iPad’s contributed to enhance inclusion of students with visual impairment in public schools

This study aimed to identify the extent iPad’s contributed to enhance inclusion of students with visual impairment (partially) in public schools. The study used the descriptive and analytical approach. The population consisted of (160) students who received iPad device within the “vision project” implemented at UNRWA schools in Gaza strip. The study used a questionnaire prepared and adapted by the researcher, to measure degree of iPad’s contribution to inclusion in general and at three dimensions: academic, psychological, and behavioral. Results showed the level of iPad’s contribution to enhance inclusion among students with visual impairment was high, with an average of 2.70 and a relative weight 90%. Concerning the three dimensions, results showed the academic attained as average of 2.77 with relative weight 88.6%, however in the second dimension (psychological) the mean was 2.98 with relative weight 99.3%, lastly for the third dimension (behavioral), the mean was 2.67 with relative weight 89.0%. This indicated high level of iPad’s contribution to enhance inclusion of students with visual impairment at public schools specifically at UNRWA schools. The study recommended use iPads for best inclusive practices.

Modeling the Sustainable Development Nexus as a Complex-Coupled System

This chapter begins with defining complex systems, presents an overview of the applied science of dynamical systems by focusing on the main components of complexity and chaos, and introduces the concept of dimensionality of systems. Systems have structural and temporal (dynamic) components – they exist in space and time. This chapter focuses on the time dimension, called temporality. The authors classify a third dimension, chaos (randomness), and illustrate that all systems can be defined according to their structure, dynamics, and chaos. These three dimensions constitute the dimensionality of systems, which can be used to define and categorize all types of systems. A system dynamics model to quantify the progress and interactions among the United Nation's Sustainable Development Goals (SDG) is introduced. The benefits and limitations of a system dynamics modeling approach in this context are then discussed.

Two Cases of Feigned Homicidality: Assessing the Third Dimension in Homicidal Threats

Although data and research on the topic are lacking, the phenomenon of feigned homicidality in short-term hospitalization appears to have increased in recent years. Inpatient psychiatrists not only assess the seriousness of homicidal threats, but also whether such threats are authentic. However, specific literature and diagnostic manuals provide virtually no clinical guidance for this. The authors present two case examples of homicidality feigned for self-serving purposes that had little to do with hostility against the would-be victim. They recommend an approach to assessment that first takes any threat of homicide seriously, and involves an attempt to assess the seriousness of the threat and risk of harm. Secondly, if feigned homicidality is suspected, clinicians can methodically assess for this using criterion that have been applied to the assessment of malingering.

QDC-2D: A Semi-Automatic Tool for 2D Analysis of Discontinuities for Rock Mass Characterization

Quantitative characterization of discontinuities is fundamental to define the mechanical behavior of discontinuous rock masses. Several techniques for the semi-automatic and automatic extraction of discontinuities and their properties from raw or processed point clouds have been introduced in the literature to overcome the limits of conventional field surveys and improve data accuracy. However, most of these techniques do not allow characterizing flat or subvertical outcrops because planar surfaces are difficult to detect within point clouds in these circumstances, with the drawback of undersampling the data and providing inappropriate results. In this case, 2D analysis on the fracture traces are more appropriate. Nevertheless, to our knowledge, few methods to perform quantitative analyses on discontinuities from orthorectified photos are publicly available and do not provide a complete characterization. We implemented scanline and window sampling methods in a digital environment to characterize rock masses affected by discontinuities perpendicular to the bedding from trace maps, thus exploiting the potentiality of remote sensing techniques for subvertical and low-relief outcrops. The routine, named QDC-2D (Quantitative Discontinuity Characterization, 2D) was compiled in MATLAB by testing a synthetic dataset and a real case study, from which a high-resolution orthophoto was obtained by means of Structure from Motion technique. Starting from a trace map, the routine semi-automatically classifies the discontinuity sets and calculates their mean spacing, frequency, trace length, and persistence. The fracture network is characterized by means of trace length, intensity, and density estimators. The block volume and shape are also estimated by adding information on the third dimension. The results of the 2D analysis agree with the input used to produce the synthetic dataset and with the data collected in the field by means of conventional geostructural and geomechanical techniques, ensuring the procedure’s reliability. The outcomes of the analysis were implemented in a Discrete Fracture Network model to evaluate their applicability for geomechanical modeling.

The Whale Optimization Algorithm Approach for Deep Neural Networks

One of the biggest challenge in the field of deep learning is the parameter selection and optimization process. In recent years different algorithms have been proposed including bio-inspired solutions to solve this problem, however, there are many challenges including local minima, saddle points, and vanishing gradients. In this paper, we introduce the Whale Optimisation Algorithm (WOA) based on the swarm foraging behavior of humpback whales to optimise neural network hyperparameters. We wish to stress that to the best of our knowledge this is the first attempt that uses Whale Optimisation Algorithm for the optimisation task of hyperparameters. After a detailed description of the WOA algorithm we formulate and explain the application in deep learning, present the implementation, and compare the proposed algorithm with other well-known algorithms including widely used Grid and Random Search methods. Additionally, we have implemented a third dimension feature analysis to the original WOA algorithm to utilize 3D search space (3D-WOA). Simulations show that the proposed algorithm can be successfully used for hyperparameters optimization, achieving accuracy of 89.85% and 80.60% for Fashion MNIST and Reuters datasets, respectively.