Computer Science

Internet censorship, whether imposed by governments seeking to control the flow of information available to their citizens, or by parental figures wishing to shield their "parishioners" from the dangers of the Internet, or in organizations trying to restrict the Internet usage within their networking territory. Numerous applications are readily accessible for the average user to aid-in bypassing Internet censorship. Several technologies and techniques are associated with the formation of these applications, whereas, each of these applications deploys its unique mechanism to circumvent Internet censorship. Using anti-censorship applications in the work environment can have a negative impact on the network, leading to excessive degradation in the bandwidth, immense consumption of the Internet data usage capacity and possibly open the door for security breaches. Triumphing the war on anti-censorship applications has become more difficult to achieve at the network level due to the rapid updates and the adopted new technologies to circumvent censorship. In this study, a comprehensive overview on Internet censorship and anti-censorship applications is provided by analyzing Ultrasurf behavior, classifying its traffic patterns and proposing a behavioral-based solution that is capable of detecting and preventing the Ultrasurf traffic at the network level.

The impending energy crisis has driven up the cost of electricity at an exponential rate. Managing electric consumption thus has become a very crucial task especially for home consumers. In this paper we present EnerPlan, a non-intrusive method to aid consumers to reduce their energy cost by advising them a consumption plan for their devices. Our system builds consumer classes based on regional statistical data. Using these classes a target consumer's device load and distribution is inferred and this inferred data is used to construct a device usage plan which when followed can reduce the electric bill of the user. We use expert-based and auto-generated fuzzy rules to construct our system. Results of the two different methods are presented and compared. Our results demonstrate that the data prepared using the proposed approach can be used to save electricity. The users can reduce their electricity bills by following the plans made by EnerPlan.

This paper describes how Crystal, a language based on familiar mathematical notation and lambda calculus, addresses the issues of programmability and performance for parallel supercomputers. Some scientifc programmers and theoreticians may ask, "What is new about Crystal?" or "How is it different from existing functional languages?" The answers lie in its model of parallel computation and a theory of parallel program optimization, and we examine this in the text to follow. We illustrate the power of our approach with benchmarks of compiled parallel code from Crystal source. The target machines are hypercube multiprocessors with distributed memory, on which it is considered difficult for functional programs to achieve high efficiency.

This paper describes how Crystal, a language based on familiar mathematical notation and lambda calculus, addresses the issues of programmability and performance for parallel supercomputers. Some scientifc programmers and theoreticians may ask, "What is new about Crystal?" or "How is it different from existing functional languages?" The answers lie in its model of parallel computation and a theory of parallel program optimization, and we examine this in the text to follow. We illustrate the power of our approach with benchmarks of compiled parallel code from Crystal source. The target machines are hypercube multiprocessors with distributed memory, on which it is considered difficult for functional programs to achieve high efficiency.

In the latest research, the application of three-dimensional electromagnetic tracking system (ETS) for biomechanical and kinesiologic research of cervical spine has been demonstrated. Little information is available regarding coupled movements that accompany the primary movement in vivo. The purpose of the present study was to investigate the feasibility of quantifying the primary movements of the cervical spine and their corresponding coupled motions in healthy subjects by a three-dimensional ETS. Twenty healthy subjects (10 males and 10 females) participated in the study. Cervical extension, flexion, side bending, rotation in neutral position, and rotation in a position of full cervical flexion were analyzed via ETS. All measurements were performed actively except for rotation in a position of full cervical flexion. According to our results, the high intraclass correlation coefficient (ICC (2, 1)) values (greater than 0.791) suggested that ETS is appropriate for measuring primary ...

Qualitative research is an appropriate method for obtaining insight into situations and problems when a researcher has little knowledge concerning a research question. Applying to a cultural context of health and illness, this method is commonly used for providing in-depth description of cultural beliefs and local knowledge related to health issues, or for exploring the reasons for certain health seeking behaviours adopted by research informants. This study provides a pragmatic approach in examining the various stages of a qualitative data collection process pertaining to the aboriginal people or the Orang Asli of Malaysia. The research was conducted in three selected Orang Asli villages in the states of Selangor, Pahang and Perak of Peninsular Malaysia. A total of 55 in-depth interviews were successfully recorded during the fieldwork duration of July 2013 to January 2015. Employing face-to-face in-depth interviews and non-participant observations, the research collected data with regard to health and health seeking behaviors of the Orang Asli. The primary data were used to illustrate how various qualitative data collection methods could be used to facilitate the data collection process. Several concepts employed in data collection such as theoretical sensitivity, triangulation and verification were also elaborated.

Discussions on socially and culturally dominant values, beliefs and practices pertaining to patient’s health and culture are not isolated but integral to the practice of contemporary clinical medicine. Medical anthropologists play a unique role in redefining and repositioning the application of CAM in biomedical sciences. This article addresses the current state of knowledge regarding the distinction between medical anthropology and complementary and alternative medicine (CAM). Participant observations of, and in-depth interviews with ten Malaysian Chinese women cancer survivors were carried out to study their CAM use during and after cancer treatment. The results provide insights about the patterns of CAM use as well as the social and cultural factors under-pining the choice of CAM used by cancer survivors before and after treatment. The survivors’ preference for CAM use during cancer diagnosis was found to be influenced by their values, beliefs, and practices with respect to five ...

