR and iNOS mRNA levels were found to be lower in active TB group compared to household contacts and healthy controls (P=0.0001 and 0.005 respectively). The serum levels of Vitamin D were also found to be lower in active TB group as compared to healthy controls (P =0.001). Levels of cathelicidin and NO was higher in patient group as compared to other groups (p=0.01 and 0.5 respectively). However, the expression of VDR and iNOS and levels of vitamin D was significantly (P < 0.05) higher in household contacts compared to both active TB and healthy control groups. Inference: Higher levels of Vitamin D along with VDR and iNOS expression in household contacts as compared to patients suggest that vitamin D might have a protective role against TB which prevents activation of the disease. From our data, we can conclude that decreased vitamin D levels could be implicated in disease progression and we can use cathelicidin and NO as a biomarker for early diagnosis of pulmonary tuberculosis.

Keywords: vitamin D, VDR, iNOS, tuberculosis

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Authors: Ayala Amir

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The paper presents interdisciplinary research which draws on the literary study and the cultural study of photography to explore a literary genre defined by nostalgia – the photographed book for children. This genre, which was popular in the second half of the 20th century, presents the romantic, nostalgic image of childhood created in the visual arts in the 18th century (as suggested by Ann Higonnet). At the same time, it capitalizes on the nostalgia inherent in the event of photography as formulated by Jennifer Green-Lewis: photography frames a moment in the present while transforming it into a past longed for in the future. Unlike Freudian melancholy, nostalgia is an effect that enables representation by acknowledging the loss and containing it in the very experience of the object. The representation and preservation of the lost object (nature, childhood, innocence) are in the center of the genre of children's photography books – a modern version of ancient pastoral. In it, the unique synergia of word and image results in a nostalgic image of childhood in an era already conquered by modernization. The nostalgic effect works both in the representation of space – an Edenic image of nature already shadowed by its demise, and of time – an image of childhood imbued by what Gill Bartholnyes calls the "looking backward aesthetics" – under the sign of loss. Little critical attention has been devoted to this genre with the exception of the work of Bettina Kümmerling-Meibauer, who noted the nostalgic effect of the well-known series of photography books by Astrid Lindgren and Anna Riwkin-Brick. This research aims to elaborate Kümmerling-Meibauer's approach using the theories of the study of photography, word-image studies, as well as current studies of childhood. The theoretical perspectives are implemented in the case study of photography books created in one of the most innovative social structures in our time – the Israeli Kibbutz. This communal way of life designed a society where children will experience their childhood in a parentless rural environment that will save them from the fate of the Oedipal fall. It is suggested that in documenting these children in a fictional format, photographers and writers, images and words cooperated in creating nostalgic works situated on the border between nature and culture, imagination and reality, utopia and its realization in history.

Keywords: nostalgia, photography , childhood, children's books, kibutz

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Authors: Erika Takidah, Salina Kassim

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Digital transformation has accelerated in the new millennium. It is reshaping the financial services industry from a traditional system to financial technology. Moreover, the number of financial inclusion rates in Indonesia is less than 60%. An innovative model needed to elucidate this national problem. On the other hand, the Islamic financial service industry and financial technology grow fast as a new aspire in economic development. An Islamic bank, takaful, Islamic microfinance, Islamic financial technology and Islamic social finance institution could collaborate to intensify the financial inclusion number in Indonesia. The primary motive of this paper is to examine the strategy of collaboration-based Islamic financial services to enhance financial inclusion in Indonesia, particularly facing the digital era. The fundamental findings for the main problems are the foundations and key ecosystems aspect involved in the development of collaboration-based Islamic financial services. By using the Interpretive Structural Model (ISM) approach, the core problems faced in the development of the models have lacked policy instruments guarding the collaboration-based Islamic financial services with fintech work process and availability of human resources for fintech. The core strategies or foundations that are needed in the framework of collaboration-based Islamic financial services are the ability to manage and analyze data in the big data era. For the aspects of the Ecosystem or actors involved in the development of this model, the important actor is government or regulator, educational institutions, and also existing industries (Islamic financial services). The outcome of the study designates that strategy collaboration of Islamic financial services institution supported by robust technology, a legal and regulatory commitment of the regulators and policymakers of the Islamic financial institutions, extensive public awareness of financial inclusion in Indonesia. The study limited itself to realize financial inclusion, particularly in Islamic finance development in Indonesia. The study will have an inference for the concerned professional bodies, regulators, policymakers, stakeholders, and practitioners of Islamic financial service institutions.

