Design and implement a new secure prototype structure of e-commerce system

<p><br />The huge development of internet technologies and the widespread of modern and advanced devices lead to an increase in the size and diversity of e-commerce system development. These developments lead to an increase in the number of people that navigate these sites asking for their services and products. Which leads to increased competition in this field. Moreover, the expansion in the size of currency traded makes transaction protection an essential issue in this field. Providing security for each online client especially for a huge number of clients at the same time, causing an overload on the system server. This problem may lead to server deadlock, especially at rush time, which reduce system performance. To solve security and performance problems, this research suggests a prototype design for agent software. This agent will play the role of broker between the clients and the electronic marketplace. This is done by providing security inside the client device and converting the client’s order into a special form which is called a record form to be sent to the commercial website. Experimental results showed that this method increase system performance in terms of page loading time, transaction processing and improves the utilization of system resources.</p>

Do You Ever Get Off Track in a Conversation? The Conversational System’s Anatomy and Evaluation Metrics

Conversational systems are now applicable to almost every business domain. Evaluation is an important step in the creation of dialog systems so that they may be readily tested and prototyped. There is no universally agreed upon metric for evaluating all dialog systems. Human evaluation, which is not computerized, is now the most effective and complete evaluation approach. Data gathering and analysis are evaluation activities that need human intervention. In this work, we address the many types of dialog systems and the assessment methods that may be used with them. The benefits and drawbacks of each sort of evaluation approach are also explored, which could better help us understand the expectations associated with developing an automated evaluation system. The objective of this study is to investigate conversational agents, their design approaches and evaluation metrics. This approach can help us to better understand the overall process of dialog system development, and future possibilities to enhance user experience. Because human assessment is costly and time consuming, we emphasize the need of having a generally recognized and automated evaluation model for conversational systems, which may significantly minimize the amount of time required for analysis.

IMPLEMENTASI METODE AHP PADA SISTEM PENDUKUNG KEPUTUSAN PARIWISATA JAWA TIMUR

Perubahan perilaku wisatawan dalam berwisata dengan bantuan perangkat digital salah satunya adalah perencanaan wisata, contohnya yaitu menentukan destinasi wisata. Pemilihan destinasi wisata yang bervariasi di Provinsi Jawa Timur oleh para calon wisatawan dapat dipermudah guna meningkatkan strategi manajemen pariwisata. Penelitian ini bertujuan untuk menghasilkan Sistem Pendukung Keputusan atau Decision Support System (DSS) berbasis website yang dapat mempermudah wisatawan dalam menentukan pilihan destinasi pariwisata di wilayah Jawa Timur. Sebagai metode pengambilan keputusan, Analytical Hierarchy Process (AHP) diterapkan. Metode System Development Life Cycle (SDLC) yang meliputi tahap perencanaan, analisis, desain, dan produksi serta pengujian dan implementasi, digunakan dalam mengembangkan Sistem Pendukung Keputusan. Pengujian khusus sistem dan user-testing menunjukkan bahwa seluruh fungsionalitas yang diuji bekerja dengan baik dengan black box testing, sedangkan user-testing menunjukkan bahwa 87,13% pengguna setuju bahwa sistem ramah pengguna.