Perumahan yang sempurna ialah yang dapat memenuhi keperluan penghuni, memberi kesejahteraan kepada isi rumah dan seterusnya memacu kepada peningkatan kualiti hidup. Program Perumahan Rakyat (PPR) merupakan program pembangunan rumah untuk rakyat di kawasan bandar yang tidak mempunyai kediaman sendiri sama ada untuk disewa atau dimiliki mengikut kawasan. Program ini memberi manfaat kepada penghuni bandar untuk menjalani kehidupan yang selesa seterusnya dapat mencapai kesejahteraan hidup. Namun terdapat tiga isu sosioekonomi dalam pelaksanaan skim PPR ini iaitu perpaduan, sosial dan ekonomi. Justeru, tujuan penulisan artikel ini untuk membincangkan impak sosioekonomi dan politik terhadap Program Perumahan Rakyat (PPR) Lembah Subang, Selangor. Kajian ini menggunakan metodologi secara kuantitatif melalui penggunaan instrumen borang soal selidik bagi mengumpul data daripada responden. Seramai 360 orang responden terlibat dan rujukan terhadap data sekunder iaitu artikel jurnal, kertas pers...

Qualitative research is an appropriate method for obtaining insight into situations and problems when a researcher has little knowledge concerning a research question. Applying to a cultural context of health and illness, this method is commonly used for providing in-depth description of cultural beliefs and local knowledge related to health issues, or for exploring the reasons for certain health seeking behaviours adopted by research informants. This study provides a pragmatic approach in examining the various stages of a qualitative data collection process pertaining to the aboriginal people or the Orang Asli of Malaysia. The research was conducted in three selected Orang Asli villages in the states of Selangor, Pahang and Perak of Peninsular Malaysia. A total of 55 in-depth interviews were successfully recorded during the fieldwork duration of July 2013 to January 2015. Employing face-to-face in-depth interviews and non-participant observations, the research collected data with r...

While most cultures are a heritage of many nations most are alien and are adopted to achieve certain goals. Malawi is endowed with a rich culture but unfortunately reading is not among them. A reading nation is an informed and knowledgeable society that can contribute positively to economic transformation of its country and efforts being made in adopting the culture of reading are a manifestation. It is not surprising that the now so familiar phrase "developing a reading culture" has found itself a place amongst the media's daily vocabulary. The development of this culture should start at an early stage of childhood and nurture it to adulthood and in the process building a literate nation that can transform itself into an informed and knowledgeable society able to play their rightful role in the global village. Poor delivery of information services in the rural areas is, however, contributing highly to lower levels of educational standards and high levels of illiteracy. Further to this, the digital divide between the developed and developing nations is putting the rural masses at a great disadvantage in as far as access to relevant and timely information is concerned. A reading culture if developed at a tender age will ensure that pupils/students are well equipped to excel in their studies thereby improving the standards of education among the rural masses. In addition, deliberate efforts should be made to empower the rural masses with literacy skills that will improve their livelihoods. Innovative solutions should also be explored to provide low-cost means of accessing Information Communications Technologies which creates economic, political and social empowerment for the rural people in the developing world.

The COVID-19 pandemic compelled educational institutions to swiftly shift from conventional classroom instruction to remote and hybrid learning models, prompting the widespread adoption of digital tools and mobile apps for online education. As the world emerges from this crisis, there's a growing interest in exploring innovative ways to utilize multimedia tools for improved engagement, accessibility, and learning outcomes. Multimedia encompasses diverse content formats, including videos, interactive simulations, and online collaboration tools, offering various avenues to enhance the process of teaching and learning. This research paper investigates the role of multimedia tools in education, focusing on their utilization, and the challenges and barriers associated with their integration into classroom settings within the Jakarta District of Indonesia's higher education sector. Qualitative research methods were employed, involving interviews, observations, and documentation analysis conducted at a higher education institution in Bekasi District, Indonesia. Interviews were conducted with the educators (providing learning materials). The study discovered that the incorporation of multimedia tools, such as images, videos, animations, and interactive platforms like Kahoot, enhances students' focus, interest, and engagement, consequently improving memory retention and comprehension. The research also identified various challenges in successfully incorporating multimedia tools into the field of education, including resource limitations, digital literacy gaps, connectivity issues, lecturer's unfamiliarity with technology, lack of motivation, inadequate digital tools, subscription costs, quality concerns, and potential distractions. The paper offers practical recommendations for successful multimedia integration in classrooms, emphasizing clear guidelines, brief video content, specific tasks for students, thought-provoking questions, early material distribution, and guidance in using ICT.

This study investigates the effectiveness of advanced query optimization techniques in SQL databases, focusing on multi-level indexing, query rewriting, and dynamic query execution plans. The research employs a qualitative approach, gathering data from a variety of SQL databases characterized by large datasets typical of big data environments. Through structured interviews, focus groups, and observational methods, insights from database administrators highlight the practical benefits and challenges associated with implementing these techniques. The findings reveal significant improvements in query performance, with multi-level indexing reducing data retrieval times by approximately 40%, query rewriting decreasing execution times by 35%, and dynamic query execution plans enhancing resource utilization efficiency by 25%. These techniques were also praised for their ease of use, adaptability to different data types and query complexities, and overall reliability. This study contributes to the existing body of knowledge by providing a comprehensive analysis of the practical applications and performance enhancements offered by advanced query optimization methods in SQL databases, underscoring their value in managing large-scale, dynamic data environments.

COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3-chymotrypsin-like cysteine protease (3CLpro) enzyme is the vital molecular target against the SARS-CoV-2. Therefore, in the present study, 1528 anti-HIV1compounds were screened by sequence alignment between 3CLpro of SARS-CoV-2 and avian infectious bronchitis virus (avian coronavirus) followed by machine learning predictive model, drug-likeness screening and molecular docking, which resulted in 41 screened compounds. These 41 compounds were re-screened by deep learning model constructed considering the IC50 values of known inhibitors which resulted in 22 hit compounds. Further, screening was done by structural activity relationship mapping which resulted in two structural clefts. Thereafter, functional group analysis was also done, where cluster 2 showed the presence of several essential functional groups having pharmacological impo...

The increasing digitalization of industrial and healthcare environments has heightened the importance of cybersecurity to protect sensitive data and ensure the integrity of data management systems. This article examines advanced cybersecurity protocols designed to address the unique challenges faced by these sectors. It explores various threats, including ransomware, phishing, and insider threats, as well as system vulnerabilities found in legacy systems, IoT and medical devices, and cloud computing. The implementation of robust security measures such as encryption, multi-factor authentication, and intrusion detection systems is analyzed in depth. Through a comprehensive review of existing research and real-world case studies, including those of Maersk Line, Memorial Health System, and Norsk Hydro, this study provides insights into effective strategies for enhancing cybersecurity in industrial and healthcare settings. The findings highlight the critical role of these measures, alongside regular staff training and awareness programs, in safeguarding data management systems. By leveraging advanced technologies and proactive security practices, organizations can better protect their sensitive data against evolving cyber threats.

It was moved, seconded and passed by unanimous voice vote to accept the April 28, 2009 minutes as presented and the May 19, 2009 correcting the date of the meeting on the minutes. ___________________________________________________________________________ Ms. Rousseau raised a question regarding the handling of minutes and a brief discussion followed between Ms. Rousseau and Chairman LeBlanc. Ms. Rousseau felt that they were the only ones who really knew what they said and they had no idea what an individual typed into the minutes. She felt a responsibility to the citizens of Portsmouth to make sure they get the most accurate minutes possible and that minutes should not be approved without the Board seeing the changes made. Chairman LeBlanc noted that the minutes had been approved as corrected and the corrections were made in accordance with the tape that was made of the meeting. The corrected minutes could be viewed in city hall or on line. He saw no reason to change the protocols that had been place for over 20 years ____________________________________________________________________________ B. Request for Extension -24 Central Avenue Mr. Grasso made a motion to grant an extension of the Special Exception through December 31, 2009, which was seconded by Mr. Parrott. Mr. Grasso stated that he remembered when the applicant had appeared and they had discussed that the initial timeframe would not be enough to complete the construction. He found this to be a reasonable request and Mr. Parrott concurred.

Sleep is a basic human need, making up around one-third of our lives and being essential to the recovery of our physical well-being and general standard of living. However, poor sleep quality can interfere with these critical restorative processes, leading to disorders such as apnea and insomnia. These conditions not only impair daily performance but also have long-term health consequences. Furthermore, the challenges imposed by modern lifestyles have increased the prevalence of these sleep disorders, emphasizing the need for effective diagnostic tools. This research aims to harness the capabilities of Machine Learning (ML), specifically the Random Forest algorithm, to detect and analyze patterns indicative of sleep disorders in collected data sets. Random Forest is particularly suited for this task due to its ability to manage complex data sets by building multiple decision trees, thus creating a comprehensive and robust model for classifying sleep disorders. The findings of the study are promising, showing that the Random Forest algorithm can achieve a high level of accuracy in sleep disorder detection. The model demonstrated a test accuracy rate of 97.33%, with a precision of 96%, and a recall rate of 100%. Additionally, it achieved an F1-Score of 98% and a Kappa Score of 0.945, validating the reliability of this algorithm in producing precise classifications. This research offers significant insights into the patterns of sleep disorders and contributes to the development of targeted interventions aimed at improving sleep quality. Ultimately, this could significantly enhance the quality of life for individuals suffering from sleep disorders.

E-Government merupakan suatu upaya untuk memanfaatkan teknologi informasi dan komunikasi yang dimaksudkan untuk meningkatkan efisiensi, efektivitas, transparansi dan akuntabilitas penyelenggaraan pemerintah dan pelayanan publik. Pengembangan E-Government di Indonesia semakin bergulir dan berjalan seperti penerapan E-Budgeting, E-Procurement, E-Audit, E-Catalog, E-Payment, E-Controlling bahkan hingga E-Health. Kini proses rekrutmen Aparatur Sipil Negara (ASN) pun bisa dilakukan melalui online untuk memudahkan proses pendaftaran dan memilih instansi. Sejauh ini, masih terdapat beberapa kendala yang dialami para pelamar CPNS dalam penggunaan website SSCN. Oleh karena itu, untuk mengetahui tingkat kesuksesan website SSCN dimata pengguna, maka perlu dilakukan pengukuran kesuksesan website dengan menggunakan model DeLone dan McLean (2003). Data yang didapat kemudian diolah dan didapatkan 201 responden dengan data valid. Diperoleh hasil yang menunjukkan terdapat beberapa variabel berpengar...