Keywords: collaboration, financial inclusion, Islamic financial services, Islamic fintech

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Authors: Hung-Sheng Lin, Cheng-Hsuan Li

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Over the past few years, kernel-based algorithms have been widely used to extend some linear feature extraction methods such as principal component analysis (PCA), linear discriminate analysis (LDA), and nonparametric weighted feature extraction (NWFE) to their nonlinear versions, kernel principal component analysis (KPCA), generalized discriminate analysis (GDA), and kernel nonparametric weighted feature extraction (KNWFE), respectively. These nonlinear feature extraction methods can detect nonlinear directions with the largest nonlinear variance or the largest class separability based on the given kernel function. Moreover, they have been applied to improve the target detection or the image classification of hyperspectral images. The double nearest proportion feature extraction (DNP) can effectively reduce the overlap effect and have good performance in hyperspectral image classification. The DNP structure is an extension of the k-nearest neighbor technique. For each sample, there are two corresponding nearest proportions of samples, the self-class nearest proportion and the other-class nearest proportion. The term “nearest proportion” used here consider both the local information and other more global information. With these settings, the effect of the overlap between the sample distributions can be reduced. Usually, the maximum likelihood estimator and the related unbiased estimator are not ideal estimators in high dimensional inference problems, particularly in small data-size situation. Hence, an improved estimator by shrinkage estimation (regularization) is proposed. Based on the DNP structure, LDA is included as a special case. In this paper, the kernel method is applied to extend DNP to kernel-based DNP (KDNP). In addition to the advantages of DNP, KDNP surpasses DNP in the experimental results. According to the experiments on the real hyperspectral image data sets, the classification performance of KDNP is better than that of PCA, LDA, NWFE, and their kernel versions, KPCA, GDA, and KNWFE.

Keywords: feature extraction, kernel method, double nearest proportion feature extraction, kernel double nearest feature extraction

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Authors: Yin Ma, Xun Wang, Kelsey Austin

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Purpose – Building upon career construction theory and the conservation of resources theory, we developed a moderated mediation model to examine how the perceived university support impact students’ career adapting responses, namely, crystallization, exploration, decision and preparation, via the mediator career adaptability and moderator perceived parental support. Design/methodology/approach – The multi-stage sampling strategy was employed and survey data were collected. Structural equation modeling was used to perform the analysis. Findings – Perceived university support could directly promote students’ career adaptability, and promote three career adapting responses, namely, exploration, decision and preparation. It could also impact four career adapting responses via mediation effect of career adaptability. Its impact on students’ career adaptability can greatly increase when students’ receive parental related career support. Research limitations/implications – The cross-sectional design limits causal inference. Conducted in China, our findings should be cautiously interpreted in other countries due to cultural differences. Practical implications – University support is vital to students’ career adaptability and supports from parents can enhance this process. University-home collaboration is necessary to promote students’ career adapting responses. For students, seeking and utilizing as much supporting resources as possible is vital for their human resources development. On an organizational level, universities could benefit from our findings by introducing the practices which ask students to rate the career-related courses and encourage them to chat with parents regularly. Originality/ value – Using recently developed scale, current work contributes to the literature by investigating the impact of multiple contextual factors on students’ career adapting response. It also provide the empirical support for the role of human intervention in fostering career adapting responses.