APLIKASI PENGENALAN TINGKAT KEMATANGAN BUAH TOMAT MENGGUNAKAN FITUR WARNA HSV BERBASIS ANDROID

Tomatoes ripen relatively quickly, so tomato farmers must be able to properly sort the tomatoes for distribution. Farmers typically sort the tomatoes by hand. Tomato farmers are generally experts at manually sorting tomatoes, but humans have many limitations, such as being tired and unfocused. Because these issues can lead to inconsistencies and inaccuracies in sorting, a tool is required to help with the process. As a result, it is necessary to create an Android application to aid in the sorting process. The reason for using Android as a platform is that it is a tool that a large number of people own. The LVQ algorithm is used as a learning algorithm to find the best model for tomato recognition. To build the model, the algorithm requires features. Colors with Hue, Saturation, and Value (HSV) are used. The Personal eXtreme Programming (PXP) system development methodology was used to create applications that recognize the level of ripeness of tomatoes. Unified Modeling Language (UML) is the analytic tool of choice. The application was successfully developed on the Android platform based on the test results. The application's use results in an accuracy of 80%. Green and red tomatoes are the most well-known types of tomatoes. Turning tomatoes are difficult to identify because many of them are mistaken for green tomatoes.Keyword: Android; eXtreme Programming; HSV; Recognition; TomatoBuah tomat memiliki waktu kematangan relatif cepat, sehingga petani tomat harus dapat menyortir buah tomat dengan tepat yang akan didistribusikan. Pada umumnya petani menyortir buah tomat secara manual. Petani tomat juga pada umumnya sudah ahli dalam menyortir tomat secara manual, tetapi manusia memiliki banyak keterbatasan seperti lelah dan tidak fokus. Masalah tersebut dapat meyebabkan inkonsistensi dan ketidaktepatan dalam penyortirannya, sehingga dibutuhkan alat bantu untuk membantu proses peyortiran tersebut. Oleh karena itu, perlu dikembangkan sebuah aplikasi Android yang dapat membantu proses penyortiran tersebut. Alasan penggunaan Android sebagai platform karena merupakan alat yang banyak dimiliki orang pada umumnya. Algoritme LVQ digunakan sebagai algoritme pembelajaran untuk mendapatkan model terbaik dalam mengenali buah tomat. Algoritme tersebut membutuhkan fitur untuk membangun modelnya. Fitur yang digunakan adalah warna Hue, Saturation, dan Value (HSV). Aplikasi pengenalan tingkat kematangan buah tomat dikembangkan menggunakan metodologi pengembangan sistem Personal eXtreme Programming (PXP). Alat analisis yang digunakan adalah Unified Modeling Language (UML). Berdasarkan hasil pengujian, aplikasi berhasil dikembangkan pada platform Android. Penggunaan aplikasi tersebut menghasilkan akurasi sebesar 80%. Tomat yang paling banyak dikenali adalah tomat Green dan Red. Tomat Turning cukup sulit dikenali, karena tomat tersebut cukup banyak yang dikenali sebagai tomat Green.Kata Kunci: Android; eXtreme Programming; HSV; Pengenalan; Tomat

Brassinosteroids Mitigate Cadmium Effects in Arabidopsis Root System without Any Cooperation with Nitric Oxide

The heavy metal cadmium (Cd) affects root system development and quiescent center (QC)-definition in Arabidopsis root-apices. The brassinosteroids-(BRs)-mediated tolerance to heavy metals has been reported to occur by a modulation of nitric oxide (NO) and root auxin-localization. However, how BRs counteract Cd-action in different root types is unknown. This research aimed to find correlations between BRs and NO in response to Cd in Arabidopsis’s root system, monitoring their effects on QC-definition and auxin localization in root-apices. To this aim, root system developmental changes induced by low levels of 24-epibrassinolide (eBL) or by the BR-biosynthesis inhibitor brassinazole (Brz), combined or not with CdSO4, and/or with the NO-donor nitroprusside (SNP), were investigated using morpho-anatomical and NO-epifluorescence analyses, and monitoring auxin-localization by the DR5::GUS system. Results show that eBL, alone or combined with Cd, enhances lateral (LR) and adventitious (AR) root formation and counteracts QC-disruption and auxin-delocalization caused by Cd in primary root/LR/AR apices. Exogenous NO enhances LR and AR formation in Cd-presence, without synergism with eBL. The NO-signal is positively affected by eBL, but not in Cd-presence, and BR-biosynthesis inhibition does not change the low NO-signal caused by Cd. Collectively, results show that BRs ameliorate Cd-effects on all root types acting independently from NO.