Puji dan syukur Kami panjatkan kehadirat Allah SWT yang senantiasa melimpahkan rahmat Nya kepada kita semua, serta sholawat dan salam Kami haturkan kepada Nabi Muhammad SAW. Alhamdulillah berkat rizki dan kesempatan yang diberikan oleh Allah SWT, Kami telah menyelesaikan Sistem Informasi Kegiatan Unit Akreditasi BAAK (SIKUAT BAAK) yang dibangun untuk memenuhi kebutuhan pimpinan untuk mengontrol dan mengawasi kegiatan kerja para pegwai dalam melakukan tugasnya sehari-hari (job desc). Sampai dengan saat ini, sistem informasi ini sedang Kami kembangkan ke versi selanjutnya dengan fasilitas modul-modul yang lebih lengkap lagi. Akhir kata, semoga sistem informasi yang kami bangun bermanfaat bagi para pemakainya guna perencanaan maupun pengambilan keputusan.

Multivariate measurements of human brain white matter (WM) with diffusion MRI (dMRI) provide information about the role of WM in a variety of cognitive functions and in brain health. Statistical models take advantage of the regularities in these data to make inferences about individual differences. For example, dMRI data provide the basis for accurate brain-age models -models that predict the chronological age of participants from WM tissue properties. Deep learning (DL) models are powerful machine learning models, which have been shown to provide benefits in many multivariate analysis settings. We investigated whether DL would provide substantial improvements for brain-age models based on dMRI measurements of WM in a large sample of children and adolescents. We found that some DL models fit the data better than a linear baseline, but the differences are small. In particular, recurrent neural network architectures provide up to ~6% improvement in accuracy. This suggests that information about WM development is mostly accessible with linear models, and does not require the additional invariance and non-linearity offered by DL models. However, in some applications this incremental improvement may prove critical. We provide open-source software that fits DL models to dMRI data ().

Multivariate measurements of human brain white matter (WM) with diffusion MRI (dMRI) provide information about the role of WM in a variety of cognitive functions and in brain health. Statistical models take advantage of the regularities in these data to make inferences about individual differences. For example, dMRI data provide the basis for accurate brain-age models – models that predict the chronological age of participants from WM tissue properties. Deep learning (DL) models are powerful machine learning models, which have been shown to provide benefits in many multivariate analysis settings. We investigated whether DL would provide substantial improvements for brain-age models based on dMRI measurements of WM in a large sample of children and adolescents. We found that some DL models fit the data better than a linear baseline, but the differences are small. In particular, recurrent neural network architectures provide up to ∼6% improvement in accuracy. This suggests that inform...

We propose a time-dependent variant of the restoration routing problem scheduling restoration tasks for each crew given a limited time horizon. The model provides a feasible initial solution for real-world restoration crew routing problems. We also acknowledge the effect of topological characteristics on the network resilience enhancement during the restoration process.

En este artículo se presenta el diseño, construcción y funcionamiento de un dispositivo móvil de detección de gases o Nariz electrónica, con capacidad de ser controlado y monitoreado en tiempo real de manera remota vía WiFi. En primer lugar, se presenta los componentes principales de la nariz electrónica, como lo son sensores de gas y las tarjetas controladoras, quienes permiten la comunicación y el monitoreo de forma inalámbrica y en tiempo real. Seguido tenemos el diseño mecánico conformado por servomotores, ruedas y chasis, que permite el acople de la nariz electrónica y le brinda movilidad y soporte. Posteriormente se incluye información referente al contenido de la programación de los diferentes componentes, software utilizado y su funcionamiento. Finalmente se plantea la posibilidad de utilizar este dispositivo como una solución de bajo costo al problema que representa para el hombre la medición de diferentes concentraciones de gases, ya sea en lugares desconocidos o difíciles de acceder y que presenten algún tipo de riesgo a la integridad individual o colectiva.

This paper reviews the literature of Balanced Scorecard (BSC) as a strategic performance measurement tool. The research concerning the effectiveness of BSC indicate that BSC is a useful tool for communicating strategy, strategic learning and developing organizational culture. However, related research also shows that the implementation of BSC is not associated with economic benefit particularly for short-term period. This suggests that the adoption of BSC need a careful inquiry by the organization and the organization should not accept it as a 'generic' solution as a performance measurement tool.

The use of image processing schemes as part of the security systems have been increasing, to detect, classify as well as to tract object and human motion with a high precision. To this end several approaches have been proposed during the last decades using image processing techniques, because computer vision let us to manipulated digital image sequences to extract useful information contained in a video stream. In this paper we present a motion detection algorithm using the movement vectors estimation which are subsequently filtered to obtain better information about real motion into a given scenes. Experimental results show that the accuracy of proposed system.