Keywords: career adapability, university and parental support, China studies, sociology of education

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Authors: Karen V. Lee

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The background and significance of this study involve communication in education by a faculty advisor exploring story and music that informs others about a disabled teacher. Social issues draw deep reflection about the emotional turmoil. As a musician becoming a teacher is a passionate yet complex endeavor, the faculty advisor shares a poetic but painful story about a disabled teacher being inducted into the teaching profession. The qualitative research method as theoretical framework draws on autoethnography of music and story where the faculty advisor approaches a professor for advice. His musicianship shifts her forward, backward, and sideways through feelings that evoke and provoke curriculum to remove communication barriers in education. They discover they do not transfer knowledge from educational method classes. Instead, the autoethnography embeds musical language as a metaphorical conduit for removing communication barriers in teacher education. Sub-themes involve communication barriers and educational technologies to ensure teachers receive social, emotional, physical, spiritual, and intervention disability resources that evoke visceral, emotional responses from the audience. Major findings of the study discover how autoethnography of music and story bring the authors to understand wider political issues of the practicum internship for teachers with disabilities. An epiphany reveals the irony of living in a culture of both uniformity and diversity. They explore the constructs of secrecy, ideology, abnormality, and marginalization by evoking visceral and emotional responses from the audience. As the voices harmonize plot, climax, characterization, and denouement, they dramatize meaning that is episodic yet incomplete to highlight the circumstances surrounding the disabled protagonist’s life. In conclusion, the qualitative research method argues for embracing storied experiences that depict communication in education. Scholarly significance embraces personal thoughts and feelings as a way of understanding social phenomena while highlighting the importance of removing communication barriers in education. The circumstance about a teacher with a disability is not uncommon in society. Thus, the authors resolve to removing barriers in education by using stories to transform the personal and cultural influences that provoke new ways of thinking about the curriculum for a disabled teacher.

Keywords: communication in education, communication barriers, autoethnography, teaching

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Mai Alharthy, Agnes Shiel, Hynes Sinead

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Objectives: The objectives of the study are to translate and culturally adapt the RBMT-3 to be appropriate for use within an Arabic-speaking population and to achieve maximum equivalency between the translated and original versions and to evaluate the psychometric properties of the Arabic version of the RBMT-3. Participants' numbers are 16 (10 females and 6 males). All participants are bilingual speakers of Arabic and English, above 18 years old and with no current nor past memory impairment. Methods: The study was conducted in two stages: Translation and cultural adaptation stage: Forward and backward translations were completed by professional translators. Five out of the 14 RBMT-3 subtests required cultural adaptations. Half of the faces in the face recognition subtests were replaced with Arabic faces by a professional photographer. Pictures that are irrelevant to the Arabic culture in the picture recognition subtests were replaced. Names, story and orientations subtests were also adapted to suit the Arabic culture. An expert committee was formed to compare the translated and original versions and to advise on further changes required for test materials. Validation of the Arabic RBMT-3- pilot: 16 Participants were tested on version 1 of the English version and the two versions of the Arabic RBMT-3 ( counterbalanced ). The assessment period was 6 weeks long, with two weeks gap between tests. All assessments took place in a quiet room in the National University of Ireland Galway. Two qualified occupational therapists completed the assessments. Results: Wilcox signed-rank test was used to compare between subtest scores. Significant differences were found in the story, orientation and names subtests between the English and Arabic versions. No significant differences were found in subtests from both Arabic versions except for the story subtest. Conclusion: The story and orientation subtests should be revised by the expert committee members to make further adaptations. The rest of the Arabic RBMT-3 subtests are equivalent to the subtests of the English version. The psychometric properties of the Arabic RBMT-3 will be investigated in a larger Arabic-speaking sample in Saudi Arabia. The outcome of this research is to provide clinicians and researchers with a reliable tool to assess memory problems in Arabic speaking population.