Deep learning-based system development for black pine bast scale detection

The prevention of the loss of agricultural resources caused by pests is an important issue. Advances are being made in technologies, but current farm management methods and equipment have not yet met the level required for precise pest control, and most rely on manual management by professional workers. Hence, a pest detection system based on deep learning was developed for the automatic pest density measurement. In the proposed system, an image capture device for pheromone traps was developed to solve nonuniform shooting distance and the reflection of the outer vinyl of the trap while capturing the images. Since the black pine bast scale pest is small, pheromone traps are captured as several subimages and they are used for training the deep learning model. Finally, they are integrated by an image stitching algorithm to form an entire trap image. These processes are managed with the developed smartphone application. The deep learning model detects the pests in the image. The experimental results indicate that the model achieves an F1 score of 0.90 and mAP of 94.7% and suggest that a deep learning model based on object detection can be used for quick and automatic detection of pests attracted to pheromone traps.

Effects of Elevated Temperature on Root System Development of Two Lupine Species

The aim of this study was to assess the effect of elevated temperature on the growth, morphology and spatial orientation of lupine roots at the initial stages of development and on the formation of lupine root architecture at later stages. Two lupine species were studied—the invasive Lupinus polyphyllus Lindl. and the non-invasive L. luteus L. The plants were grown in climate chambers under 25 °C and simulated warming at 30 °C conditions. The angle of root curvature towards the vector of gravity was measured at the 48th hour of growth, and during a 4-h period after 90° reorientation. Root biometrical, histological measurements were carried out on 7-day-old and 30-day-old plants. The elevation of 5 °C affected root formation of the two lupine species differently. The initial roots of L. polyphyllus were characterized by worse spatial orientation, reduced growth and reduced mitotic index of root apical meristem at 30 °C compared with 25 °C. The length of primary roots of 30-day-old lupines and the number of lateral roots decreased by 14% and 16%, respectively. More intense root development and formation were observed in non-invasive L. luteus at 30 °C. Our results provide important information on the effect of elevated temperature on the formation of root architecture in two lupine species and suggest that global warming may impact the invasiveness of these species.

Digital discretion and public administration in Africa: Implications for the use of artificial intelligence

The digitalisation of public services is implicated in fundamental changes to how civil servants make decisions and exercise discretion. Most significant has been a shift in responsibility away from ‘street-level bureaucrats’ to ‘system-level bureaucrats’; a technology-savvy community of officials, consultants and private enterprises involved in the design of information technology systems and associated rules. The relatively recent inclusion of artificial intelligence (AI) and data-driven algorithms raises new questions about the conflation of policy formulation and system development activities, but also intensifies concerns about the epistemic dependence and policy alienation of public officials. African public administrations are in an especially vulnerable position with respect to the adoption of AI, and so this chapter seeks to synthesise lessons from previous digital implementations on the continent, and considers the implications for AI use. Four broad considerations emerge from the review of literature: Integrity of recommendations provided by decision-support systems, including how they are influenced by local organisational practices and the reliability of underlying infrastructures; Inclusive decision-making that balances the (assumed) objectivity of data-driven algorithms and the influence of different stakeholder groups; Exception and accountability in how digital and AI platforms are funded, developed, implemented and used; and a Complete understanding of people and events through the integration of traditionally dispersed data sources and systems, and how policy actors seek to mitigate the risks associated with this aspiration.

Mitigating Motion Sickness in Automated Vehicles with Vibration Cue System

<p>Motion sickness is very common in road transport. To guarantee ride comfort and user experience, there is an urgent need for effective solutions to motion sickness mitigation in semi- and fully-automated vehicles. Considering both effectiveness and user-friendliness, a vibration cue system is proposed to inform passengers of the upcoming vehicle movement through tactile stimulation. By integrating the motion planning results from automated driving algorithms, the vibration cueing timing and patterns are optimized with the theory of motion anticipation. Using a cushion-based prototype of vibration cue system, 20 participants were invited to evaluate this solution in two conditions of driving simulator experiments. Results show that with the proposed vibration cue system, it could also help participants to comprehend the cues and to generate motion anticipation. The participants’ motion sickness degrees were significantly lowered. This research may serve as one foundation for the detailed system development in practical applications.</p><p>(This article has been accepted for publication in <i>Ergonomics</i>, published by Taylor & Francis.)</p><br>