Kemajuan teknologi dunia telah membawa banyak perubahan dalam dunia pendidikan. Tujuan kajian ini adalah untuk meninjau inovasi pengajaran bersepadu dan strategi pengajaran dan pembelajaran di era Revolusi Industri 4.0. Secara khususnya objektif kajian adalah mengenalpasti keperluan penggunaan inovasi dalam pengajaran, pembelajaran dan pemudahcaraan. Metodologi kajian ini adalah berbentuk kepustakaan. Penggunaan teknologi digital dapat mengubah suasana pengajaran dan pembelajaran yang lebih moden dan menarik berbanding kaedah tradisional. Hasil kajian mendapati bahawa strategi pengajaran dan pembelajaran bersepadu yang digunakan di era Revolusi Industri 4.0 adalah berteraskan empat elemen utama merupakan teras pendidikan bersepadu dalam strategi aplikasi iaitu creativity , reflectivity , reciprocity dan responsibility .  Hasil kajian juga mendapati penggunaan teknologi digital seperti pembelajaran teradun ( blended learning ), i-Folio dan Massive Open Online Courses (MOOC) membantu ...

Several regularization terms, some of them widely applied to neural networks, such as weight decay and weight elimination, and some others new, are tested when applied to networks with a small number of connections handling continuous variables. These networks are found when using additive algorithms that work by adding processors. First the different methods and their rationale is presented. Then, results are shown, first for curve fitting problems. Since the network constructive algorithm is being used for system modeling, results are also shown for a toy problem that includes recurrency buildup, in order to test the influence of the regularization terms in this process. The results show that this terms can be of help in order to detect unnecessary connections. No clear winner has been found among the presented terms in these tests.

IS Success Model dan TAM di bawah bimbingan Fitroh dan Nidaul Hasanati. Sistem informasi akademik (SIAKAD) merupakan sistem informasi akademik berbasis web pada Universitas Sahid Jakarta yang saat ini digunakan untuk membantu penyelenggaraan kegiatan pengisian Kartu Rencana Studi (KRS), pengambilan Kartu Hasil Studi (KHS), penjadwalan kuliah, validasi dosen penasihat akademik, informasi beasiswa, informasi pembayaran kuliah, dan pendaftaran wisuda. Namun, saat ini belum diketahui sejauh mana keberhasilan dari SIAKAD yang telah diimplementasikan dan adanya permasalahan berupa keinginan Universitas Sahid Jakarta membangun sistem informasi manajemen kampus yang handal dan go online, serta menciptakan manajemen sistem kampus yang terkomputerisasi sehingga dapat dirasakan manfaatnya oleh civitas akademik, penambahan fitur terhadap SIAKAD sebelum diajukan terhadap SEVIMA terlebih dahulu pihak Universitas Sahid Jakarta perlu mengetahui berdasarkan kebutuhan yang diperlukan user. Salah satu faktor penentu keberhasilan sebuah sistem yang diterapkan adalah dari sisi persepsi penggunanya. Tujuan penelitian ini adalah untuk mendapatkan dan mengetahui variabel yang signifikan terhadap keberhasilan Sistem informasi akademik dengan menggunakan pendekatan DeLone and McLean IS Success Model dan TAM yang diadaposi dari penelitian Laksono (2017) mengkombinasikan hubungan jalur variabel Service Quality terhadap Perceived Ease of Use karena menurut kualitas yang diberikan oleh sebuah website dapat mempengaruhi bagaimana tingkat kemudahan dalam penggunaannya. Penelitian dilakukan dengan pendekatan kuantitatif, penyebaran kuesioner secara online dengan 30 pernyataan, dan analisis data demografis dengan Microsoft Excel 2013 sedangkan analisis PLS-SEM dengan SmartPLS 3.2.8. Hasilnya dari 12 jalur hubungan variabel, 3 hubungan jalur variabel dinyatakan tidak signifikan dan ditolak karena nilai path coefficient dan T-test (System Quality, Information Quality) kurang dari 0.1 dan 1.96, sedangkan 9 hubungan jalur variabel dinyatakan signifikan dan diterima karena nilai path coefficient dan T-test dari kesembilan jalur hubungan variabel tersebut berada di ambang batas yaitu 0.1 dan 1.96. Hasil penelitian ini diharapkan dapat menjadi menjadi salah satu bahan pertimbangan dalam pengambilan keputusan pihak penyedia layanan sistem informasi akademik untuk dapat diterapkan lebih maksimal.

This document describes the fundamental criteria in the design of an automated Cartesian table with three XYZ axes with an interchangeable head for plasma and oxyfuel cutting, as well as the selection of the processes implemented for its construction. For this purpose, the table is divided into four fundamental parts: X axis, Y axis, Z axis and control system. As it is a table for a high precision process such as plasma, a study of machine errors is carried out using the Denavit -Hartenberg method and the errors associated with deformation using simulation software. To conclude, it is determined that with the design detailed in this document, it is possible to build a CNC table with high precision and low cost.