Keywords: memory impairment, neuropsychological assessment, cultural adaptation, cognitive assessment

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Authors: M. V. Shivaani, P. K. Jain, Surendra S. Yadav

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Worldwide regulators, practitioners and researchers view risk-disclosure as one of the most important steps that will promote corporate accountability and transparency. Recognizing this growing significance of risk disclosures, the paper first develops a risk disclosure index. Covering 69 risk items/themes, this index is developed by employing thematic content analysis and encompasses three attributes of disclosure: namely, nature (qualitative or quantitative), time horizon (backward-looking or forward-looking) and tone (no impact, positive impact or negative impact). As the focus of study is on substantive rather than symbolic disclosure, content analysis has been carried out manually. The study is based on non-financial companies of Nifty500 index and covers a ten year period from April 1, 2005 to March 31, 2015, thus yielding 3,872 annual reports for analysis. The analysis reveals that (on an average) only about 14% of risk items (i.e. about 10 out 69 risk items studied) are being disclosed by Indian companies. Risk items that are frequently disclosed are mostly macroeconomic in nature and their disclosures tend to be qualitative, forward-looking and conveying both positive and negative aspects of the concerned risk. The second objective of the paper is to gauge the factors that affect the level of disclosures in annual reports. Given the panel nature of data, and possible endogeneity amongst variables, Diff-GMM regression has been applied. The results indicate that age and size of firms have a significant positive impact on disclosure quality, whereas growth rate does not have a significant impact. Further, post-recession period (2009-2015) has witnessed significant improvement in quality of disclosures. In terms of corporate governance variables, board size, board independence, CEO duality, presence of CRO and constitution of risk management committee appear to be significant factors in determining the quality of risk disclosures. It is noteworthy that the study contributes to literature by putting forth a variant to existing disclosure indices that not only captures the quantity but also the quality of disclosures (in terms of semantic attributes). Also, the study is a first of its kind attempt in a prominent emerging market i.e. India. Therefore, this study is expected to facilitate regulators in mandating and regulating risk disclosures and companies in their endeavor to reduce information asymmetry.

Keywords: risk disclosure, voluntary disclosures, corporate governance, Diff-GMM

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Authors: Deniz Sari, Selahattin İncecik, Nesimi Ozkurt

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Surface ozone, which named as one of the most critical pollutants in the 21th century, threats to human health, forest and vegetation. Specifically, in rural areas surface ozone cause significant influences on agricultural productions and trees. In this study, in order to understand to the surface ozone levels in rural areas we focus on the north-western side of Biga Peninsula which covers by the mountainous and forested area. Ozone concentrations were measured for the first time with passive sampling at 10 sites and two online monitoring stations in this rural area from 2013 and 2015. Using with the daytime hourly O3 measurements during light hours (08:00–20:00) exceeding the threshold of 40 ppb over the 3 months (May, June and July) for agricultural crops, and over the six months (April to September) for forest trees AOT40 (Accumulated hourly O3 concentrations Over a Threshold of 40 ppb) cumulative index was calculated. AOT40 is defined by EU Directive 2008/50/EC to evaluate whether ozone pollution is a risk for vegetation, and is calculated by using hourly ozone concentrations from monitoring systems. In the present study, we performed the trajectory analysis by The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to follow the long-range transport sources contributing to the high ozone levels in the region. The ozone episodes observed between 2013 and 2015 were analysed using the HYSPLIT model developed by the NOAA-ARL. In addition, the cluster analysis is used to identify homogeneous groups of air mass transport patterns can be conducted through air trajectory clustering by grouping similar trajectories in terms of air mass movement. Backward trajectories produced for 3 years by HYSPLIT model were assigned to different clusters according to their moving speed and direction using a k-means clustering algorithm. According to cluster analysis results, northerly flows to study area cause to high ozone levels in the region. The results present that the ozone values in the study area are above the critical levels for forest and vegetation based on EU Directive 2008/50/EC.