Arti cial Life and the more general area of Complex Systems does not have a uni ed theoretical framework although most theoretical work in these areas is based on simulation. This is primarily due to an insu cient representational power of the classical mathematical frameworks for the description of discrete dynamical systems of interacting objects with often complex internal states. Unlike computation or the numerical analysis of di erential equations, simulation does not have a well established conceptual and mathematical foundation. Simulation is an arguable unique union of modeling and computation. However, simulation also quali es as a separate species of system representation with its own motivations, characteristics, and implications. This work outlines how simulation can be rooted in mathematics and shows which properties some of the elements of such a mathematical framework has. The properties of simulation are described and analyzed in terms of properties of dynamical systems. It is shown how and why a simulation produces emergent behavior and why the analysis of the dynamics of the system being simulated always is an analysis of emergent phenomena. Indeed, the single fundamental class of properties of the natural world that simulation will open to new understanding, is that which occurs only in the dynamics produced by the interactions of the components of complex systems. Simulation o ers a synthetic, formal framework for the experimental mathematics of representation and analysis of complex dynamical systems. A notion of a universal simulator and the de nition of simulatability is proposed. This allows a description of conditions under which simulations can distribute update functions over system components, thereby determining simulatability. The connection between the notion of simulatability and the notion of computability is de ned and the concepts are distinguished. The basis of practical detection methods for determining e ectively non-simulatable systems in practice is presented. The conceptual framework is illustrated through examples from molecular self-assembly end engineering.

In this paper we describe a multiagent simulation model of human behavior in the aftermath of a hypothetical, large-scale, human-initiated crisis in the center of Washington D.C. Prior studies of this scenario have focused on modeling the physical effects of the attack, such as thermal and blast effects, prompt radiation, and fallout. Casualty and mortality estimates have been obtained by assuming a spatially static human population, ignoring human behavioral response to the event.We build a simulation of a behaving human population and its interaction with various interdependent infrastructures, to try to understand how human response to such an event would change outcomes, and also how modeling this response would enable us to develop new perspectives on planning for this event.Here we present details of the simulation, focusing on the agent design and multiagent interaction, and present initial results on how rapid restoration of communication could alter behavior beneficially.

The COVID-19 global outbreak represents the most significant epidemic event since the 1918 influenza pandemic. Simulations have played a crucial role in supporting COVID-19 planning and response efforts. Developing scalable workflows to provide policymakers quick responses to important questions pertaining to logistics, resource allocation, epidemic forecasts and intervention analysis remains a challenging computational problem. In this work, we present scalable high performance computing-enabled workflows for COVID-19 pandemic planning and response. The scalability of our methodology allows us to run fine-grained simulations daily, and to generate county-level forecasts and other counter-factual analysis for each of the 50 states (and DC), 3140 counties across the USA. Our workflows use a hybrid cloud/cluster system utilizing a combination of local and remote cluster computing facilities, and using over 20,000 CPU cores running for 6–9 hours every day to meet this objective. Our st...

Given a random RNA secondary structure, S, we study RNA sequences having fixed ratios of nucleotides that are compatible with S. We perform this analysis for RNA secondary structures subject to various base-pairing rules and minimum arc- and stack-length restrictions. Our main result reads as follows: in the simplex of nucleotide ratios, there exists a convex region, in which, in the limit of long sequences, a random structure asymptotically almost surely (a.a.s.) has compatible sequence with these ratios and outside of which a.a.s. a random structure has no such compatible sequence. We localize this region for RNA secondary structures subject to various base-pairing rules and minimum arc- and stack-length restrictions. In particular, for GC-sequences (GC denoting the nucleotides guanine and cytosine, respectively) having a ratio of G nucleotides smaller than 1/3, a random RNA secondary structure without any minimum arc- and stack-length restrictions has a.a.s. no such compatible se...

The complexities of social and technological policy domains, such as the economy, the environment, and public health present challenges that require a new approach to modeling and decision making. The information required for effective policy and decision making in these complex domains is massive in scale, fine-grained in resolution, and distributed over many data sources. Thus, one of the key challenges in building systems to support policy informatics is information integration. We describe our approach to this problem, and how we are building a multi-theory, multi-actor, multi-perspective system that supports continual data uptake, state assessment, decision analysis, and action assignment based on large-scale high-performance computing infrastructures. Our simulation-based approach allows rapid course-of-action analysis to bound variances in outcomes of policy interventions, which in turn allows the short time-scale planning required in response to emergencies such as epidemic ...

We present a generic mobility and traffic generation framework that can be incorporated into a tool for modeling and simulating large scale ad hoc networks. Three components of this framework, namely a mobility data generator (MDG), a graph structure generator (GSG) and an occlusion modification tool (OMT) allow a variety of mobility models to be incorporated into the tool. The MDG module generates positions of transceivers at specified time instants. The GSG module constructs the graph corresponding to the ad hoc network from the mobility data provided by MDG. The OMT module modifies the connectivity of the graph produced by GSG to allow for occlusion effects. With two other modules, namely an activity data generator (ADG) which generates packet transmission activities for transceivers and a packet activity simulator (PAS) which simulates the movement and interaction of packets among the transceivers, the framework allows the modeling and simulation of ad hoc communication networks. The design of the framework allows a user to incorporate various realistic parameters crucial in the simulation. We illustrate the utility of our framework through a comparative study of three mobility models. Two of these are synthetic models (random waypoint and exponentially correlated mobility) proposed in the literature. The third model is based on an urban population mobility modeling tool (TRANSIMS) developed at the Los Alamos National Laboratory. This tool is capable of providing comprehensive information about the demographics, mobility and interactions of members of a large urban population. A comparison of these models is carried out by computing a variety of parameters associated with the graph structures generated by the models. There has recently been interest in the structural properties of graphs that arise in real world systems. We examine two aspects of this for the graphs created by the mobility models: change associated with power control (range of transceivers) and variation in time as transceivers move in space.