Keywords: AOT40, Biga Peninsula, HYSPLIT, surface ozone

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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Authors: Elsadig Naseraddeen Ahmed Mohamed

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In contrast to the uncertainty and complementary principle, it will be shown in the present paper that the probability of the simultaneous occupation event of any definite values of coordinates by any definite values of momentum and energy at any definite instance of time can be described by a binary definite function equivalent to the difference between their numbers of occupation and evacuation epochs up to that time and also equivalent to the number of exchanges between those occupation and evacuation epochs up to that times modulus two, these binary definite quantities can be defined at all point in the time’s real-line so it form a binary signal represent a complete mechanical description of physical reality, the time of these exchanges represent the boundary of occupation and evacuation epochs from which we can calculate these binary signals using the fact that the time of universe events actually extends in the positive and negative of time’s real-line in one direction of extension when these number of exchanges increase, so there exists noninvertible transformation matrix can be defined as the matrix multiplication of invertible rotation matrix and noninvertible scaling matrix change the direction and magnitude of exchange event vector respectively, these noninvertible transformation will be called actual transformation in contrast to information transformations by which we can navigate the universe’s events transformed by actual transformations backward and forward in time’s real-line, so these information transformations will be derived as an elements of a group can be associated to their corresponded actual transformations. The actual and information model of the universe will be derived by assuming the existence of time instance zero before and at which there is no coordinate occupied by any definite values of momentum and energy, and then after that time, the universe begin its expanding in spacetime, this assumption makes the need for the existence of Laplace’s demon who at one moment can measure the positions and momentums of all constituent particle of the universe and then use the law of classical mechanics to predict all future and past of universe’s events, superfluous, we only need for the establishment of our analog to digital converters to sense the binary signals that determine the boundaries of occupation and evacuation epochs of the definite values of coordinates relative to its origin by the definite values of momentum and energy as present events of the universe from them we can predict approximately in high precision it's past and future events.

Keywords: binary-signal mechanics, actual-information model of the universe, actual-transformation, information-transformation, uncertainty principle, Laplace's demon

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Authors: Balasooriya B. M. C. M., Sujeeva N., Thowfeek Z., Siddiqa Omo, Liyanagunawardana J. E., Jayawardana Saiu, Manathunga S. S., Katulanda G. W.

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Introduction and objectives: Adrenal venous sampling (AVS) is the gold standard to discriminate unilateral primary aldosteronism (UPA) from bilateral disease (BPA). AVS is technically demanding and only performed in a limited number of centers worldwide. To the best of our knowledge, Except for one study conducted in India, no other research studies on this area have been conducted in South Asia. This study aimed to evaluate the effectiveness of AVS in the management of primary aldosteronism. Methods: A total of 32 patients who underwent AVS at the National Hospital of Sri Lanka from April 2021 to April 2023 were enrolled. Demographic, clinical and laboratory data were obtained retrospectively. A procedure was considered successful when adequate cannulation of both adrenal veins was demonstrated. Cortisol gradient across the adrenal vein (AV) and the peripheral vein was used to establish the success of venous cannulation. Lateralization was determined by the aldosterone gradient between the two sides. Continuous and categorical variables were summarized with mean, SD, and proportions, respectively. The mean and standard deviation of the contralateral suppression index (CSI) were estimated with an intercept-only Bayesian inference model. Results: Of the 32 patients, the average age was 52.47 +26.14 and 19 (59.4%) were males. Both AVs were successfully cannulated in 12 (37.5%). Among them, lateralization was demonstrated in 11(91.7%), and one was diagnosed as a bilateral disease. There were no total failures. Right AV cannulation was unsuccessful in 18 (56.25%), of which lateralization was demonstrated in 9 (50%), and others were inconclusive. Left AV cannulation was unsuccessful only in 2 (6.25%); one was lateralized, and the other remained inconclusive. The estimated mean of the CSI was 0.33 (89% credible interval 0.11-0.86). Seven patients underwent unilateral adrenalectomy and demonstrated significant improvement in blood pressure during follow-up. Two patients await surgery. Others were treated medically. Conclusions: Despite failure due to procedural difficulties, AVS remained useful in the management of patients with PA. Moreover, the success of the procedure needs experienced hands and advanced equipment to achieve optimal outcomes in PA.