Human behavior, social networks, and the civil infrastructures are closely intertwined. Understanding their co-evolution is critical for designing public policies and decision support for disaster planning. For example, human behaviors and day to day activities of individuals create dense social interactions that are characteristic of modern urban societies. These dense social networks provide a perfect fabric for fast, uncontrolled disease propagation. Conversely, people's behavior in response to public policies and their perception of how the crisis is unfolding as a result of disease outbreak can dramatically alter the normally stable social interactions. Effective planning and response strategies must take these complicated interactions into account. In this chapter, we describe a computer simulation based approach to study these issues using public health and computational epidemiology as an illustrative example. We also formulate game-theoretic and stochastic optimization problems that capture many of the problems that we study empirically.

We consider the bilateral contract satisfaction problem arising from electrical power networks due to the proposed deregulation of the electric utility industry in the USA. Given a network § and a set (or multiset) of pairs of vertices (contracts) with associated demand functions that reflect the amount of flow which needs to be sent between the pairs of vertices, the goal is to find the maximum number of simultaneously satisfiable contracts. Four different algorithms for bilateral contract satisfaction problems are considered: (i) SMALLEST-FIRST HEURISTIC (ii) LARGEST-FIRST HEURISTIC (iii) RANDOM-ORDER HEURISTIC and (iv) ILP-RANDOMIZED ROUNDING: an integer linear programming based approximation algorithm with proven performance guarantee in restricted cases. The main focus of the paper is to study how the heuristics performed in fairly realistic settings. For this purpose we used an approximate electrical power network from Colorado. From our preliminary analysis, it appears that although the first three heuristic algorithms do not have a worst-case guarantee, they outperform the theoretically better ILP-RANDOMIZED ROUNDING algorithm. We also tested the algorithm on four types of scenarios that are likely to occur in a deregulated marketplace. The empirical results show that the networks that are adequate in regulated marketplace might not be adequate for satisfying all the bilateral contracts in a deregulated industry. Our studies indicate that simple clearing mechanisms that are currently in use in many of the power markets are computationally fast and near-optimal in their use of network capacity; also, a linear programming upper bound on the quality of any solution, turns out to be a very good bound in practice. ¨Basic and Applied Simulation Sciences, (D-2), and Computer and Computational Science (CCS-3),

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Large scale microscopic (i.e. vehicle-based) traffic simulations pose high demands on computational speed in at least two application areas: (i) real-time traffic forecasting, and (E) long-term planning applications (where repeated "looping" between the microsimulation and the simulated planning of individual person's behavior is necessary). As a rough number, a real-time simulation of an area such as Los Angeles (ca. 1 million travellers) will need a computational speed of much higher than 1 million aparticle" (= vehicle) updates per second. This paper reviews how this problem is approached in different projects and how these approaches are dependent both on the specific questions and on the prospective user community. The approaches reach from highly parallel and vectorizable, single-bit implementations on parallel supercomputers for Statistical Physics questions, via more realistic implementations on coupled workstations, to more complicated driving dynamics implemented again on parallel supercomputers.

A simulation is collection of agents that, according to some schedule, are making decisions based on information about other agents in that collection. In this paper we present a class of dynamical systems called Sequential Dynamical Systems (SDS) that was developed to capture these key features of computer simulations. Here, as an example of the use of SDS, we demonstrate how one can obtain information about a simulation by a factorization into smaller simulations.

Given an alphabet Σ, a (directed) graph G whose edges are weighted and Σ-labeled, and a formal language L ⊆ Σ * , the formal-language-constrained shortest/simple path problem consists of finding a shortest (simple) path p in G complying with the additional constraint that l(p) ∈ L. Here l(p) denotes the unique word obtained by concatenating the Σ-labels of the edges along the path p. The main contributions of this paper include the following: (1) We show that the formal-language-constrained shortest path problem is solvable efficiently in polynomial time when L is restricted to be a context-free language (CFL). When L is specified as a regular language we provide algorithms with improved space and time bounds. (2) In contrast, we show that the problem of finding a simple path between a source and a given destination is NP-hard, even when L is restricted to fixed simple regular languages and to very simple classes of graphs (e.g., complete grids). (3) For the class of treewidth-bounded graphs, we show that (i) the problem of finding a regular-language-constrained simple path between source and destination is solvable in polynomial time and (ii) the extension to finding CFL-constrained simple paths is NP-complete. Our results extend the previous results in [SIAM

We consider the problem of determining the maximum capacity of the media access (MAC) layer in wireless ad hoc networks. Due to spatial contention for the shared wireless medium, not all nodes can concurrently transmit packets to each other in these networks. The maximum number of possible concurrent transmissions is, therefore, an estimate of the maximum network capacity, and depends on the MAC protocol being used. We show that for a large class of MAC protocols based on virtual carrier sensing using RTS/CTS messages, which includes the popular IEEE 802.11 standard, this problem may be modeled as a maximum Distance-2 matching (D2EMIS) in the underlying wireless network: Given a graph ( ), find a set of edges such that no two edges in are connected by another edge in . D2EMIS is NP-complete. Our primary goal is to show that it can be approximated efficiently in networks that arise in practice. We do this by focusing on an admittedly simplistic, yet natural, graph-theoretic model for ad hoc wireless networks based on disk graphs, where a node can reach all other nodes within some distance (nodes may have unequal reach distances). We show that our approximation yields good capacity bounds. Our work is the first attempt at characterizing an important "maximum" measure of wireless network capacity, and can be used to shed light on previous topology formation protocols like Span and GAF that attempt to produce "good" or "capacity-preserving" topologies, while allowing nodes to alternate between sleep and awake states. Our work shows an efficient way to compute an upper bound on maximum wireless network capacity, thereby allowing topology formation algorithms to determine how close they are to optimal. We also outline a distributed algorithm for the problem for unit disk graphs, and briefly discuss extensions of our results to: 1) different node interference models; 2) directional antennas; and 3) other transceiver connectivity structures besides disk graphs.

We build an agent based computational framework to study large commodity markets. A detailed representation of the consumers, producers and the market is used to study the micro level behavior of the market and its participants. The user can control players' preferences, their strategies, assumptions of the model, its initial conditions, market elements and trading mechanisms. The first part of the paper describes the computational framework and its three main modules. The later part describes a case study that examines the decentralized market in detail, specifically the computational options available for matching the buyers and suppliers in a synthetic market. The study illustrates the sensitivity of the outcome of various economic variables, such as clearing price, quantity, profits and social welfare, to different matching schemes in a bilateral computational setting. Based on seven different matching orders for the buyers and suppliers, our study shows that the results can vary dramatically for different pairing orders.

We study a class of discrete dynamical systems that is motivated by the generic structure of simulations. The systems consist of the following data: (a) a ®nite graph Y with vertex set f1Y F F F Y ng where each vertex has a binary state, (b) functions p i X F n 2 3 F n 2 and (c) an update ordering p. The functions p i update the binary state of vertex i as a function of the state of vertex i and its Y-neighbors and leave the states of all other vertices ®xed. The update ordering is a permutation of the Y-vertices. By composing the functions p i in the order given by p one obtains the sequential dynamical system (SDS DS): We derive a decomposition result, characterize invertible SDS DS and study ®xed points. In particular we analyse how many dierent SDS D S that can be obtained by reordering a given multiset of update functions and give a criterion for when one can derive concentration results on this number. Finally, some speci®c SDS DS are investigated.

Knowledge of fundamental traffic flow characteristics of traffic simulation models is an essential requirement when using these models for the planning, design, and operation of transportation systems. In this paper we discuss the following: a description of how features relevant to traffic flow are currently under implementation in the TRANSIMS microsimulation, a proposition for standardized traffic flow tests for traffic simulation models, and the results of these tests for two different versions of the TRANSIMS microsimulation.

Protecting secrets is a key challenge in our contemporary information-based era. In common situations, however, revealing secrets appears unavoidable, for instance, when identifying oneself in a bank to retrieve money. In turn, this may have highly undesirable consequences in the unlikely, yet not unrealistic, case where the bank's security gets compromised. This naturally raises the question of whether disclosing secrets is fundamentally necessary for identifying oneself, or more generally for proving a statement to be correct. Developments in computer science provide an elegant solution via the concept of zero-knowledge proofs: a prover can convince a verifier of the validity of a certain statement without facilitating the elaboration of a proof at all. In this work, we report the experimental realisation of such a zero-knowledge protocol involving two separated verifier-prover pairs. Security is enforced via the physical principle of special relativity, and no computational assumption (such as the existence of one-way functions) is required. Our implementation exclusively relies on offthe-shelf equipment and works at both short (60 m) and long distances (400 m) in about one second. This demonstrates the practical potential of multi-prover zero-knowledge protocols, promising for identification tasks and blockchain-based applications such as cryptocurrencies or smart contracts.

1. That is, preventing that Bob unknowingly obtains a falsified secret should Alice fail to cooperate honestly. 2. In order to get a computationally secure scheme under cryptographic assumptions, it would otherwise suffice to use a variation on oblivious transfer (attributed to Oded Goldreich in Ism) to allow "Alice to transfer to Bob exactly one out of two recognizable messages" so that neither has conaol over which message will be received.

We consider a situation where two parties, Alice and Bob, share a common secret string and would like to mutually check their knowledge of that string. We describe a simple and e cient protocol based on oblivious transfer to check mutual knowledge of a common string in such a way that honest parties will always succeed in convincing each other, while a dishonest party interacting with an honest party will have vanishingly small probability of convincing him. Moreover, a dishonest party gains only a very small amount of information about the secret string from running the protocol: whoever enters the protocol with no knowledge of the secret string would have to enter this protocol an exponential number of times in order to gain non-negligible information about the string.