Keywords: adrenal venous sampling, lateralization, contralateral suppression index, primary aldosteronism

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Authors: Jalal Haghighat Monfared, Zahra Akbari

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Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: business intelligence, business intelligence capability, decision making, decision quality

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Authors: Noppadol Poomvises, Prateep Pakdeerod, Anchalee Kongsuk

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In the middle of September 2017, a tropical storm named ‘DOKSURI’ swept through Udon Thani, Northeastern Thailand. The storm dumped heavy rain for many hours and caused large amount of water flowing into Huai Phueng reservoir. Level of impounding water increased rapidly, and the extra water flowed over a service spillway, morning-glory type constructed by concrete material for about 50 years ago. Subsequently, a sinkhole was formed on the dam crest and five points of water piping were found on downstream slope closely to spillway. Three techniques of geophysical investigation were carried out to inspect cause of failures; Electrical Resistivity Imaging (ERI), Multichannel Analysis of Surface Wave (MASW), and Ground Penetrating Radar (GPR), respectively. Result of ERI clearly shows evidence of overtop event and heterogeneity around spillway that implied possibility of previous shape of sinkhole around the pipe. The shear wave velocity of subsurface soil measured by MASW can numerically convert to undrained shear strength of impervious clay core. Result of GPR clearly reveals partial settlements of freeboard zone at top part of the dam and also shaping new refilled material to plug the sinkhole back to the condition it should be. In addition, the GPR image is a main answer to confirm that there are not any sinkholes in the survey lines, only that found on top of the spillway. Integrity interpretation of the three results together with several evidences observed during a field walk-through and data from drilled holes can be interpreted that there are four main causes in this account. The first cause is too much water flowing over the spillway. Second, the water attacking morning glory spillway creates cracks upon concrete contact where the spillway is cross-cut to the center of the dam. Third, high velocity of water inside the concrete pipe sucking fine particle of embankment material down via those cracks and flushing out to the river channel. Lastly, loss of clay material of the dam into the concrete pipe creates the sinkhole at the crest. However, in case of failure by piping, it is possible that they can be formed both by backward erosion (internal erosion along or into embedded structure of spillway walls) and also by excess saturated water of downstream material.

Keywords: dam inspection, GPR, MASW, resistivity

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Authors: Sunil Gaikwad

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Gender discrimination is a very prevalent and much used word in the legal parlance. , The more socially, culturally, economically and educationally backward the community, the more gender discrimination is seen there. Gender discrimination is a worldwide Phenomena. In India it was more prevalent, due to illiteracy, bad social and religious customs. in Indian family system male child is considered as inheritor of the family clan, support for parents in their old age and girls as the property of others and unnecessary load on parents and on property as the dowry has to be give at her marriage as also some festivals like Raksha Bandhan and Bhau Teej during Deepawali (wherein having brother is compulsory)insist on having a male child in the family, hence most couples try to give birth only to male child at the cost of female child, hence the female feticide was going on a large scale due to which, sex ratio had considerably decreased creating problem for geeting groom for bride groom thereby putting question mark on family system. To redo the damage done to the society due to the female feticide Government of India has enacted various Laws and introduced various welfare schemes for the upliftment of girl child and also launched countrywide awareness campaign to create awareness among people about the importance of girl child and punitive laws for infanticide which is now bearing fruits but still cases of female feticide are coming fore. There is an urgent need to go to the roots of the problem and to find practicable and effective legal and social measures to overcome this issue, and the purpose of this research paper is the same. The research paper discusses in detail the reasons and superstitions that are responsible for the gender discriminations and comes out with effective measures including necessary and effective changes in the existing Laws, effective awareness campaign against religious superstitions for gender equality. For this research paper doctrinal research methodology is used to drive the research to its logical conclusion, for which various primary and secondary sources literature has been perused and studied. It is worth noting that while working on the paper suggestions and recommendations and conclusions have been drawn where it is suggested and concluded that there is an urgent need to re think about the festivals which encourages gender discriminations, to sensitize and create ample of awareness among people by effectively utilizing Radio, Television, Social Media folk arts, public shows and to make existing laws more effective and strict implementation for the purpose and zero tolerance for female feticide.

Keywords: awareness, effective laws, female foeticide, festivals, superstitions

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